WO2011017077A9 - Nanochannel-based sensor system with controlled sensitivity - Google Patents

Abstract

Disclosed are sensors, devices, systems, arrays of sensors and methods, including a sensing device that includes a sensor including one or more nanochannels constructed from semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with at least one analyte contained in a sample introduced to the sensor. The device also includes a controller to control sensitivity of the sensor to the presence of the at least one analyte.

Description

NANOCHANNEL-BASED SENSOR SYSTEM WITH CONTROLLED SENSITIVITY

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims benefit and priority to U.S. Provisional Patent Application No. 61/228,840, filed July 27, 2009, and entitled "Apparatus for Attenuation Control in Biosensing Applications Employing Semiconductor Nanoelectronic Device", U.S. Provisional Patent Application No. 61/228,844, filed July 27, 2009, and entitled "Multiplexed Panel Test Chips in Biosensing Applications Employing Semiconductor Nanoelectronic Device", and U.S. Provisional Patent Application No. 61/228,846, filed July 27, 2009, and entitled "Use of Redundant Measurement in Biosensing Application Employing Semiconductor Nanoelectronic Device to Improve Precision and Reliability," the disclosures of all of which are hereby incorporated by reference in their entireties.

STATEMENT OF GOVERNMENT SPONSORED SUPPORT

[0002] This invention was made with government support under grant No. W81XWH-04-1- 0578 awarded by the U.S. Army Medical Research and Materiel Command. The government has certain rights in the invention.

BACKGROUND

[0003] The present disclosure is related to the field of sensors used to sense chemical or biological species (also referred to as analytes), for example in an analyte solution (sample). More particularly, the present disclosure is related to nanoscale sensors, such as sensors implemented using semiconductor devices (e.g., FET transistors), or similar small-scale electrical devices, as sensitive transducers to convert chemical activity of interest into corresponding electrical signals representative of the chemical activity.

[0004] US Patent 7,129,554 of Lieber et al. describes nanosensors which may be utilized for such purposes. The nanosensors may include of one or more nanowires which may have a tubular form. The nanowires can be functionalized at their surfaces to permit interaction with adjacent molecular entities, such as chemical species, and the interaction induces a change in a property (such as conductance) of the functionalized nanowire. This behavior serves as the basis for nanochannel-based nanosensors.

[0005] International patent publication WO 2008/063901A1 of Yu Chen et al, the content of which is hereby incorporated by reference in its entirety, describes a nanochannel based sensor system which may be used in a variety of sensing applications. Low doping of the silicon device make it suitable for the sensitive pH, glucose, ion, DNA, and biomarker measurements. International patent publication WO 2009/124111A1 to Mohanty et al, further describes a nanoscale glucose sensor. The sensor systems employ an array of field effect nanoelectronic devices having critical dimensions on the order of, in some embodiments, 100 nm or less, with surface functionalization to interact with a species of interest. Due to their nanoscale dimensions, the devices exhibit strong sensitivity to variations in surface charge arising from the functional chemical interaction. Sensors using nanoscale electrical transducers provide a solution towards minimizing device size for implantable device applications, while also reducing device cost. Also, when a so called "top-down" semiconductor manufacturing approach is used, additional benefits can be obtained, including easier integration with supporting electronics and scalable manufacturing.

[0006] A challenge facing most diagnostics systems is the tradeoff between achieving very high sensitivity and range. Often this tradeoff has to be made due to sensor saturation, an inherent technological limitation in most sensors. Current procedures to address this limitation require dilution of the specimen to ensure that sensor device does not saturate. This increases the complexity in laboratory handling, costs and even diminishes the performance of the tests with regard to sensitivity. There is a lot of value to providers, and laboratories for a diagnostics system that prevents or minimizes lab and specimen handling complexities by delivering high sensitivity and range without compromising on specificity and other quality measures. This simplification of lab handling is a big step in facilitating point-of-care because it avoids having to perform complex tests in a central lab. Solutions promoting point-of-care processing will result in reduced costs of diagnosis and increased access. Traditional detectors are generally not suitable for such applications. [0007] Additionally, because the human body is a highly complicated and intricate system, a single test is rarely sufficient for a confident clinical decision. There is a lot of value to patients, providers, and researchers to perform a combination of biomarker tests in parallel or multiplexed fashion, which may be used in clinical decision making. Multiplexed diagnostics devices have traditionally been plagued by poor sensor quality and lack of sensor flexibility. The lack of flexibility has often resulted in most point-of-care devices being single test instruments, or at best having limited multiplexing capabilities. Similar challenges exist for multiplexed devices in central laboratories, such challenges being mainly driven by high error rates in testing. Multiplexed microarrays can also be used in field applications such as pollution and toxicology applications.

SUMMARY

[0008] For many sensing applications, it is beneficial to employ sensors having high sensitivity to a species of interest. Sensors with high sensitivity can be used to detect much smaller amounts or concentrations of the species, which may be necessary or desirable in some applications, and/or such sensors can provide a high signal-to-noise ratio, and thus improve the quality of measurements that are taken using such sensors.

[0009] As described herein, silicon nanostructures (e.g., nanochannels) can be used to fabricate a field effect transistors (FET). In conventional FETs, lithographic methods are used to fabricate gates at the bottom, the top, or the side. In addition, the nanochannels' surfaces can be functionalized with specific receptor or antibody to interact with agents/species of interest. In a fluid, the ligand (or antigen) can bind to the receptor, which results in a change in the surface charge profile and the surface potential. Essentially, this binding behaves as a field effect. The conductance and the I-V characteristics of the nanochannel can therefore be used to characterize biomolecular binding— for instance, to determine concentration and binding dissociation constant. The present disclosure describes how characteristics of differential conductance dl/dV can be used for even higher sensitivity in the field effect due to biomolecular binding. In particular, dl/dV characteristics allow measurement at low bias, essential for avoiding electrolysis. [00010] In some embodiments, a sensor system is disclosed for detecting a chemical or biological species (analytes) in a sample which includes a sensing element (also referred to as "sensor," "nanoscale sensor," or "nanosensor") and a bias and measurement circuit. The sensing element includes one or more nanochannels, each nanochannel having an outer surface functionalized to chemically interact with the species to create a corresponding surface potential, and each nanochannel having a sufficiently small cross section to exhibit a shift of a differential conductance characteristic into a negative bias operating region by a shift amount dependent on the surface potential or the surface charge. In one embodiment, each nanochannel has a cross section of about 100 nm by 150 nm or smaller. Functionalization can be done according to standard protocols, including for example the use of enzymes such as urease (for urea sensing) or glucose oxidase (for glucose sensing), or antibodies and antigens.

[00011] In some embodiments, the bias and measurement circuits disclosed apply a bias voltage across two ends of the nanochannels, the bias voltage being sufficiently negative to achieve a desired dependence of the differential conductance of the sensing element on the surface potential of the nanochannels. This dependence has a steeply sloped region of high amplification which is substantially greater than a reference amplification exhibited by the sensing element at a zero-bias condition, thus achieving relatively high signal-to-noise ratio. The bias and measurement circuit measures the differential conductance of the sensing element and converts the measured differential conductance into a signal indicative of presence or activity of the species, for example by using a look-up table or alternative conversion mechanism reflecting a prior calibration operation. In some embodiments, applied gate voltage can be used to control a sensor's sensitivity. The bias and reference gate voltage can be used independently to control sensitivity.

[00012] Nanoscale Silicon-based FET devices show sensitivity, reliability, robustness and the sensor flexibility needed in multiplexed diagnostics microarrays. By developing and implementing the nanoscale devices on traditional top-down silicon, the reliability and robust quality of top-down Silicon semiconductor manufacturing processes can be improved and error rates in testing, both in point-of-care and central reference labs can be reduced. This innovation will directly result in increased effectiveness of each patient visit to a lab or clinic, reduced cost of diagnosis, and earlier diagnosis, treatment, and monitoring. Traditional detectors are not suitable for such applications. [00013] In one aspect, a sensing device is disclosed. The device includes a sensor including one or more nanochannels constructed from a semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with at least one analyte contained in a sample introduced to the sensor. The device also includes a controller to control sensitivity of the sensor to the presence of the at least one analyte.

[00014] Embodiments of the sensing device may include any of the features described in the present disclosure, as well as any one or more of the following features.

[00015] The one or more nanochannels of the sensor may be a gate structure of a field effect transistor (FET), and the connected electrodes include a drain and source of the FET.

[00016] The one or more nanochannels may be configured to operate in a negative source drain electric configuration. The sensitivity of the one or more nanochannels may be determined based on one or more of, for example, voltage applied to the one or more nanochannels, and analyte binding at the one or more nanochannels.

[00017] At least one of the one or more nanochannels may be treated with a functionalizing agent to functionalize surfaces of the at least one of the one or more nanochannels such that the functionalized surfaces of the at least one of the one or more nanochannels are configured to interact with the at least one analyte.

[00018] The functionalizing agent may include one or more of an analyte detection substance, and a reactive substance. The interaction may include a chemical interaction that varies one or more of, for example, conductance of the one or more nanochannels, and/or capacitance of the one or more nanochannels.

[00019] The sensing device may further include an analyte interface to receive and enable contact between the sample and the one or more nanochannels.

[00020] The analyte interface may be configured to receive one or more of, for example, a fluid, aerosol, and/or air.

[00021] The controller configured to control the sensitivity of the one or more nanochannels may be configured to cause voltage to be applied to at least one of the one or more nanochannels to cause conductance of the at least one of the one or more nanochannels to change. [00022] The controller configured to cause the voltage to be applied may be configured to cause one or more of, for example, increase the voltage applied to the at least one nanochannel to increase the conductance of the at least one of the one or more nanochannels, and/or decrease the voltage applied to the at least one nanochannel to decrease the conductance of the at least one of the one or more nanochannels.

[00023] The controller configured to control the sensitivity of the one or more nanochannels may be configured to cause a pre-determined voltage level to be applied to at least one of the one or more nanochannels at a pre-determined time instance.

[00024] The one or more nanochannels may have geometric configurations corresponding to a pre-determined sensitivity level to the presence of the at least one analyte.

[00025] The geometric configuration of the one or more nanochannels may be defined through top-down fabrication process.

[00026] The one or more nanochannels may have a critical dimension of less than 100 nm.

[00027] The at least one analyte may include one or more of, for example, antibody, nucleic acid, PNA, aptamer, ligand, receptor, protein, lipid, carbohydrate, other small molecule and/or biopolymer. A reactive agent used in functionaliztion of the at least one nanochannel may include one or more of, for example, antibody, nucleic acid, PNA, aptamer, ligand, receptor, protein, lipid, carbohydrate, or other small molecule and/or biopolymer. The analyte detection may be governed by one or more chemical associations between the at least one analyte and the reactive agent.

[00028] The sensitivity of the sensor may further be controlled by one or more of, for example, modulating an ionic strength of the sample, and/or adding at least one additive to the sample to control the ionic strength of the sample.

[00029] At least one of the one or more nanochannels may include a three-dimensional control surface defined by length, width and height dimensions, the three-dimensional control surface including a pre-determined surface area configuration.

[00030] The sensitivity of the sensor may further be controlled by applying a surface coating with pre-determined properties to the one or more nanochannels. [00031] The surface coating may include an AI₂O₃ insulation layer grown by atomic layer deposition.

[00032] The surface coating may include any of a group of specific inorganic materials used as an insulation layer for the purpose of affecting the sensitivity of the one or more nanochannels.

[00033] The sensitivity of the sensor may further be determined based on doping of a control surface layer composition.

[00034] In a further aspect, a nanoscale sensor is disclosed. The nanoscale sensor includes one or more nanochannels constructed from semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with at least one analyte contained in a sample introduced to the sensor. The nanoscale sensor is associated with a controllable sensitivity that is modulated based, at least in part, on controllable variable voltage applied to the nanoscale sensor.

[00035] Embodiments of the nanoscale sensor may include any of the features described in the present disclosure, including any of the features described above in relation to the sensing device, as well as any of one or more of the following features.

[00036] The nanoscale sensor may be coupleable to a controller to control sensitivity of the sensor to the presence of the at least one analyte.

[00037] In yet another aspect, a sensor system is disclosed. The system includes an array of multiple nanoscale sensors, each of the multiple nanoscale sensors including one or more nanochannels constructed from semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with at least one analyte contained in a sample introduced to the multiple sensors. The system further includes a controller to control sensitivity of at least one of the multiple sensors to the presence of the at least one analyte.

[00038] Embodiments of the sensor system may include any of the features described in the present disclosure, including any of the features described above in relation to the sensing device and the nanoscale sensor, as well as any one or more of the following features. [00039] The array of multiple sensors may be logically organized into a plurality of individually operable subsets of sensors. The system may further includes a controller operative to generate control signals to enable electrical operation of the subsets of the nanoelectronic devices, and a device selection unit operative, in response to the control signals, to enable electrical sensing operation of a selected at least one of the subsets of the sensors to generate respective sensing output signals.

[00040] Each subset of sensors may include at least one of the multiple sensors configured to be biased by a drain source voltage to control the at least one of the multiple sensors' characteristics.

[00041] The controller may be configured to control sensitivity of any one or more of the subsets of sensors to any of the at least one analyte.

[00042] The controller may further be configured to cause sampled operation of the sensors of the selected subset to achieve reduced power consumption as compared to continuous operation of the multiple sensors in the array.

[00043] The controller may further be configured to perform monitoring of at least one of the multiple sensors to determine accuracy of sensed output signals as being representative of actual analyte levels of the analyte.

[00044] The controller configured to control the sensitivity of the one or more nanochannels may be configured to cause voltage to be applied to at least one of the one or more nanochannels to cause conductance of the at least one of the one or more nanochannels to change.

[00045] In yet another aspect, a method is disclosed. The method includes analyzing a sample including at least one analyte, the sample introduced into a sensor that includes one or more nanochannels constructed from semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with the at least one analyte contained in the sample introduced to the sensor. The method further include controlling sensitivity of the sensor to the presence of the at least one analyte. [00046] Embodiments of the method may include any of the features described in the present disclosure, including any of the features described above in relation to the sensing device, the sensor and the sensor system, as well as any one or more of the following features.

[00047] The method may further include treating at least one of the one or more nanochannels of the sensor with a functionalizing agent to functionalize surfaces of the at least one of the one or more nanochannels such that the functionalized surfaces of the at least one of the one or more nanochannels are configured to interact with the at least one analyte.

[00048] Controlling the sensitivity of the sensor may include causing voltage to be applied to at least one of the one or more nanochannels to cause conductance of the at least one of the one or more nanochannels to change.

[00049] The sensor may be disposed in an array of multiple sensors logically organized into a plurality of individually operable subsets of sensors. The method may further include generating control signals to select at least one of the subsets of sensors, and selecting, in response to the generated control signals, the at least one of the subsets of the sensors to enable electrical sensing operation of the selected at least one of the subsets of sensors and to generate respective sensing output signals.

[00050] Each of the subsets of sensors may include at least one of the multiple sensors configured to be biased by a drain source voltage to control the at least one of the multiple sensors' characteristics.

[00051] In another aspect, a nanoscale sensor is disclosed. The nanoscale sensor includes an array of a plurality of nanoelectronic devices having respective control surfaces individually or collectively functionalized with at least one analyte reactive substance, one or more of the plurality of nanoelectronic devices is associated with a controllable sensitivity that is modulated based, at least in part, on controllable variable voltage applied to the one or more nanoelectronic devices. The sensor further includes a fluid material interface structure configured to enable contact between the control surfaces and a common volume of a material being measured. At least some of the plurality of nanoelectronic devices in the array are configured to perform multiple redundant measurements from two or more spatially distinct control surfaces. [00052] Embodiments of the sensor may include any of the features described in the present disclosure, including any of the features described above in relation to the sensing device, the first nanoscale sensor, the sensor system, and the method, as well as any one or more of the following features.

[00053] The plurality of nano electronic devices may include control nanochannels placed on a single chip, wherein the control nanochannels are associated with respective conductance channels configured to be controllably opened, and wherein the control nanochannels are operative in keeping reference gate voltage grounded, and applying a negative source drain voltage to enable opening of the respective conductance channels to make the respective conductance channels suitable for surface potential change measurement

[00054] The control nanochannels may be placed on the same chip and may further be configured to engage in performance monitoring of the nanoelectronic devices to ascertain how accurately the sensing output signals reflect an actual analyte level of analytes in the material being measured.

[00055] Binding may be measured by a conversion factor used to determine an equilibrium constant of an enzymatic step.

[00056] The binding may be measured by a conversion factor used to determine an "on" rate K_on, and/or and "off rate K_Qff of a binding between an analyte and the analyte reactive substance on the control surfaces.

[00057] Two or more markers measured by multiplexing may be applied to diagnosing cardiac failure as acute myocardial infarction versus unstable angina. The two or more markers measured by multiplexing applied to diagnosing cardiac failure as acute myocardial infarction versus unstable angina may include one or more of, for example, cardiac Troponin T, cardiac Troponin I, CK-MB, myoglobin, and/or BNF.

[00058] The two or more markers measured by multiplexing applied to diagnosing risk to cardiac disease or failure as acute myocardial infarction may be separately used to assess heart failure.

[00059] Two or more markers measured by multiplexing may be diagnostic for one or more of, for example, a cancer indication, a treatment response decision, or staging, and/or monitoring of cancer. The two or more markers may include one or more of, for example, PSA, CA 12.5, Her2, and/or ovarian cancer markers.

[00060] Two or more markers measured by multiplexing may be used to evaluate drug response susceptibility determine by one or more of, for example, SNP, mutation, a combinations of SNPs, DNA chromosomal deletions, amplifications, and/or copy number.

[00061] Two or more markers measured by multiplexing may be applied to one or more of diagnosing toxic proteins pathogens viruses or infectious agents in one or more of, for example, an emergency room environment, and/or point-of-care environment.

[00062] Two or more markers measured by multiplexing may be for the surveying of toxic agents, including one or more of, for example, surveying toxic agents to detect bioterrorism agents, and/or surveying toxic agents in food sources.

[00063] In a further aspect, a nanoscale sensor is disclosed. The nanoscale sensor includes an array of nanoelectronic devices including respective control surfaces, the array being configured to allow for intimate contact between the control surfaces and an antigen carrying bodily fluid, the array of nanoelectronic devices being logically organized into a plurality of individually operable subsets of the nanoelectronic devices, each subset biased by a drain source voltage to attenuate sensor characteristics, at least one of the subsets functionalized using an analyte detection substance to chemical interact with an associated biomarker. The sensor also includes selection circuitry operative in response to control inputs to enable electrical sensing operation of a selected one of the subsets of the nanoelectronic devices to generate respective sensing output signals, and controllable nanochannels associated with at least one of the subsets of the nanoelectronic devices, the controllable nanochannels operative to be actuated by control signals to enable electrical operation of the subsets of the nanoelectronic devices.

[00064] Embodiments of the nanoscale sensor may include any of the features described in the present disclosure, including any of the features described above in relation to the sensing device, the sensors, the sensor system, and the method, as well as any one or more of the following features. [00065] The controllable nanochannels may further be operative to engage in performance monitoring of the nanoelectronic devices to ascertain how accurately output signals sensing reflect actual analyte level of different analytes in the antigen carrying bodily fluid.

[00066] The control nanochannels may further be operative to engage in performance monitoring of the nanoelectronic devices to sense one or more of a binary determination, graded stepwise, or continuous distribution of analyte concentration

[00067] Two or more markers measured by multiplexing may be separately evaluated on one or more of the control surfaces, and the attenuation criteria may be set so that the measurements of the two analytes may occur at dynamic ranges that are not overlapping, and may be separated by logarithms of concentration and/or affinity.

[00068] In another aspect, a method to manufacture a nanoscale sensor array is disclosed. The method includes applying a pre-determined pattern of a plurality of nanoscale sensors to a semiconductor-based wafer, the pre-determined pattern of a plurality of nanoscale sensors including data for at least one nanoscale sensor representative of a pre-determined sensitivity to one or more analytes in a sample that is different from another pre-determined sensitivity of at least one other nanoscale sensor to the one or more analytes. The method further includes functionalizing at least one control surface of the plurality of nanoscale sensors on a resultant wafer with the applied pattern using an analyte detection substance to chemically interact with an associated biomarker. The pre-determined pattern further includes data for one or more of the plurality of nanoscale sensors associated with a controllable sensitivity that is modulated based, at least in part, on controllable variable voltage to be applied to the one or more of the plurality of the nanoscale sensors when a manufactured array is in use.

[00069] Embodiments of the method may include any of the features described in the present disclosure, including any of the features described above in relation to the sensing device, the sensors, the sensor system, and the method, as well as any one or more of the following features.

[00070] Applying the pattern may include one or more of, for example, etching out the wafer with an anisotropic reactive-ion etch (RIE) material based on the pre-determined pattern, and/or performing a lithography procedure based on the pre-determined pattern. [00071] The method may further include growing a layer of AI₂O₃ on control surfaces of the nanoscale sensors located on the resultant wafer with the applied pre-determined pattern.

[00072] Details of one or more embodiments are set forth in the accompanying drawings and in the description below. Further features, aspects, and advantages will become apparent from the description, the drawings, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

[00073] The foregoing and other objects, features and advantages will be apparent from the following description of particular embodiments of the present disclosure, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily drawn to scale, emphasis instead being placed upon illustrating the principles of various embodiments of the present disclosure.

[00074] FIG. 1 is a schematic diagram a sensor device used to detect analytes in a sample;

[00075] FIGS 2(a) - 2(d) depict a nanochannel-based sensing element of the sensor of FIG. 1;

[00076] FIG. 3 is diagram of a sensor employing an array of nanochannels;

[00077] FIGS. 4(a)-4(e) include a set of graphs depicting electrical characteristics of a nanochannel-based sensing element;

[00078] FIG. 5 includes schematic diagrams of a bias/measurement circuits;

[00079] FIGS. 6(a)-6(b) is a set of graphs of measured differential conductance of a biomolecular sensor as respective functions of time and anitbiotin concentration;

[00080] FIGS. 7(a)-7(d) is a set of graphs illustrating measured differential conductance of a biomolecular sensor as functions of time and sensor bias voltage;

[00081] FIG. 8 is a graph illustrating measured differential conductance of an urea sensor;

[00082] FIGS. 9(a)-9(b) is a set of graphs illustrating measured differential conductance change of a glucose sensor; [00083] FIGS. 10{a)-10(b) are schematic diagrams showing a sensor composed of an array of functional ized nanoelectronic devices, circuitry, and a sensing signal output, and a side-view of the chemical layers of a nanochannel;

[00084] FIGS. 1 1 (a)-l 1(b) are schematic diagrams of a sensor in a side-view, and top-view, illustrating the multiple nanochannels on a sensor;

[00085] FIG. 12 (12(a)-12(b)) is a diagram of a system for sensing biomarkers and an enlarged image view of a silicon sensor composed of multiple nanochannels;

[00086] FIGS. 13(a)-13(j) is an illustration of the dependence of the differential conductance change as the bias voltage, reference gate voltage and concentrations are varied. FIG. 13(a)- 13(b) illustrates the change in the differential conductance as the pH of the solution is at the values pH 4, pH 6, pH 8, pH 10, at different values of the gate voltage at -0.4 V, 0.0 V, +0.4 V, +0.6 V. FIG. 13(c)-13(f) shows the dependence of the differential conductance change introduced by 80 ng/mL of anitbiotin at different bias voltages ranging from 600 mV,-700, mV, -800 mV, and -900 mV. FIG. 13(g)-13G) shows the dependence of the differential conductance change introduced by 80 ng/mL of anitbiotin at different reference gate voltages ranging from 100 mV, 200, mV, 300 mV, and 400 mV.

[00087] FIG.14 (14(a)-14(d)) is a graphical representation of I/V data reads for a sensor;

[00088] FIG. 15 (15(a)-15(b)) is a graphical representation of the sensitivity of the electrical properties of the device as selected geometric parameters are varied;

[00089] FIG. 16 is a flow chart of a procedure to process chemical/biological analytes;

[00090] FIG. 17 is a schematic diagram of an example nanoscale sensor system;

[00091] FIG. 18 (18(a)-18(b)) is a photograph of a sensor having multiple nanochannels;

[00092] FIG. 19 is a schematic diagram of multiple sensors arranged in an array of nanosensor subsets;

[00093] FIG. 20 is a schematic diagram of an implementation to measure conductance in a nanosensor;

[00094] FIG. 21 is a table that illustrates a group of biomarker panels that may be measured with a multiplexed array of nanosensors;

[00095] FIG. 22 is a flow chart of a multiplexing measuring procedure; and [00096] FIG. 23 is a schematic diagram that illustrates surface chemistry functionalization of nanochannels for the purpose of attaching an antibody to measure an analyte.

DETAILED DESCRIPTION

[00097] Disclosed are systems, devices and methods, including a sensing device that includes a sensor including one or more nanochannels constructed from a semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with at least one analyte (also referred to as "agent" or "species") contained in a sample (also referred to as an "analyte solution") introduced to the sensor. The sensing device further includes a controller to control sensitivity of the sensor to the presence of the at least one analyte. In some embodiments, the controller configured to control the sensitivity of the one or more nanochannels is configured to cause voltage to be applied to at least one of the one or more nanochannels to cause conductance of the at least one of the one or more nanochannels to controllably change. In some embodiments, the one or more nanochannels of the sensors are the gate structure of a field effect transistor (FET), and the connected electrodes include the drain and source of the FET. In yet further embodiments, at least one of the one or more nanochannels is treated with a functionalizing agent to functionalize surfaces of the at least one of the one or more nanochannels such that the functionalized surfaces of the at least one of the one or more nanochannels is configured to interact with the at least one analyte.

Definitions

[00098] In the present disclosures, the following definitions are used.

[00099] "Analyte" in the context of the present disclosure encompasses, without limitation, proteins, nucleic acids, carbohydrates, lipids, and metabolites, together with their

polymorphisms, mutations, variants, modifications, subunits, fragments, protein-ligand complexes, and degradation products, protein-ligand complexes, elements, related metabolites, and other sample-derived measures. The "analyte" may also include any of the substances comprising the "analyte detector," "reactive agent," and/or "reactive substance," as defined below. [000100] "Analyte Detector," or alternatively "Reactive Agent" or "Reactive Substance," in the context of the present disclosure encompasses, without limitation, another analyte whose purpose is to measure the second analyte by capture, binding, affinity, chemical reaction, pH change, or by another means. An "analyte detector," "reactive agent," and/or "reactive substance" may be an antibody, nanobody, aptamer, polymer, receptor, ligand, and may include any of the substances comprising the "Analyte." Practically speaking, an

"analyte detector" will provide specificity to a molecular interaction.

[000101] "Analytical accuracy" refers to the reproducibility and predictability of the measurement process itself, and may be summarized in such measurements as coefficients of variation, and tests of concordance and calibration of the same samples or controls with different times, users, equipment and/or reagents. These and other considerations in evaluating new biomarkers are also summarized in Vasan, 2006.

[000102] "Attenuation" in the context of the present disclosure encompasses, without limitation, the ability to reduce or enhance the measured electrical signal to avoid for example saturation of the signal at high concentrations, or to provide for an appropriate gain, allowing analytes to be measured over a wide dynamic range without dilution or concentration protocols.

[000103] "Biomarker" in the context of the present disclosure encompasses, without limitation, proteins, nucleic acids, carbohydrates, and metabolites, together with their polymorphisms, mutations, variants, modifications, subunits, fragments, protein-ligand complexes, and degradation products, protein-ligand complexes, elements, related metabolites, and other analytes or sample-derived measures. Biomarkers can also include mutated proteins or mutated nucleic acids. Biomarkers also encompass non-blood borne factors or non-analyte physiological markers of health status, such as "clinical parameters" defined herein, as well as "traditional laboratory risk factors", also defined herein. Biomarkers also include any calculated indices created mathematically or combinations of any one or more of the foregoing measurements, including temporal trends and differences. Where available, and unless otherwise described herein, determinants which are gene products are identified based on the official letter abbreviation or gene symbol assigned by the international Human Genome Organization Naming Committee (HGNC) and listed at the date of this filing at the US National Center for Biotechnology Information (NCBI) web site. [000104] "Calibrator Marker" is an analyte that permits the determination of a quantity of a second analyte or biomarker present in a sample. The expression level of the calibrator marker being constant across a plurality of samples and (ii) from the expression being specific for said one or more chosen cell type(s). It is sufficient that the calibrator markers are constantly expressed across the set of samples under consideration. Nevertheless, it is envisaged that the calibrator markers are constantly expressed one or more chosen cell type(s) under most or all conceivable conditions. The term "constant per cell" means that each cell of one or more chosen cell type(s) expresses the same or substantially the same amount of transcript and/or protein of the calibrator marker. The term "specific for one or more chosen cell type(s)" in relation to expression designates calibrator markers whose detectable expression is confined or substantially confined to one or more chosen cell type(s). The term "chosen cell type(s)" may refer to a subset of the cell types present in the sample.

Alternatively, the chosen cell types may embrace all cell types present in the sample. In both cases, the chosen cell type(s) is/are (a) cell types for which calibrator markers are known. In case of a plurality of chosen cell types, these calibrator markers are constantly expressed in all chosen cell types, preferably at identical or substantially identical levels across the different cell types comprised in the set of chosen cell types.

[000105] "Clinical parameters" encompasses all non-sample or non-analyte biomarkers of subject health status or other characteristics, such as, without limitation, age (Age), ethnicity (RACE), gender (Sex), or family history (FamHX).

[000106] "Conductance" is defined, without limitations, as a measure of how freely electricity flows through an electrical element. In equations, conductance is symbolized by the uppercase letter G. The unit of conductance is the Siemens (abbreviated S).

[000107] "Control Surface" is a term meaning the exposed surface to an analyte detection strategy. In the present disclosure a "Control Surface" generally refers to the surfaces (e.g., three-dimensional surfaces) of nanochannels of the nanoscale sensors described in this disclosure.

[000108] "Device" in the context of the present disclosure includes, without limitation, the collection of nanochannels, nanosensors, and calibrating nanochannels, nanosensors, and nanowires connected to an electrical output and display [000109] "Enhancement" refers to a property of adjusting the amplitude of the measured electrical signal to amplify the response, to provide for an appropriate gain, allowing analytes to be measured over a wide dynamic range without dilution or concentration protocols, to optimize the signal-to-noise ratio for the appropriate dynamic range for the selected analyte.

[000110] "Field Effect", and "Field Effect Transistor", and "FET." In a Field Effect Transistor (FET), an electric field is used to control the electrical conductance between two terminals of a channel in a semiconductor, by regulating the flow of charge carriers in the channel. The electric field may be generated using a control, or gate electrode, or

spontaneously, or by altering the surface potential using electrochemical methods.

[000111] "FN" is false negative, which for a disease state test means classifying a disease subject incorrectly as non-disease or normal.

[000112] "FP" i_s false positive, which for a disease state test means classifying a normal subject incorrectly as having a disease.

[000113] A "formula," "algorithm," or "model" is any mathematical equation, algorithmic, analytical or programmed process, or statistical technique that takes one or more continuous or categorical inputs (herein called "parameters") and calculates an output value, sometimes referred to as an "index" or "index value." Non-limiting examples of "formulas" include sums, ratios, and regression operators, such as coefficients or exponents, biomarker value transformations and normalizations (including, without limitation, those normalization schemes based on clinical parameters, such as gender, age, or ethnicity), rules and guidelines, statistical classification models, and neural networks trained on historical populations. Of particular use in combining biomarkers are linear and non-linear equations and statistical classification analyses to determine the relationship between levels of biomarkers detected in a subject sample and the subject's responsiveness to chemotherapy. In panel and combination construction, of particular interest are structural and synactic statistical classification algorithms, and methods of risk index construction, utilizing pattern recognition features, including established techniques such as cross-correlation, Principal Components Analysis (PCA), factor rotation, Logistic Regression (LogReg), Linear Discriminant Analysis (LDA), Eigengene Linear Discriminant Analysis (ELD A), Support Vector Machines (SVM), Random Forest (RF), Recursive Partitioning Tree (RPART), as well as other related decision tree classification techniques, Shrunken Centroids (SC), StepAIC, Kth-Nearest Neighbor, Boosting, Decision Trees, Neural Networks, Bayesian Networks, Support Vector Machines, and Hidden Markov Models, among others. Other techniques may be used in survival and time to event hazard analysis, including Cox, Weibull, Kaplan-Meier and Greenwood models. Many of these techniques are useful either combined with a biomarker selection technique, such as forward selection, backwards selection, or stepwise selection, complete enumeration of all potential panels of a given size, genetic algorithms, or they may themselves include biomarker selection methodologies in their own technique. These may be coupled with information criteria, such as Akaike's Information Criterion (AIC) or Bayes Information Criterion (BIC), in order to quantify the tradeoff between additional biomarkers and model improvement, and to aid in minimizing overfit. The resulting predictive models may be validated in other studies, or cross-validated in the study they were originally trained in, using such techniques as Bootstrap, Leave-One-Out (LOO) and 10-Fold cross-validation (10-Fold CV). At various steps, false discovery rates may be estimated by value permutation according to techniques known in the art. A "health economic utility function" is a formula that is derived from a combination of the expected probability of a range of clinical outcomes in an idealized applicable patient population, both before and after the introduction of a diagnostic or therapeutic intervention into the standard of care. It encompasses estimates of the accuracy, effectiveness and performance characteristics of such intervention, and a cost and/or value measurement (a utility) associated with each outcome, which may be derived from actual health system costs of care (services, supplies, devices and drugs, etc.) and/or as an estimated acceptable value per quality adjusted life year (QALY) resulting in each outcome. The sum, across all predicted outcomes, of the product of the predicted population size for an outcome multiplied by the respective outcomes expected utility is the total health economic utility of a given standard of care. The difference between (i) the total health economic utility calculated for the standard of care with the intervention versus (ii) the total health economic utility for the standard of care without the intervention results in an overall measure of the health economic cost or value of the intervention. This may itself be divided amongst the entire patient group being analyzed (or solely amongst the intervention group) to arrive at a cost per unit intervention, and to guide such decisions as market positioning, pricing, and assumptions of health system acceptance. Such health economic utility functions are commonly used to compare the cost-effectiveness of the intervention, but may also be transformed to estimate the acceptable value per QALY the health care system is willing to pay, or the acceptable cost- effective clinical performance characteristics required of a new intervention. For diagnostic (or prognostic) interventions, as each outcome (which in a disease classifying diagnostic test may be a TP, FP, TN, or FN) bears a different cost, a health economic utility function may preferentially favor sensitivity over specificity, or PPV over NPV based on the clinical situation and individual outcome costs and value, and thus provides another measure of health economic performance and value which may be different from more direct clinical or analytical performance measures. These different measurements and relative trade-offs generally will converge only in the case of a perfect test, with zero error rate (a.k.a., zero predicted subject outcome misclassifications or FP and FN), which all performance measures will favor over imperfection, but to differing degrees.

[000114] "Measuring" or "measurement," or alternatively "detecting" or "detection," means assessing the presence, absence, quantity or amount (which can be an effective amount) of either a given substance within a clinical or subject-derived sample, including the derivation of qualitative or quantitative concentration levels of such substances, or otherwise evaluating the values or categorization of a subject's non-analyte clinical parameters.

[000115] "Nanochannel" refers to a single element within a nanoscale sensor.

[000116] "Nanoelectronic" refers to the scale of electrical conductance across surfaces of 1-999 nanometers

[000117] "Nanoscale sensor array" refers to an entire array manufactured on a continuous surface, and is also known as a 'chip' , a 'biochip', and commonly referred to as the whole chip

[000118] "Nanosensor" refers to a single element in the array where a separable measurement of FET and conductance is monitored.

[000119] "Nanowire" is a synonym to a "nanochannel."

[000120] "Negative predictive value" or "NPV" is calculated by TN/(TN + FN) or the true negative fraction of all negative test results. It also is inherently impacted by the prevalence of the disease and pre-test probability of the population intended to be tested. See, e.g., O'Marcaigh AS, Jacobson RM, "Estimating The Predictive Value Of A Diagnostic Test, How To Prevent Misleading Or Confusing Results," Clin. Ped. 1993, 32(8): 485-491, which discusses specificity, sensitivity, and positive and negative predictive values of a test, e.g., a clinical diagnostic test. Often, for binary disease state classification approaches using a continuous diagnostic test measurement, the sensitivity and specificity is summarized by Receiver Operating Characteristics (ROC) curves according to Pepe et al, "Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic, Prognostic, or Screening Marker," Am. J. Epidemiol 2004, 159 (9): 882-890, and summarized by the Area Under the Curve (AUC) or cstatistic, an indicator that allows representation of the sensitivity and specificity of a test, assay, or method over the entire range of test (or assay) cut points with just a single value. See also, e.g., Shultz, "Clinical Interpretation Of Laboratory Procedures," chapter 14 in Teitz, Fundamentals of Clinical Chemistry, Burtis and Ashwood (eds.), 4th edition 1996, W.B. Saunders Company, pages 192-199; and Zweig et al, "ROC Curve Analysis: An Example Showing The Relationships Among Serum Lipid And Apolipoprotein Concentrations In Identifying Subjects With Coronory Artery Disease," Clin. Chem., 1992, 38(8): 1425-1428. An alternative approach using likelihood functions, odds ratios, information theory, predictive values, calibration (including goodness-of-fit), and reclassification measurements is summarized according to Cook, "Use and Misuse of the Receiver Operating Characteristic Curve in Risk Prediction," Circulation 2007, 115: 928-935. Finally, hazard ratios and absolute and relative risk ratios within subject cohorts defined by a test are a further measurement of clinical accuracy and utility. Multiple methods are frequently used to defining abnormal or disease values, including reference limits, discrimination limits, and risk thresholds.

[000121] "Normalizing" in relation to expression data is common in the art and relates to a processing step of the raw expression data which renders the signal intensities of each gene comparable across multiple measurements. Expression levels of a particular gene may differ between samples for a variety of reasons. Reasons of particular relevance are different amounts of cells in the samples analyzed on the one side and different transcriptional activity of the gene(s) under consideration on the other side. While the former is generally not indicative of a distinct biological state of the samples being compared, the latter generally is. In case protein expression levels are monitored instead of or in addition to RNA expression levels, different transcriptional and/or translational activity may contribute to different protein expression levels. Meaningful analysis of expression data requires the two possible

contributions to changes in expression levels-amount of cells and/or RNA vs. transcriptional and/or translational activity to be disentangled. Normalization is a method for disentangling said contributions. Practically speaking, normalization is a transformation of the raw expression data such that the effect of different amounts of cells and/or of RNA is removed or substantially removed. Global normalization, a procedure well known in the art, for example involves (i) the determination of the average signal intensity across all genes whose expression is being measured and (ii) subsequent division of raw signal intensities by the average signal intensity obtained in step (i).

[000122] "Performance" is a term that relates to the overall usefulness and quality of a diagnostic or prognostic test, including, among others, clinical and analytical accuracy, other analytical and process characteristics, such as use characteristics (e.g., stability, ease of use), health economic value, and relative costs of components of the test. Any of these factors may be the source of superior performance and thus usefulness of the test, and may be measured by appropriate "performance metrics," such as AUC, time to result, shelf life, etc. as relevant.

[000123] "Positive predictive value" or "PPV" is calculated by TP/(TP+FP) or the true positive fraction of all positive test results. It is inherently impacted by the prevalence of the disease and pre-test probability of the population intended to be tested.

[000124] "Raw expression data" refers to expression data prior to normalization. For example, and in the case of expression data obtained from microarrays, raw expression data are the data obtained from the image processing of the scanned hybridized microarray.

[000125] "Risk" in the context of the present disclosure, relates to the probability that an event will occur over a specific time period, as in the responsiveness to treatment, and can mean a subject's "absolute" risk or "relative" risk. Absolute risk can be measured with reference to either actual observation post-measurement for the relevant time cohort, or with reference to index values developed from statistically valid historical cohorts that have been followed for the relevant time period. Relative risk refers to the ratio of absolute risks of a subject compared either to the absolute risks of low risk cohorts or an average population risk, which can vary by how clinical risk factors are assessed. Odds ratios, the proportion of positive events to negative events for a given test result, are also commonly used (odds are according to the formula p/(l-p) where p is the probability of event and (1- p) is the probability of no event) to no-conversion.

[000126] "Risk evaluation" or "evaluation of risk" in the context of the present disclosure encompasses making a prediction of the probability, odds, or likelihood that an event or disease state may occur, the rate of occurrence of the event or conversion from one disease state. Risk evaluation can also comprise prediction of future clinical parameters, traditional laboratory risk factor values, or other indices of cancer, either in absolute or relative terms in reference to a previously measured population. The methods of the present disclosure may be used to make continuous or categorical measurements of the responsiveness to treatment thus diagnosing and defining the risk spectrum of a category of subjects defined as being at responders or non-responders. In the categorical scenario, the systems, devices and methods of the present disclosure can be used to discriminate between normal and other subject cohorts at higher risk for responding. Such differing use may require different biomarker/calibrator marker combinations and individualized panels, mathematical algorithms, and/or cut-off points, but be subject to the same aforementioned measurements of accuracy and performance for the respective intended use.

[000127] A "sample" in the context of the present disclosure is a biological sample isolated from a subject and can include, by way of example and not limitation, tissue biopies, whole blood, serum, plasma, blood cells, endothelial cells, lymphatic fluid, ascites fluid, interstitital fluid (also known as "extracellular fluid" and encompasses the fluid found in spaces between cells, including, inter alia, gingival crevicular fluid), bone marrow, cerebrospinal fluid (CSF), saliva, mucous, sputum, sweat, urine, or any other secretion, excretion, or other bodily fluids.

[000128] "Semiconductor" is a substance, usually a solid chemical element or compound, that can conduct electricity under some conditions but not others, making it a suitable medium for the control of electrical current. Its conductance varies depending on the current or voltage applied to a control electrode,

[000129] "Sensitivity" refers to the attenuation/enhancement features of the sensor so that a minimal characteristic level of an analyte may be reproducibly detected. A device may have different sensors for different analytes, where each analyte may be measured in a distinct sensitivity range.

[000130] "Statistical Sensitivity" is calculated by TP/(TP+FN) or the true positive fraction of disease subjects, and refers to the statistical parameter from marker or analyte evaluations.

[000131] "Signal intensity" as used herein refers to a measured quantity indicative of the expression level of an analyte. Preferably, the signal intensity is proportional to the amount of the analyte whether it be a protein, nucleic acid, lipid, glycolipid, polymer, peptide, cell, virus, or small molecule. Depending on the analyte detector used, which is further detailed below, the signal may be recognized by the Field Effect Transition and conductance process, or radiation and/or particles emitted by a radioactive label or dye (quantum dots).

[000132] "Specificity" is calculated by TN/(TN+FP) or the true negative fraction of nondisease or normal subjects, and refers to the statistical parameter from marker or analyte evaluations..

[000133] By "statistically significant", it is meant that the alteration is greater than what might be expected to happen by chance alone (which could be a "false positive"). Statistical significance can be determined by any method known in the art. Commonly used measures of significance include the p-value, which presents the probability of obtaining a result at least as extreme as a given data point, assuming the data point was the result of chance alone. A result is often considered highly significant at a p-value of 0.05 or less.

[000134] A "subject" in the context of the present disclosure is generally a mammal. The mammal can be a human, non-human primate, mouse, rat, dog, cat, horse, or cow, but are not limited to these examples. Mammals other than humans can be advantageously used as subjects that represent animal models of cancer. A subject can be male or female.

[000135] "TN" is true negative, which for a disease state test means classifying a non- disease or normal subject correctly.

[000136] "TP" i_s rue positive, which for a disease state test means correctly classifying a disease subject.

Nanoscale Sensors

[000137] With reference to FIG. 1, a schematic diagram of a sensor 10 (also referred to as "sensing element," "nanosensor," or "nanoscale sensor") configured to be is exposed to chemical or biological analyte (also referred to as agent or species) in an analyte solution (sample) 12 is shown. The sensor 10 has connections to a bias/measurement circuit 14 that provides a bias voltage to the sensor 10 to measure the value of "differential conductance" (i.e., small-signal change of conductance with respect to bias voltage) of the sensor 10. As will be described in greater details below, in some implementations, sensitivity of the sensor to the presence of the chemical/biological analytes that the sensor is configured to detect is controlled, at least partly, by adjusting the gate voltage coupled to the sensor (sensing element) in some pre-determined manner, using, for example, a controller. For example, applying a controlled voltage (e.g., at a pre-determined level) to a nanochannel of the sensing element (the nanochannel defining the gate element of a FET device) varies one or more of the electrical properties of the sensing element. For example, controlled application of voltage to the nanochannel causes the conduction channel formed in FET-based nanosensor to be extended or squeezes, thus enabling the sensor's sensitivity to be controlled by adjustment of the gate voltage. By applying a pre-determined voltage to the gate to the cause the widening or narrowing of the conduction channel, the sensitivity of the sensing element (sensor) can be controlled in a pre-determined manner (e.g., changes to the conductance gradient of the conduction channel resulting from chemical/biological interactions with surface charges will be more pronounced or attenuated in a pre-determined way depending on how the controlled application of voltage to sensor modified the conduction of the channel).

[000138] In some implementations, the differential conductance of the device is measured by applying a small modulation of bias voltage to generate a value of an output signal (OUT) that provides information about the chemical or biological species of interest in the sample 12, for example a simple presence/absence indication or a multi-valued indication representing a concentration of the species in the sample 12. Each sensor 10 includes, in some embodiments, one or more conductor structures (e.g., elongated ridges or wires) of a semiconductor material such as silicon, which may be doped with impurities to achieve desired electrical characteristics. Such structures are referred to as nanochannels, which are conductive structures (i.e., electrical conductive channels) that can interact with

analytes/species within a sample introduced to the device, such as a fluid containing one or more analytes to be measured. Thus, each sensing element include one or more "nanoscale" nanochannels, with the nanochannels including dimensions sufficiently small that

chemical/electrical activity on the channels' surfaces can result in a more pronounced effect of electrical operation than can be achieved with larger devices. In some embodiments, the sensor has one or more constituent nanochannels having a cross-sectional dimension of less than about 150 nm (nanometers), and even less than about 100 nm. Examples of suitable nanostructures that can be used in implementations of the nanoscale sensors include nanowires, nantubes nanocrystals, nanocantilevers, quantum dots, etc. Such nanostructure are attractive as biosensors because the critical dimensions of the nanostructures, such as the diameter of the nanowire, are comparable to the sizes of biological and chemical species. The detection sensitivity is therefore greatly enhanced as the signal can be effectively transduced because of large surface-to-volume ratio. In a nanoscale conductor, the surface-to-volume ratio is large because of the structure's size, so its electrical properties, such as conductance, capacitance, etc., are significantly influences by surface contributions. Therefore, the presence of, for example, charged proteins on the surface of an active nanostructure (e.g., nanowire) can induce a relatively large fractional change in the nanostructure conductance to enable relatively easy detection.

[000139] The surfaces of the sensing element 10 may "functionalized" by a series of chemical reactions to incorporate receptors or sites for chemical interaction with the species of interest in the analyte solution 12. Thus, the surfaces of the nanochannels are chemically or biologically treated to deposit chemical/biological agent with predetermined

chemical/biological characteristics that when such treatment agents come in contact with particular species in the analyte solution introduced to a sensor, the interaction between the deposited agent and its intended analyte species results in a change to the conductance of the nanochannel on which the agent is deposited, thus causing a change in the voltage detected by the sensor. The detected voltage is proportional to the concentration of the analyte species that interacted with the functionalized element. Particularly, as a result of this interaction, the charge distribution or "surface potential" of the surface of the sensor 10 changes in a corresponding manner, and this change of surface potential alters the conductivity of the sensing element 10 in a way that is detected and measured by the bias/measurement circuit 14.

[000140] With reference to FIG. 23, in some implementation, functionalization of the nanochannels is performed by growing an AI₂O₃ layer by, for example Atomic Layer

Deposition to a desired thickness to cover the whole sample. The sensor surface may be modified by 3-aminopropyl triethoxysilane solution (5%) in methanol (5% DI water) for two hours and then silane is activated by glutaraldehyde (10% in 0.1 M NaCl solution) for 10 minutes, the sample is modified by the desired antibody or probe molecule for 2 hours. The surface is then passivated by ethanolamine (10% in 100 mM NaCl solution) for 2 hours, or by other molecules to control non-specific binding events. [000141] In some embodiments, the number of binding sites per nanochannel can be varied from as few ten binding sites, set by the limit of detection, to near saturation coverage, of about one antibody per 10 nm , corresponding to about sixty thousand molecules for each surface of a typical nanochannel, which in turn corresponds to nearly one hundred and fifty (150) thousand to one hundred and eighty (180) thousand antibodies for each three- dimensionally patterned nanochannel. In practice, the coverage may be reduced from the saturation value, in order to ensure that the target binding events do not interfere with each other.

[000142] In some embodiments, the sensor 10 is a field-effect device, i.e., its channel conductivity is affected by a localized electric field related to the surface potential or surface charge density. Measured differential conductance values are converted into values representing the property of interest (e.g., the presence or concentration of species), based on known relationships as may have been established in a separate calibration procedure. FET devices include a large family of devices, including metal-oxide FET (also called insulated gate field-effect transistor), junction field-effect transistors (JFETs), and so on.

[000143] With reference now to FIG. 2, various diagrams of the configuration of an example sensing element 10, implemented using a field effect transistor (FET) are shown. As depicted in the side view of FIG. 2(a), a silicon nanochannel 16 extends between a source (S) contact (also referred to as source electrode) 18 and a drain (D) contact 20 (also referred to as a drain electrode), all implemented on an insulating oxide layer 22 above a silicon substrate 24. FIG. 2(b) is a top view showing the narrow elongated nanochannel 16 extending between the wider source and drain contacts 18 and 20, which are formed of a conductive material such as, for example, gold-plated titanium. FIG. 2(c) is a cross- sectional view in the plane C-C of FIG. 2(a), and Figure 2(d) is a cross section diagram of the nanochannel 16 shown in greater detail. In the illustrated embodiment, the nanochannel 16 includes an inner silicon member 26 and an outer oxide layer 28 such as aluminum oxide.

[000144] With reference to FIG. 3, a schematic diagram of an array 10 of sensors lOa-d that each includes a plurality of nanochannels. In the illustrated example of FIG. 3, the sensors lOa-d are arranged into four sets 30a-d, each set including approximately twenty parallel nanochannels 16 extending between respective source and drain contacts 18 and 20. By utilizing multiple nanochannels (such as a nanochannel 16 shown in FIG. 2) to constitute each sensing element, greater signal strength (current) may be obtained from each sensing element (upon interaction with a species that the sensors' functionalized nanochannel are configured to sense) and thus the signal-to-noise ratio of each of the sensing element 10 may be improved to enhance its sensitivity. Each of the sets 30a-d constituting the respective sensors lOa-d may be functionalized differently so as to react to different species which may be present in the analyte solution 12, enabling an assay- like operation. In such

configurations, each of the sensors lOa-d has separate connections to the bias/measurement circuit 14 to provide for independent operation.

[000145] The sensing element 10 may be made by a variety of techniques employing generally known semiconductor manufacturing equipment and methods. Generally, a "top- down" fabrication approach may be used. An advantage of such an approach is the relative substantial control the approach offers over physical and electronic degrees of freedom. The geometry and alignment of the nanowire can be fully controlled by e-beam lithography and standard/conventional semiconductor processing techniques. Furthermore, physical gate electrodes next to the nanowire can be fabricated with complete (or near complete) control over their locations and sizes. These local gate electrodes enable controlled accumulation or depletion of surface charge carriers on the nanowire and provide the ability to tune the nanowire conductance necessary for the optimization of the detection sensitivity. In such configurations, the nanowire pH sensor regains the control and the benefits, usual in standard electronic FET devices.

[000146] In some embodiments, Silicon-on-Insulator (SOI) wafers are employed. For example, a starting SOI wafer may have a device layer thickness of 100-300 nm and oxide layer thickness of 300-500 nm (e.g., 380 nm), on a 600 μιη boron-doped substrate, with a device-layer volume resistivity of 10-20 Ω-cm. After patterning the nanochannel channels and the electrodes in separate steps, the structure is etched out with an anisotropic reactive-ion etch (RIE). This process exposes the three surfaces (top and sides) of the silicon nanochannels 16 along the longitudinal direction, resulting in increased surface-to-volume ratio.

Additionally, a layer of AI₂O₃ (5 to 15 nm thick) may be grown by atomic layer deposition (ALD). Selective response to specific biological or chemical species may then be realized by functionalizing the nanochannels 16 following standard protocols. In subsequent use, it may be convenient to employ a machined plastic flow cell fitted to the device and sealed with silicone gel, with the sensor 10 bathed in a fluid volume of about 30 μί, for example, connected to a syringe pump. Additionally, the sensor 10 may include other control elements or "gates" adjacent to the nanochannels 16. In some embodiments, a conductive element ("top gate") may be formed along the top of each nanochannel 16. Such a top gate may be useful for testing or characterization, and, in some embodiments, to provide a way to tune the conductance of the sensing element in a desired manner. Additionally and/or alternatively, one or more "side gates" may be utilized for similar purposes, these being formed alongside each nanochannel 16 immediately adjacent to the oxide layer 28.

[000147] FIG. 4 shows salient electrical characteristics of a nanochannel-based sensor 10, employing nanochannels having a height or thickness of 100 nm. FIGS 4(a) and 4(c) are curves of drain-source current I_ds versus drain-source voltage V_ds for different "gate" voltages V_g . The curves of FIG. 4(a) are for a device having nanochannels 16 of width W = 350 nm, and the curves of FIG. 4(c) are for a device having nanochannels 16 of width W = 80 nm. FIGS. 4(b) and 4(d) are curves of the "differential conductance" dWdV_ds versus V_ds for devices having width W of 350 nm and 80 nm respectively. FIG. 4(e) is a plot of the magnitude of the value of V_ds at which the peak of the dWdV_ds curve occurs as a function of width W

[000148] The curves of FIG. 4 are characteristic of a device similar to that of FIG. 2 but including a top gate located immediately above the nanochannel 16, separated from the silicon portion 26 by the aluminum oxide 28. The voltage on this gate was varied by an external DC source to simulate the effect of a change of surface potential caused by interaction of a functionalized nanochannel 16 with a species of interest. In FIG. 4, current values are given in micro-Amperes (μΑ) and differential conductance in micro-Siemens (μ8). It is believed that small changes in the conductance of the device (related to the inverse of the source-drain resistance) are best measured by considering the differential conductance dl/dV (e.g., as in FIGS. 4(b) and 4(d)) with the derivative taken at constant V_g. This method yields

measurements at higher signal-to-noise ratio compared to using a digital method of computing derivatives from I_ds and V_ds separately.

[000149] With continued reference to FIGS. 4(a) and 4(b), for the 350 nm device it is observed that the I_{ds ds} characteristic of this device is substantially independent of the gate voltage V_g for large negative source-drain bias, V_ds less than -2V. As seen in FIG. 4(b), the peaks of the d dVds curves for all values of V_g is in the immediate neighborhood of Vd_s = 0. The actual peak value of d dV_ds increases by about a factor of two as V_g increases from -I V to +3 V.

[000150] FIGS. 4(c) and 4(d) illustrate the markedly different characteristics of a sensing element 10 using nanochannels 16 having a width W of 80 nm. The I_{ds ds} characteristic is much more heavily dependent on V_g. For example, the curves for one-volt increments of V_g are separated by approximately 0.7-volt increments of Vd_s. FIG. 4(d) illustrates a

corresponding separation of the peaks of the dWdVds curves. FIG. 4(e) captures the width dependence in a slightly different form, showing the relationship between the magnitude of Vds at the dlds/dVds peak as a function of width W and, in the inset, the d dVds curves themselves as a function of W for V_g =0. It is believed that the spreading or shifting of the differential conductance peaks illustrated in Figures 4(c) - 4(e) is due at least in part to the reduction of device size to below a certain threshold such that the effect of surface potential becomes much more pronounced. Mathematically, the surface-to-volume ratio of a generally rectangular solid is approximately inversely proportional to a transverse dimension such as W, and thus smaller (narrower) devices exhibit greater sensitivity to surface charge than larger (wider) devices. For the nanochannels 16, this sensitivity is in the form of differential conductivity as a function of surface charge or surface potential. Below a threshold width, which in the illustrated embodiment lies in the range of 150 - 200 nm, the locations of the peaks of the dWdVds curves are shifted to different values of V_Js as a function of the surface potential. Additionally, the appearance of the conductance peak might be related to the formation of a Schottky barrier by contact between the source/drain contacts 18 and 20 (which are gold/titanium in some embodiments) and low-doped silicon of the nanochannels 16, in combination with the reduced cross-sectional dimensions of the nanochannels 16.

[000151] With reference to FIG. 5, circuit diagrams of example implementations of bias/measurement circuits, such as the bias/measurement circuit 14 depicted in FIG. 1, are shown. FIG. 5(a) depicts a first implementation of a bias/measurement circuit that includes conductors 32-1 and 32-2, which are connected to first and second ends (e.g., source S and drain D, respectively) of a sensing element, such as the sensing element 10. For convenient reference, the locations and polarities of V_Js and I_ds are shown. A DC source 34 generates a DC voltage Vbi_as, and an AC source 36, such as a lock-in amplifier, generates a small AC measurement voltage V_meas- These voltages are added together by a summing amplifier circuit 38 implements, in shown example, using an operational amplifier. Amplifier circuit 40 completes the circuit between the sensor and the AC source 36, which thus causes a resultant voltage level to form at the output terminal of the amplifier circuit. The voltage level 50 is representative of the measure of dWdV_ds (labeled dl/dV in FIG. 5), and thus of the conductance of the gate of the nanoscale sensing element (which, as described herein, is based on the extent of the chemical/biological interaction between the functionalized nanochannels of the sensing elements and a particular species in the analyte that the nanochannels are configured to sense). This dl/dV value can be provided as an input to a further module, implemented as a separate circuitry, such as a look-up table (LUT) 42, to determine, based in the value of dl/dV the identity of the analyte species of interest and/or its detected quantity, corresponding to the particular dl/dV value. The entries/values stored in the LUT 42 may have previously determined by performing a separate calibration procedure at an earlier time.

[000152] FIG. 5(b) depicts another implementation of a bias/measurement circuit. The measurement circuit includes a small AC modulation (provided by an EG&G 5210 lock-in amplifier), superimposed on the DC bias across the nanowire (provided, for example, by a Keithley 2400 source meter). The AC modulation and the DC bias are added by a non- inverting summing circuit, integrated with the preamplifier circuit (with ¾=220 kΩ and R_m=2.2 ΜΩ). The entire device may be placed in an RF-shielded aluminum box to prevent noise pickup. Differential conductance measurements are done by sweeping the DC bias at constant AC modulation amplitude, and measuring the response with the lock-in amplifier, referenced to the AC signal frequency.

[000153] The implementation of FIG. 1 may be useful in a variety of sensing

applications, ranging from simple pH detection to the sensing of large proteins and even viruses. Several applications are described below as examples. It is to be noted that the descriptions are examples only, and that variations and alternatives may be employed.

[000154] FIGS. 6 and 7 illustrate an application to detection of proteins or similar biomolecules. The underlying data was obtained in experiments in which the surface of the nanochannels (such as the nanochannel 16 depicted in FIG. 2) was functionalized with biotinylated bovine serum albumin (BSA), also referred to as "biotin". The sensor 10 was composed of 20 parallel nanochannels 16 of width W = 250 nm, and biased at Vd_s = -0.5 V. The analyte included a buffer solution containing 1 mM NaCl and 1 mM phosphate. FIG. 6(a) shows the value of dl/dV over time as the concentration of antibiotin in the buffer is varied. FIG. 6(b) shows a corresponding curve of the change of differential conductance (AdI/dV) as a function of antibiotin concentration, where the "change" is the difference between a measured value of dl/dV at the specified concentration and a measured value of dl/dV for the buffer solution itself (no antibiotin present). It can be shown that the dissociation constant K_eq for the binding reaction can be derived from these data. The equilibrium constant is one of the signature standard values that can be used to characterize and identify the analyte.

[000155] FIG. 7 shows additional data of interest. FIGS. 7 (a) and 7(b) each show dl/dV as a function of time, first for the buffer itself ("buffer") and then for the buffer with 100 ng/mL of antibiotin ("antibiotin"). FIG. 7(a) exhibits operation at a bias voltage Vd_s of - 0.4 V, whereas FIG. 7(b) exhibits operation at a bias voltage Vd_s of -0.9 V. It can be seen that operation at the bias voltage of -0.9 V exhibits substantially greater signal-to-noise ratio, due to the greater sensitivity or "amplification" that results from the above-described shifting of dl/dV. FIG. 7(c) shows the differential conductance change introduced by biotin (1) at different values of Vd_s at a constant reference gate voltage V_rg =0.3 (squares and bottom scale), and (2) at different values of V_rg and a constant V_ds = 0 (triangles and top scale). The inset shows the signal-to-noise ratio of the device as a function of V_ds. Fig. 7(d) superimposes two curves, one showing the change of differential conductance versus Vd_s caused by 5 mV of change of the reference gate voltage V_rg (squares and left scale), and the other showing the change of differential conductance versus V_ds caused by 100 ng/mL of antibiotin solution (triangles and right scale). This data suggests that the change of surface potential caused by 100 ng/mL of antibiotin is similar in effect to a change of about 7.2 mV of reference gate voltage. Relationships such as shown in FIG. 7(d) provide a basis for calibration.

[000156] In some embodiments, the biotin-antibiotin binding mechanism may be replaced by other molecular binding mechanisms depending on the biomolecule of interest. In order to exploit different binding mechanisms, it is necessary to functionalize the surface of the nanochannels accordingly (i.e., to deposit material that will provide the desired binding locations and activity). For example, as noted in some embodiments, surface functionalization can be performed in the manner depicted in FIG. 23. [000157] In some embodiments, the disclosed sensors can be applied in the field of genomics, for detecting nucleic acid sequences, in the field of proteomics for detecting proteins and peptides, and in the field of metabolomics for detecting metabolites and small molecules.

[000158] Another application of the disclosed sensor is in the detection of urea in samples. In one experiment, a sensing element 10 with an array of twenty parallel nanochannels 16, each being 150 nm wide, 100 nm thick, and 6 um long. The device was covered with 8 nm of AI₂O₃ grown by atomic layer deposition. The surface was first modified by treatment with (3-Aminopropyl) Triethoxysilane (APTES) (3% in ethanol with 5% water). The surface was then functionalized by depositing 2% urease in 20mM NaCl solution (5% glycerol, 5% BSA) and maintaining in glutaraldehyde vapor for 40 minutes, then air-drying. Urea samples are in 50 mM NaCl solution.

[000159] FIG. 8 shows results for various concentrations of urea in solution. The device was biased at V_ds = -0.6 V. As shown, the differential conductance varies from about 160 nS to about 40 nS as the urea concentration increases from about 0.0 to about 0.7 mM.

[000160] It should be noted that the APTES-treated sensing element 10 can itself be used as a pH sensor. Experiments have shown an almost linear negative relationship between dl/dV and pH, with dl/dV ranging from 380 nS to 350 nS as pH changes from 2 to 10. The disclosed sensor is also applicable to the detection of glucose in samples. In one experiment, oxide-covered nanochannels were functionalized with glucose oxidase deposited in acetic chloride (50 mM) buffer solution (5% glycerol, 5% BSA, pH 5.1). Glucose samples were in solution with 50 mM NaCl and 50mM of potassium ferricyanide.

[000161] FIG. 9 shows the results for various concentrations of glucose in a solution. FIG. 9(a) shows a saturation effect for concentrations above about 10-20 mM. FIG. 9(b) shows the performance of the device over several days. As is evident, device performance degrades over time, which may be due to deactivation of the glucose oxidase enzyme on the surface. Such changes in device performance over time should generally be given

consideration in uses of the device.

Sensitivity Control [000162] In some embodiments, sensitivity control for individual sensors of an array of sensors (e.g., a chip) is implemented. For example, in some embodiments, tunable application of voltage to a nanosensor (e.g., gate voltage, bias voltage, reference voltage) in a controlled pre-determined manner (e.g., based on a pre-determined relationship between the applied voltage and resultant sensitivity) can be used to achieve individual sensitivity control of each sensor or group of sensors in, for example, a nanoscale FET -based sensor array.

[000163] As explained above, in the present disclosure, the conductance of the FET- implemented sensor may be controlled in several ways. One way is to increase the signal-to- noise ratio while maintaining sensitivity (resulting from small surface-to-volume ratio) using parallel structures, such as parallel wires, ridges, etc., to implement individual sensing elements.

[000164] Under that approach, nanochannels that include a three-dimensional control surface defined by length, width and height dimensions, with a pre-determined surface area configuration, may be fabricated. The three-dimensional structure of the control surface of the nanostructures increases the surface-to-volume ratio, and thus increase the sensitivity of the nanochannels. Control of the three-dimensional configuration of the nanostructures (and thus of their surface-to-volume ratio) can be implemented at the time of sensor manufacturing. For example, when manufacturing a chip with sensors having nanochannels, during an etching or lithography procedures (as described herein) to shape the surfaces of the nanochannels, the surfaces can be shaped, e.g., according to a pre-determined geometric pattern, to carve particular surface features/topography (including hills and valleys) that would enable achieving a desired surface-to-volume ratio and/or sensitivity for the corresponding sensor.

[000165] Another way to control sensitivity of nanoscale sensors is to change the conductance of nanochannels (open or close the channels). The conductance channels need to be opened to detect any current flow. At the dopant level of the devices and systems described herein, channels will have a small conductance (corresponding to a few ΜΩ of resistance) at relatively low gate voltage levels.

[000166] Accordingly, in some embodiments, e.g., for nanoscale sensors described herein, one way to increase conductance of the nanochannels is to apply a sufficiently large back gate voltage to open the conductance channel, but without causing the conductance in the channel to be so high that the sensors are too sensitive to surface binding sites. Conversely, at very low conductance values, the current may be too small to measure without introducing a lot of noise, so the sensors may again performs poorly. Accordingly, implemented sensors will generally have an associated optimal value, or range of values, of conductance (and thus have an optimal value, or range of values, of applied tuning voltage, such as gate voltage) at which the sensors perform optimally, or near optimally, in terms of sensitivity.

[000167] There are two potentially adverse effects that need to be taken into account when applying a voltage to controllably open or close the conduction channel. First, power consumption of the sensing element increases. Second, the use of a large back gate voltage makes it hard to control the device locally, which is important for the micro/nano scale devices. Controlling voltage can also be applied through a reference gate in the solution, but then electrolysis might be introduced at large values of the voltage difference.

[000168] With reference now to FIG. 10, a schematic diagram of a sensor system 100 is shown. The system 100 includes at least one device 110 which includes an array 112 of functionalized nanoelectronic sensors (sensing elements). The system also includes one or more sensor selection units 114 (such units including circuitry implemented with or without a processor-based device) and a controller 116 (such a controller including circuitry

implemented with or without a processor-based device) to control the selection units, which, in response to control signals received from the controller, are configured to individually control the controllable sensitivity (attenuation/enhancement5) for the various nanoscale sensors in the array 112 to thus control their operations (e.g., individually disable, enable or otherwise tune the sensors). The device 110 receives operating power via a power input 118 and includes an interface to external higher level control 120 as well as a terminal to which sensing output signals 122, corresponding to measured analyte concentration levels (e.g., antigen concentration levels) as sensed by sensors within the device 110, are provided. The individual sensors within the array 112 may be implemented in a manner similar to the sensor 10 depicted, for example, in FIGS. 1 and 2, and may be configured to have controllable sensitivity (e.g., through a controllable gate biasing voltage mechanism, a predetermined or modifiable structural configuration that can affect the nanoscale sensors' sensitivity to the detection of chemical/biological species in a sample, etc.)

[000169] Thus, the array 112 includes multiple individual nanoelectronic (nanoscale) sensors, arranged to be selectively activated by the selection units 114 in response to control signals from the controller. An array (chip) may have, for example, 1-10, tens, hundreds, thousands, or more, sensors per array. The controller is configured to, among other things, individually control the sensitivity of the nanoelectronic devices by, for example, controlling the voltage applied to the gate structures of the sensors (as noted, the gate structure may comprise one or more nanochannels whose number and structure may be configured to achieve a desired signal to noise ratio and/or detection sensitivity).

[000170] FIG. 10(b) shows a schematic diagram of one particular realization a sensor (sensing element), which includes the Source, the Drain of the electrical nanochannel. An Ag/AgCl reference gate electrode in the analyte solution is shown. Other configurations to incorporate the reference electrode on the surface of the chip to, facilitate electrical connections, may be used. In some implementations, silver or gold electrodes (or other types of electrodes) may be lithographically incorporated on the chip surface itself. This has the advantage of making the electrical connections be part of the semiconductor device. It is to be noted that such implementations may require more complex calibration procedures to account for electrode potentials at the metal surface which act as offsets.

[000171] The unit of activation in an array of sensors is referred to as a "subset", and each such subset of the array of nanoelectronic devices may range from as few as one to perhaps tens, hundreds (or more) sensors, depending on a variety of factors including signal to noise considerations, reliability, need for control or reference devices in each subset for greater accuracy/precision, etc. In some embodiments, each subset has in the range of 3 to 10 nanoscale sensors. The overall number of devices (sensors) may vary widely in different embodiments, from as few as 10 to over 10,000 for example, and will also depend on a variety of factors such as intended application and desired lifetime, cost, etc. Sensors within the array 112 of FIG. 10(a) may be laid out in a linear fashion, in a rectangular grid, or in other configurations.

[000172] In use, the array 112 of the device 110 is exposed to a specimen fluid (sample) such as blood serum. The specimen fluid may be introduced into an analyte chamber that directs the specimen fluid to come in contact with at least a surface of the microelectronic array structure that includes the nanochannels that are to be exposed to the specimen fluid. The sensors of the currently active subsets (e.g., activated through a selection circuitry that, for example, electrically couples voltage source at a tunable voltage level to the nanochannels to open their conduction channels in a pre-determined manner). These sensors are operable to respond by monitoring corresponding electrical conduction characteristics according to the chemical/biological interactions of the nanochannels with the analytes in the fluid, and become manifested as the sensing output signals 122 (which may be voltage and/or current signals whose values correspond to sensed antigen levels through the action of the sensors of the array 112).

[000173] In some embodiments, the device 110 may be implanted in a subject's body to be in contact with the specimen fluid. In some embodiments, the device 110 may be used externally to the subject's body and the specimen fluid is supplied to the device 110 in some manner. For example, the device 110 may include a fluid interface structure to channel the bodily fluid to the active surfaces of the devices of the array 112. The fluid interface structure could be a machined chamber integrated on top of the sensor (like PDMS or plastic chamber). In some implementations, the interface structure may be micro-machined in the same wafer, which will thus contain the chamber (like a lab on a chip) and the sensor device (fabricated inside the chamber). The chamber can be designed to control the "in" and "out" flows of the fluid. In some embodiments, the chamber volume could have a volume of less than 50 microliters, 100 microliters, 1 milliliter, etc.

[000174] The controller 116 and selection units 114 operate together to controllably select individual devices or subsets of devices during device use to achieve desired

performance, reliability, and precision. The controller and the selection units operating in tandem are configured to control the gate voltage, or the drain voltage of each nanoelectronic device, or control a subset of nanoelectronic (nanosensors) devices. By controllably selecting and controlling the individual sensitivity of nanosensors on the chip, conductance channels of the various sensors can be controllably opened or closed to thus enable surface potential change measurement. This approach enables controlling the device locally.

[000175] With reference to FIG. 11, diagrams of a side and top view of a sensor 124 that includes a plurality of nanochannels are shown. In the side view of FIG. 1 1(a), a silicon nano- channel 126a (which may be one of multiple nanochannels 126a-d shown in the top view of FIG. 11(b)) extends between the source (S) contact 128 and the drain (D) contact 130, all formed on an insulating oxide layer 132 above a silicon substrate 134. The source and drain contacts 128 and 130 may be formed of a conductive material, such as, for example, gold plated titanium. In some embodiments, each of the nanochannels 126a-d constituting the sensing device 124 may include an outer oxide layer such as aluminum oxide. Although not shown in FIG. 11, an additional side gate may be used to electrolyze hydrogen peroxide and thus increase the lifetime of the sensor (such as the sensor 124) in the array 112 (the array depicted schematically in FIG. 10(a)).

[000176] Thus, in some embodiments, the device 110 of FIG. 10(a) uses nanoelectronic devices, such as the nanoelectronic sensor 124, made of semiconductors, such as silicon, and configured as electrical transducers. As described above, these silicon nanostructures, such as nano-channels, nano-belts, or nanowires, etc., can be fabricated from a silicon-on-insulator (SOI) wafer that includes a device layer (typically less than 200nm thick), a silicon substrate, and an insulating layer of Si0₂ in between. The nanoelectronic devices can be patterned with electron beam lithography or photolithography, their side walls are subjected to reactive ion etching (RIE) for increasing the surface to volume ratio. Metals, such as Ti/Au, are deposited with thermal evaporator or electron beam evaporator as the source and drain contact electrodes, without further annealing process. The nanochannels the nanoelectronic devices (nanoscale sensors) may have dimensions on the order of 100 nm or less in width, and can be covered with an A1₂0₃ layer, grown, for example, by atomic layer deposition (ALD), with a thickness of, for example, 10 nm. The silicon top layer is lightly doped with boron with a concentration of 10-15 cm as the device layer.

[000177] As described herein, the signal resulting from the biomarker concentration in a test sample is based, at least in part, on the electrical properties of the nanostructures. One example is that the differential conductance of the nanosensor is representative of a detected biomarker concentration. In some embodiments, surface potentials at the nanosensor is indicative of the analyte concentration.

[000178] As further shown in FIG. 11, the illustrated embodiment the sensors 124 includes four nanochannels 126a-d. However, in alternative implementations, a single sensor may have more or fewer nanochannels. As noted, a subset in an array may include a plurality of individual sensor, such as the sensor 124, which may be controlled by electrical actuation of the devices (or sets of devices) performed via, for example, the controller 116 and the selection units 114, as described above. [000179] Turning back to FIG. 10, during a given operating interval, the controller 116 may operate the sensors of selected subsets in a pulsed or sampled manner, providing power to the devices only at regular sample times rather than continually throughout the interval. By using such sampled operation of the nanoelectronic devices of selected subsets, reduced power consumption can be achieved as compared to continuous operation of the nanoelectronic devices. This reduced power consumption can translate into increased lifetime of a limited storage power supply (such as a battery) used to supply power to the sensor device 110.

[000180] FIG. 12 is a schematic diagram of an example diagnostics and monitoring system 140 that uses silicon nanoscale sensors comprising nanochannels. The system includes an array 144 of multiple sensors (sensing elements). Each of those sensors (or a subset of sensors from the multiple sensors comprising the array 144) may be configured to sense a particular chemical or biological agent that may present in an introduced analyte. As described herein, configuring sensing devices to detect particular chemical or biological agent may be performed by functionalizing the nanochannels of various sensing elements such that the functionalized nanochannels interact with their designated chemical/biological

agents/analytes.

[000181] The multiple sensors on the array 144 may each be similar to the nanoscale sensor depicted in, for example, FIG. 11. An example of nanoscale sensor 150 with ten (10) nanochannels is shown in FIG. 12. All ten nanochannels are coupled to a single set of electrodes, namely, the source and drain contacts, and are generally functionalized in a similar manner so that the nanochannel can all interact with the same analytes (if that analyte is present in the sample). The use of multiple discrete nanochannels coupled to a single set of source and drain contacts increases the sensitivity of the sensor 150 in that it increases the redundancy of the sensing structures (i.e., the nanochannels in this case), thus increasing the likelihood of detecting a species present in relatively low concentrations within the sample, and it also increases the surface-to-volume ratio for the sensor. The nanochannels of the sensing element 150 in FIG. 12 each have a thickness of approximately 50 nm. Other nanochannel structures and dimensions may be used, depending on such factors as the desired sensitivity, desired species to be detected, cost, etc.

[000182] The array 144 in FIG. 12 is in fluid communication with a sample processor 143 (e.g., structured as a specimen chamber) that receives, for example, a test strip having the specimen to be tested (e.g., a blood serum, a urine sample, tissue extract, etc.). The sensors of the array 144 are arranged such that the surfaces of the nanochannels can come in contact with the sample introduced via the sample processor 143. As explained, particular species/analytes in the sample may chemically/biologically interact with the nanochannels of at least some of the sensors that were functionalized to interact with those specific analytes. When such an interaction is detected, a binding event between the particular species and the functionalized nanochannels is said to have occurred.

[000183] As a result of chemical/biological interaction (if any) between the various nanochannels of the sensors of the array 144 and the sample introduced via the sample processor 143, the conductance of the interacting nanochannels is modified, resulting, for example, in increased conductance of the interacting nanochannels. The modified

conductance results in a change of the voltage level measured by a bias/measurement circuit, which may be implemented on a data analyzer 146 electrically coupled to the array 144, or implemented as part of the sensors in the array 144 (e.g., each sensor is coupled to an associated bias measurement circuit, such as, for example, the circuit 14 depicted in FIG. 5). An increased conductance causes a higher magnitude of the measured voltage level, with that voltage level being representative of the concentration of the species interacting with the associated sensing element. Because the sensors are, in some embodiments, functionalized to interact with specific species, the measured voltage level for a particular sensor (or the measured voltage profile over a period of time) is thus representative of the concentration in the analyte of the particular species the detecting sensor was configured to detect.

[000184] The measured voltage level indicative of the detected concentration of the particular species detected by the sensing element is provided to a processing module of the data analyzer 146 whereupon the processing module can determine the concentration level for the detected species, e.g., based on a pre-determined lookup table (that may have been compiled/computed during an earlier calibration procedure) relating voltage level(s) for particular species to concentration levels for that species. In some implementations, the measured voltage levels may be processed by an analog-to-digital converter to determine a digital value level from the measured voltage, which can then be used to look up the concentration level. [000185] The system 140 also includes a display, such as, for example, an LCD display, on which the various results and measurements, resulting from the analysis of the sample by the array 144 and analyzed by the data analyzer 146, are presented. In some embodiments, the sample processor 143, the array 144, the data analyzer 146 and the display 148 may be housed in a single housing structure constituting the diagnostics and monitoring system 140.

[000186] As noted, one way to control the attenuation of a nanochannel (and thus control the sensitivity of the nanochannel as well as of the sensor comprising the nanochannel) is by controlling the voltage applied to the sensor (e.g., the gate voltage). Gate voltage may be the potential difference between the surface of the nanochannel and a reference electrode that is distinct from the source or the drain. The mechanism to modulate gate voltage for the purpose of sensitivity control (to attenuate or enhance measured signals) is that the gate voltage can either increase or decrease the carrier depletion zone in the semiconductor channel, causing the conductance to decrease or increase in response to the application of an electric field to the surface of the nanochannel sensor. The applied voltage can thus be used to regulate the conductance of a nanochannel. It is to be noted that the gate's conductance exhibits non-linear behavior, and thus gate voltage control would not simply cause linear offsets in terms of the measured voltage (representative of conductance) but can actually disable, or vary the behavior of a nanochannel in a non-linear way. The inherent non-linearity is useable for further characterization of the analyte-sensor interactions including the surface potential, for logical operations, and in other ways.

[000187] Accordingly, and with continued reference to FIG. 12, in some

implementations, the system 140 further includes a controller 145 (e.g., processor-based controller) that is electrically coupled to the sensor array 144, and is configured to control the sensitivity of one or more of the sensors (such as the sensor 150) arranged in the array. The controller 145 may have a configuration and functionality that includes configuration and functionality similar to that of the controller 116 depicted in FIG. 10. The controller may, for example, be coupled to a selection module (which may have a configuration and functionality that includes configuration and functionality similar to that of the selection units 114 depicted in FIG. 10) that can apply desired voltage levels to at least one sensor in the array 144. Such a selection module may include one or more voltage converters (e.g., a buck converter) coupled to a power source, and may further include circuitry to establish an electrical path to the controllable sensors

[000188] The applied voltage (gate voltage) can be controlled using a circuit such as the circuit 38 shown in FIG. 5(a), with the sensor replaced by the impedance formed by the solution. The value of the gate voltage can be set programmably using a Digital-to-Analog controller, or by Analog methods. A summing circuit can also be used to impose an AC modulation on the gate voltage if desired.

[000189] The controller 145 may control the voltage level applied to individual sensing elements in the array 144 based on pre-determined programs or patterns (stored on a storage device coupled to the controller), or based on real-time input provided by a user through a user interface. The pre-determined programs/patterns or the user input may include information specifying which of the sensors (sensing elements) is to be controlled (e.g., the identity, address and/or locations of the sensors in the array), the voltage level to be applied to the sensing element (e.g., to the gate of the affected sensing elements), the time instance at which the specified voltage levels are to be applied (e.g., in implementation where the sensors sensitivity varies according to a temporal pattern), etc. The controller thus provides control signals according to which required voltage levels are applied to specified sensors in the array 144.

[000190] In some embodiments, the controller 145 (and/or the controller 116) may be implemented using one or more processor-based devices that may include a computer and/or other types of processor-based devices suitable for multiple applications. Such devices can include volatile and non-volatile memory elements, and peripheral devices to enable input/output functionality. Such peripheral devices include, for example, a flash drive, a network connection, for downloading related content, for example, control data to control the voltage levels applied to the sensors on the array 144. Such peripheral devices may also be used for downloading software containing computer instructions to enable general operation of the controller 145 and/or the system 140. In some implementations, the various control operations performed by the controller 145 may also be performed, for example, by using special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit). [000191] FIG. 13 illustrates the principle of voltage control to control sensor sensitivity, which in turn enables control of the operation of an array of nanosensors. Specifically, FIG. I3(a)-13(b) displays the zero-bias differential conductance of the functional ized nanowire in pH solution. In the example of FIG. 13(a)-13(b), the nanowire used was 300 nm wide, 230 nm thick, and 8 um long. The solutions used in the experiment had varying hydrogen ion concentration, or pH, made from phosphate buffered saline, containing 10 mM of phosphate and 130 mM of NaCI. All the measurements were done at room temperature. Generally, the zero-bias conductance of the nanowire increased with increasing pH. As shown in FIG. I 3(a)-13(b), for a positive gate voltage at a level of V_g = 0.6 V, the differential conductance measured at different pH levels was reasonably pronounced, e.g., the differential conductance for pH of 4 at gate voltage of 0.6V was around 690 nS, whereas at a pH level of 6 the measured differential conductance was around 670 nS. As the applied gate voltage decreased, the differences in measured differential conductance at different pH levels became less pronounced, e.g., the differential conductance for pH of 4 at gate voltage of -0.4 V was around 530 nS, whereas at a pH level of 6 the measured differential conductance was slightly less than 530 nS. Thus, by varying the gate voltage, the sensitivity of the nanochannel to differences in a solution's pH levels can be altered. Therefore, by tuning (modulating) the applied voltage, conductance sensitivity of microchannels can be controlled in a

predetermined way. A positive gate bias generally implies opening of an /i-type charge carrier channel, similar to the inversion layer in silicon devices, although the sense of bias can also depend on the nature of the dopant used. A negative gate bias, applied to the device such as the one used in the experiment corresponding to the graphs of FIG. 13, implies depletion or squeezing of the charge carrier channel. The zero-bias conductance thus increases or decreases depending on the applied gate voltage.

[000192] In some implementations, the gate voltage can be controllably varied from about -3 V to + 3 V, with resolution of less than 1 mV. At higher voltage magnitudes, electrolysis in the solvent may occur which therefore sets a limit on the range of the feasible voltages that can be used. As noted herein, the applied gate voltage level should be such that it does not cause conductance of the channel to be too high (wide open channel) or too low (closed channel) that the sensor's sensitivity is compromised. In some embodiment, an operating range of a ± 60 mV near zero bias level may be used.

-43-

RECTIFIED SHEET R LE 9 [000193] FIG. I3(c)-13(f) shows the change in the differential conductance for one particular analyte examined with an antibody-antigen binding reaction as the bias voltage was varied over a range 600 mV, -700 mV, -800 mV and -900 mV. The bias voltage can be used to set the desired baseline differential conductance value for optimum measurement at zero analyte concentration, and also to adjust the amplitude of the change at a given concentration of a particular analyte.

[000194] In some implementations, the gate voltage can be set either at zero, or varied from about -5 V to + 5 V, with resolution of less than 1 mV. FIG. 13(g)-13(j) shows the change in the differential conductance for one particular analyte, as the bias voltage is varied over a range 0 mV, 200 mV, 300 mV, and 400 mV. The bias voltage can be used to set the desired baseline differential conductance value for optimum measurement at zero analyte concentration, and also to adjust the amplitude of the change at a given concentration of a particular analyte.

[000195] In some embodiments, control of the sensitivity of nanoscale sensors can also be achieved by controlling the geometry and other physical properties of the sensors. As an example, FIG. 14 shows the attenuation of a signal when the nanochannel width is increased from 80 nm to 350 nm. As the width increases, the shift in the peak positions is seen to be reduced, by a geometric factor that depends on the dimensions of the nanochannel, and the surface morphology. Other parameters being equal, as the width of the channel is reduced, the sensitivity of the sensor to surface binding events or surface potential changes is increased. This sensitivity control feature can thus be used to tailor the dynamic range of a given nanochannel sensor. Similarly, there is the conductance proportionally increases as the length of the nanochannel increases.

[000196] Spatial geometry of sensors can be used as an implementation feature to configure different sensors in an array to have different sensitivity behaviors, for example, in situations where different analytes, which may have different dynamic ranges, are examined by different sections of an array of sensors. Therefore, depending on the control surface of one nanochannel, the dynamic range may be set to a high or low level for one sensor (or set of sensors) compared with the control surface of another nanochannel on the same device.

[000197] In some embodiments, the width of the nanochannel can be varied over a range achievable using existing lithographic methods, from 10 nm to larger than 1 micron. Typical

-44-

RE TIFIED HEET width values include 50 nm, 80 nm, 150 nm, 200 nm, 350 nm, 850 nm, etc. The height of the nanochannel can be varied over a range, achievable using existing semiconductor-on-insulator wafers, from 20 nm to larger than 1 micron. Typical height values include 100 nm, 500 nm, etc. Furthermore, the length of the nanochannel can be varied over a range, achievable using existing lithographic methods, from 100 nm to larger than 100 microns. Typical length values include 1 micron, 6 microns, 10 microns, 20 microns, etc. The number of nanochannels per sensor can range from a single nanochannel to more than 100 nanochannels per sensor.

Typical values for the number of nanochannels include 1 nanochannel, 10 nanochannels, 20 nanochannels, etc.

[000198] Additionally, thickness of the surface layer on nanochannels can also determine the sensitivity of the underlying nanochannel to surface potential, and can thus be used as a further mechanism to attenuate the signal (and thus control sensor's sensitivity). With reference to FIG. 15, graphs of the attenuation obtained when the surface layer thickness (of an insulating layer, such as AI₂O₃ deposited on nanochannels) was increased from 20 nm to 120 nm are shown. On the left is the dependence of the ratio of the measured source-drain current to the effective width, ranging from 100 nm, 150 nm, 200 nm, 350 nm, and 400 nm, as the gate voltage is varied, showing greater sensitivity at smaller widths. On the right is the dependence of the differential conductance, scaled by the width, as the surface-to-volume ratio is varied, at two different thicknesses of the insulating AI₂O₃ layer, at the specific values of 20 nm and 120 nm.

[000199] Thus, the geometric definition of the control surface contributes to the degree of sensitivity of the output. Therefore, by controlling the geometry (including dimensions) of the nanochannels and/or the insulating layers, the sensitivity of the various sensing elements (nanosensors arranged on an array of sensors) can be defined and controlled. The effects of the geometry of the nanochannels and/or insulating layers on the sensing elements' sensitivity can be expressed mathematically as functions of, for example, nanochannels' width and/or height, and surface layer thickness, using geometric considerations or electromagnetic simulations.

[000200] Also affecting the sensitivity levels of nanochannel are the physical properties or compositions of the layer substances used. For example, the chemical composition, charge, charge density, and surface morphology of the materials used as the layer substance affect the behavior of the sensing element. Thus, attenuation by physical composition may be achieved, for example, through selection of specific inorganic materials in the insulating layer.

[000201] As noted herein, AI₂O₃ is commonly used as the insulating layer. The surface area, surface smoothness and porosity can be controlled by different processing operations and used to enhance or decrease the surface area of the insulating AI₂O₃ layer. Post-treatment in hot solvents results in the replacement of atomically smooth surfaces with a porous structure with a morphology that has greater effective surface area, and can thus be used to attenuate or enhance the response of the nanochannel.

[000202] In some embodiments, the thickness of the insulating AI₂O₃ layer varies from a single atomically smooth layer of about 0.3 nm, controlled, for example, by Atomic Layer Deposition, to more than 1 micron. Typical thickness values include 15 nm, 50 nm, 100 nm, 150 nm, etc.

[000203] As a second example, other inorganics such as Silicon Oxide, Silicon Nitride, Gallium Nitride or CVD diamond may be used.

[000204] In some embodiments, the sensitivity of the sensors may also be affected (and may thus be controlled) by chemical and electrical properties of the surface material that is be to detected and measured (i.e., the chemical/biological analytes in the sample). Because the materials being measured include their own electrical conductance properties, the sensitivity of the nanosensors to the probed materials will be affected by the probed materials own characteristics.

[000205] An important aspect of nanochannel implementation is that the nanochannel' s (and its associated sensor) sensitivity/attenuation can be applied or instituted in, or during, the manufacturing process of the nanosensors and the arrays on which the nanosensors are arranged. Thus, control of the sensitivity/attenuation of the nanochannels and their devices through the manufacturing process can be achieved by performing:

• Top-down lithography fabrication procedures;

• Layering and insulation - the manufacturing process is implemented to create

nanochannels of differing surface dimensionality (e.g., based on pre-determined programs, templates, maps, etc.); and

• Chemical, molecular, biological functionalization. [000206] In some embodiments, sensor sensitivity may further be controlled by performing salination processing on the analyte solution being probed. Thus, for example, such sensitivity controlling operations can be performed by one or more of modulating by ionic strength of the analyte, adding at least one additive to the analyte to control the ionic strength of the analyte, etc.

[000207] With reference to FIG. 16, a flowchart of an example procedure 200 to process (monitor and/or measure) chemical/biological analytes contained in a sample using nanoscale sensors is shown. The procedure 200 includes analyzing 210 a sample that includes at least one analyte, and is introduced into a sensor (such as any of the sensors or sensing elements depicted in, for example, FIGS. 1, 10, 11, etc.), where each sensor includes one or more nanochannels, e.g., 1, 2, 4, 6, 8, 10, 20, or more, constructed from a semiconductor material and connected at their opposite ends to electrodes (e.g., the drain and source of a FET -based device). The one or more nanochannels have at least one electrical property (e.g.,

conductance, capacitance, etc.) that varies based, at least in part, on an interaction with the at least one analyte contained in the sample introduced to the sensor.

[000208] As further shown in FIG. 16, the procedure 200 also includes controlling sensitivity of the sensor, or of the one or more nanochannels, to the presence of the at least one analyte. Such sensitivity control can be achieved by, for example, controllably adjusting the voltage applied to the sensor (e.g., the gate voltage) to control the size of the conduction channel of the nanochannels, and thus control the sensitivity of the sensor. In some embodiments, the procedure may further include treating at least one of the one or more nanochannels of the sensor with a functionalizing agent to functionalize surfaces of the at least one of the one or more nanochannels such that the functionalized surfaces of the at least one of the one or more nanochannels are configured to interact with the at least one analyte.

[000209] In some embodiments, the sensors described herein, for example, the sensor depicted in FIGS. 10(b) and 11, may be used to sense/monitor glucose. FIG. 17 shows an application of a glucose sensor 160 in a system including a control unit 162 and a pump 164, which can operate in a manner analogous to an animal pancreas to regulate blood glucose levels by selective release of the hormone insulin. To detect glucose, control surfaces of the nanochannels of the sensor 160 are functionalized with a glucose reactive substance such that when glucose interacts with that functionalized material, a chemical reaction resulting in a change to the surface potential will occur, thus affecting electrical characteristics of the sensor (e.g., change to the conductance of the conduction channel of the nanochannels of the sensor).

[000210] The sensor 160, which may be similar to any of the sensor described in the present disclosure, is exposed to a glucose-carrying bodily fluid (shown as SAMPLE in FIG. 17) and generates sensing output signals 166 which are provided to the control unit 162. The control unit 162 performs an appropriate control procedure to ascertain an amount of insulin to be supplied based on the sensed glucose level as conveyed by the sensing output signals 166, and generates pump control signals 168 which are supplied to an insulin pump 164 which dispenses the insulin in accordance with the values of the pump control signals 168. The control unit 162 may also have a separate interface (not shown) to the sensor 160.

[000211] In some embodiments, the sensor 160 may be part of an array of sensors that can be individually selected and controlled. Such controllability and selection functionality may be implemented by modules such as the controller and the selection units depicted in FIG. 10.

[000212] Any and all analyte detection elements may be used with the disclosed devices, systems and methods. For example, any material may be used where there is a specificity of detection. Examples of the types of analytes that may be examined include, without limitation, different fluids, bodily materials, air, aerosols, and/or soil. In particular, bodily fluids such as whole blood, serum, plasma, interstitial fluids, mucous, cerebrospinal fluid, synovial fluid, gastric fluid, urine, feces, intraocular fluids, sweat, skin oils, and any and all fluid material of the human body, may be examined using the devices, systems and methods described herein. Other types of materials that be examined by the disclosed devices, systems and methods include cell extracts, lysed cells, and other cell debris, necrotic cells, and material. In addition, agricultural products, plants, and yeast, or microbe materials may also be examined and detected using nanochannel sensors described in the present disclosure.

[000213] Additionally, analytes may represent complex surfaces of biological relevance. For example, any and all analytes in complex mixtures or surfaces, such as cell surfaces, virus particles, synthetic surfaces, organelles and subcellular vacuoles, membranes, droplets, etc., may be examined and detected by the devices, systems and methods disclosed herein. In addition, synthetically created surfaces, particle surfaces, virus surfaces, cell surfaces, etc., may be examined and detected by the devices, systems and methods disclosed herein. [000214] Likewise, a variety of methods to identify analytes by binding and/or hybridization to a detection strategy may be used.

Multiplexing

[000215] The devices, systems and methods described herein may also be used in the implementation of multiplexed diagnostics test panels chips. In some embodiments, multiplexed test panel chips may be implemented using arrays and/or system similar to the array 112 used with the system 100 depicted in FIG. 10.

[000216] The multiplexing functionality of the array of sensors enables parallel measurements to be performed using a single chip and also enable performance of repeated or redundant measurements to increase measurement reliability. This multiplexing feature contributes to the specifications and utilities of the device in several ways.

[000217] FIG. 18 shows multiple sensor devices integrated on a chip in order to provide an array for detection of multiple target molecules simultaneously (or substantially

simultaneously). This simultaneous detection of chemical/biological analytes is achieved by configuring the sensors comprising the array to each detect particular analytes, for example, by functionalizing the nanochannels of the various sensors to chemically/biologically interact with the desired analytes to be detected, and by controlling the sensitivity of the various sensors through control of their respective nanochannels' geometry (e.g., during the fabrication process), through dynamic control of the voltages applied to nanochannels, etc.

[000218] FIG. 19 is a schematic diagram of multiple sensors logically arranged into an array (or matrix) of NxN subsets of nanosensors. In the example of FIG. 19, each subset includes a single nanosensor with 10 nanochannels. Nanosensors with different

configurations (different number of nanochannels) may be used. However, other array configurations may be used, including arrays with different numbers of rows and columns, and with different subsets having non-uniform number of nanosensors associated with them (e.g., some subsets may have a single nanosensor, while other subsets may have multiple nanosensors). Each of the individual nanosensors may be implemented in a manner similar to the implementation of the nanoscale sensors described in the present disclosure. Accordingly, the nanosensor may have their respective sensitivity (e.g., to the presence of analytes/agents in the sample, as may be indicated by changes to the conductance of the conduction channel) controlled. For example, tunable voltage levels could be applied, via a controller, to the various subsets and/or nanosensors to control their sensitivity, or disable them (e.g., by disabling their bias/measurement circuit or applying a gate voltage level that closes the conduction channel).

[000219] As further shown in FIG. 19, various subsets of nanosensors are configured to detect different chemical/biological agents in a sample. For example, the four nanosensor subsets depicted are each configured to detect different antibody (e.g., through a

functionalization process in which control surfaces of the sensors are treated with agents configured to react to particular analytes.

[000220] A standard well-known configuration for measuring small changes impedance uses a bridge configuration (FIG. 20). Since the nanochannel sensors do not exhibit conventional ohmic resistance response over the entire range of the operation, the elements may be more generally replaced by impedances.

[000221] As the geometry of the nanochannels is achieved on the nanoscale and the manufacturing process enables to create a variety of configurations, a number of utilities can be illustrated.

[000222] In one setting, an analyte can be measured relative to one or more control proteins from the same material solution fluid, aerosol, and/or mixture. For example, a sensor configured for the detection of the breast cancer biomarker CA 15.3 is tested against a serum or buffer sample containing a different analyte, such as Prostate Specific Antigen or

Antibiotin. The nanosensor functionalized for CA15.3 does not show response above the background to varying concentrations of Antibiotin, but shows the expected response to the presence of CA15.3

[000223] Further, a procedure to associate the detection level of an analyte and the control protein with conductance data from the device can be performed.

[000224] In an additional setting, a sample can be measured on separate but equal nanochannels in order to improve the coefficient of variation for the measurement of the analyte in the sample. For example, a reduction in deviation is demonstrated when the same analyte is measured multiple times. The importance of this aspect of the present disclosure is the ability to increase the accuracy of the sample measurement. As an example, two or more independent nanochannel sets can be prepared on the same chip, and functionalized with the same antibody. The response of each set to the analyte at a fixed standard calibration is measured, using a multiplexing circuit in which each set of the nanochannels is interrogated serially, by measuring the differential conductance change. In an additional setting, two or more disease-related analytes can be measured from the same material solution fluid, aerosol, and/or mixture. As an example, solution containing CA15.3 and Prostate Specific Antigen can be analyzed on the same device.

[000225] In each of these examples, the geometry of the individual nanochannels may be configured to represent the dynamic range of the analyte being detected. For example, analytes may be present in complex fluids, such as whole blood, at vastly different concentrations. In order to independently measure these analytes in a uniform manner, a device can be configured where nanochannels of different dimensions are created by manufacturing. Therefore, measurements of the same analyte can be achieved in different dynamic ranges that are pre-determined by the concentration and/or binding affinity of the analyte to the analyte detection strategy.

[000226] An example of how individual nanochannels can be configured and

manufactured is achieved by accommodating molecular information about an analyte. For example, analyte binding is measured using a conversion factor used to determine an "on" rate, K_on, and/or and "off rate, K_Qff, of a binding between an analyte and the detection substance on the control surface. Because the binding constant is a constant under equal conditions, the changes in the geometry of the nanochannel will be a way to increase or decrease the sensitivity of the measurement.

[000227] As described herein, the top-down manufacturing process of the present disclosure allows the development and implementation of highly multiplexed nanochannels that can operate in concert. There are several considerations for the organization of the chip composed of multiple nanochannels, including:

• Considerations arising from manufacturing placement of nanosensors for parallel conductance measurements;

• Considerations arising from the need to perform separate surface functionalization; • Considerations arising from targeting of analyte detection strategies to specific addresses to the total surface; for example, by use of robotics the functionalization of a specific component is directed to a particular coordinates where a selected sensor resides on the device. The use of robotic technology provides for material printing to specific programmable addresses;

• Considerations arising from use of biological signatures such as DNA:DNA and

DNA:R A barcodes; and

• Considerations arising from use of conjugation chemistry that is directed to specific analytes.

[000228] Thus, for example, in some implementations, manufacturing of a nanoscale sensor array may include applying a pre-determined pattern of a plurality of nanoscale sensors to a semiconductor-based wafer, where the pre-determined pattern of a plurality of nanoscale sensors may include data for at least one nanoscale sensor, associated with pre-determined sensitivity to one or more analytes in a sample, that is different from associated predetermined sensitivity of at least one other nanoscale sensor to the one or more analytes. For example, the pre-determined sensitivity data can be based on previously compiled data associating sensitivity parameters (e.g., in terms of signal-to-noise ratio at a particular voltage level applied to a particular part of a sensor) for given configurations and dimensions of sensors. Such pre-determined sensitivity data may also be expressed as relative values. Such pre-determined data relating sensitivity and dimensions, configurations and other properties of nanoscale sensors can be stored in tables, indexed data records, etc. Thus, for example, where a sensor of a particular sensitivity to a given analyte is required in a manufactured array, the pre-determined pattern can be generated using the stored data in which, for the desired sensitivity and the given analyte, associated dimensions and configuration of the sensor can be retrieved.

[000229] The manufacturing may also include functionalizing at least one control surface of the plurality of nanoscale sensors on a resultant wafer with the applied pattern using an analyte detection substance to chemically interact with an associated biomarker. The predetermined pattern further includes data for one or more of the plurality of nanoscale sensors associated with a controllable sensitivity that is modulated based, at least in part, on controllable variable voltage to be applied to the one or more of the plurality of the nanosensors when a manufactured array is in use. In some embodiments, applying the pattern may include etching out the wafer with an anisotropic reactive-ion etch (RIE) material based on the pre-determined pattern and/or performing a lithography procedure based on the predetermined pattern. The manufacturing procedure may also include growing a layer of AI₂O₃ on control surfaces of the nanoscale sensors located on the resultant wafer with the applied pre-determined pattern.

[000230] FIG. 21 includes a table (captioned as Table 1) illustrating the utility of the systems, devices and methods described herein in relation to many applications where a determination of more than one biomarker in tandem will provide a better test for patient use. As shown, several examples of combinations of markers where measurements are used to determine a patient's health, health risk, and acceptability for a treatment decision, or response to therapy may be performed in parallel using the same specimen that includes the various potential agents being measured.

[000231] The types of biomarkers that may be measured by the disclosed systems, devices and methods are numerous. In different analyte categories, the examples involve protein, RNA, DNA measurements, but there is no limitation to these particular categories of biomarkers. In the example, biomarkers are selected where treatment decisions may be important in an Emergency Room department, an outpatient clinic, a point-of-care application, and/or for home use. In another example, different types of analytes may also be measured using the same device and the same specimen.

[000232] Thus, in some embodiments, two or markers measured by multiplexing are may be applied to facilitate diagnosing cardiac failure as acute myocardial infarction versus unstable angina. Such markers may include one or more of, for example, cardiac Troponin T, cardiac Troponin I, CK-MB, myoglobin, and/or BNF. The markers may be separately used to assess heart failure.

[000233] In some embodiments, two or more markers measured by multiplexing may facilitate diagnostic for one or more of, for example, a cancer indication, a treatment response decision, or staging, and/or monitoring of cancer. The two or more markers may include one or more of, for example, PSA, CA 12.5, Her2, and ovarian cancer markers.

[000234] In some embodiments, two or more markers measured by multiplexing may be used to evaluate drug response susceptibility determine by one or more of, for example, SNP, mutation, a combinations of SNPs, DNA chromosomal deletions, amplifications, and/or copy number. In some embodiments, two or more markers measured by multiplexing are applied to one or more of diagnosing toxic proteins pathogens viruses or infectious agents in one or more of, for example, an emergency room environment, and point-of-care environment. In some embodiments, two or more markers measured by multiplexing may be used for surveying of toxic agents, including one or more of, for example, surveying toxic agents to detect bioterrorism agents, and/or surveying toxic agents in food sources.

[000235] FIG. 22 is a flowchart of a multiplexing procedure 300. The procedure 300 may be performed as part of the operations of procedure 200 described in relation to FIG. 16, or may be performed independently of procedure 200, or of any other procedure.

[000236] Thus, in implementations where sensors (such as any of the sensors depicted in FIGS. 1, 10(b), etc.) are disposed in an array of multiple sensors that are logically organized into a plurality of individually operable subsets of sensors, control signals are generated 310 to select at least one of the subsets of sensors. Having generated the appropriate control signals, the at least one of the subsets of the sensors is selected 320, in response to the generated control signals, to enable electrical sensing operation of the selected at least one of the subsets of sensors and to generate respective sensing output signals. In some embodiments, at least one of the multiple sensors is configured to be biased by a drain source voltage to control the at least one of the multiple sensors' characteristics.

OTHER EMBODIMENTS

[000237] Various embodiments of the subject matter described herein can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include implementations in one or more computer programs, stored on non-transitory media, that are executable and/or interpretable on a processor-based systems including, for example, at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device. [000238] These computer programs (also known as programs, software, software applications or code) include machine instructions for a programmable processor, and can be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the term "machine-readable medium" refers to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a non-transitory machine -readable storage medium that receives machine instructions as a machine-readable signal. The term "machine- readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.

[000239] To provide for interaction with a user, the subject matter described herein can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, or some other display device, for displaying information to the user, and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user may provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback), and input from the user can be received in any form, including acoustic, speech, or tactile input.

[000240] The subject matter described herein can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a client computer having a graphical user interface or a Web browser through which a user may interact with an implementation of the subject matter described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), and the Internet.

[000241] The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. [000242] Some embodiments of the present disclosure preferably implement the various disclosed controllers or selection units via software operated on a processor-based device.

[000243] Any and all references to publications or other documents, including but not limited to, patents, patent applications, articles, webpages, books, etc., presented in the present application, are herein incorporated by reference in their entireties.

[000244] Although a few variations have been described in detail above, other modifications are possible. For example, different variations of semiconductor nanostructures may be used as the electrical signal transducers. While silicon may be a suitable material for its compatibility with integrated groups of nanochannels, other materials such GaAs can be used as the building material of the device. Within an array of such sensors, it may be desirable to refrain from functionalizing some sensors to enable them to serve as references. High density nanoscale electrical transducers can help to increase sensitivity by averaging all working elements in the array. The logic flow depicted in the accompanying figures and described herein does not require the particular order shown, or sequential order, to achieve desirable results. Other embodiments can be within the scope of the following claims.

Claims

WHAT IS CLAIMED IS:

1. A sensing device comprising:

a sensor including one or more nanochannels constructed from semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with at least one analyte contained in a sample introduced to the sensor; and

a controller to control sensitivity of the sensor to the presence of the at least one analyte.

2. The sensing device of claim 1, wherein the one or more nanochannels of the sensor are a gate structure of a field effect transistor (FET), and the connected electrodes include drain and source of the FET.

3. The sensing device of claim 2, wherein the one or more nanochannels are configured to operate in a negative source drain electric configuration, and wherein the sensitivity of the one or more nanochannels is determined based on one or more of: voltage applied to the one or more nanochannels, and analyte binding at the one or more

nanochannels.

4. The sensing device of claim 1, wherein at least one of the one or more nanochannels is treated with a functionalizing agent to functionalize surfaces of the at least one of the one or more nanochannels such that the functionalized surfaces of the at least one of the one or more nanochannels are configured to interact with the at least one analyte.

5. The sensing device of claim 4, wherein the functionalizing agent includes one or more of an analyte detection substance, and a reactive substance, and wherein the interaction includes a chemical interaction that varies one or more of: conductance of the one or more nanochannels, and capacitance of the one or more nanochannels.

6. The sensing device of claim 1, further comprising an analyte interface to receive and enable contact between the sample and the one or more nanochannels

7. The sensing device of claim 6, wherein the analyte interface is configured to receive one or more of: a fluid, aerosol, and air.

8. The sensing device of claim 1, wherein the controller configured to control the sensitivity of the one or more nanochannels is configured to:

cause voltage to be applied to at least one of the one or more nanochannels to cause conductance of the at least one of the one or more nanochannels to change.

9. The sensing device of claim 8, wherein the controller configured to cause the voltage to be applied is configured to cause one or more of:

increase the voltage applied to the at least one nanochannel to increase the conductance of the at least one of the one or more nanochannels; and

decrease the voltage applied to the at least one nanochannel to decrease the conductance of the at least one of the one or more nanochannels.

10. The sensing device of claim 1, wherein the controller configured to control the sensitivity of the one or more nanochannels is configured to:

cause a pre-determined voltage level to be applied to at least one of the one or more nanochannels at a pre-determined time instance.

11. The sensing device of claim 1 , wherein the one or more nanochannels have geometric configurations corresponding to a pre-determined sensitivity level to the presence of the at least one analyte.

12. The sensing device of claim 11, wherein the geometric configuration of the one or more nanochannels is defined through top-down fabrication process.

13. The sensing device of claim 11, wherein the one or more nanochannels has a critical dimension of less than 100 nm.

14. The sensing device of claim 1, wherein the at least one analyte includes one or more of: antibody, nucleic acid, PNA, aptamer, ligand, receptor, protein, lipid, carbohydrate, other small molecule or biopolymer;

and wherein a reactive agent used in functionaliztion of the at least one nanochannel includes one or more of: antibody, nucleic acid, PNA, aptamer, ligand, receptor, protein, lipid, carbohydrate, or other small molecule or biopolymer;

and wherein the analyte detection is governed by one or more chemical associations between the at least one analyte and the reactive agent.

15. The device of claim 1, wherein the sensitivity of the sensor is further controlled by one or more of: modulating an ionic strength of the sample, adding at least one additive to the sample to control the ionic strength of the sample.

16. The sensing device of claim 1, wherein at least one of the one or more nanochannels includes a three-dimensional control surface defined by length, width and height dimensions, the three-dimensional control surface including a pre-determined surface area configuration.

17. The sensing device of claim 1, wherein the sensitivity of the sensor is further controlled by applying a surface coating with pre-determined properties to the one or more nanochannels.

18. The sensing device of claim 17, wherein the surface coating includes an AI₂O₃ insulation layer grown by atomic layer deposition.

19. The sensing device of claim 18, wherein the surface coating includes any of a group of specific inorganic materials used as an insulation layer for the purpose of affecting the sensitivity of the one or more nanochannels.

20. The sensing device of claim 1, wherein the sensitivity of the sensor is further determined based on doping of a control surface layer composition.

21. A nanoscale sensor comprising:

one or more nanochannels constructed from semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with at least one analyte contained in a sample introduced to the sensor;

wherein the nanoscale sensor is associated with a controllable sensitivity that is modulated based, at least in part, on controllable variable voltage applied to the nanoscale sensor.

22. The nanoscale sensor of claim 21, wherein the nanoscale sensor is coupleable to a controller to control sensitivity of the sensor to the presence of the at least one analyte.

23. The sensor of claim 21, wherein the one or more nanochannels of the sensor are a gate structure of a field effect transistor (FET), and the connected electrodes include drain and source of the FET.

24. The sensor of claim 21, wherein at least one of the one or more nanochannels is treated with a functionalizing agent to functionalize surfaces of at least one of the one or more nanochannels such that the functionalized surfaces of the at least one of the one or more nanochannels is configured to interact with the at least one analyte.

25. The sensor of claim 21, further comprising an analyte interface to receive and enable contact between the analyte and the one or more nanochannels.

26. The sensor of claim 21, wherein the controller configured to control the sensitivity of the one or more nanochannels is configured to:

cause voltage to be applied to at least one of the one or more nanochannels to cause conductance of the at least one of the one or more nanochannels to change.

27. A sensor system comprising: an array of multiple nanoscale sensors, each of the multiple nanoscale sensors including one or more nanochannels constructed from a semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with at least one analyte contained in a sample introduced to the multiple nanoscale sensors; and

a controller to control sensitivity of at least one of the multiple sensors to the presence of the at least one analyte.

28. The system of claim 27, wherein the one or more nanochannels of at least one of the multiple sensors are a gate structure of a field effect transistor (FET), and the connected electrodes include drain and source of the FET.

29. The system of claim 27, wherein at least one of the one or more nanochannels of at least one of the multiple sensors is treated with a functionalizing agent to functionalize surfaces of the at least one of the one or more nanochannels such that the functionalized surfaces of the at least one of the one or more nanochannels are configured to interact with the at least one analyte.

30. The system of claim 27, further comprising an analyte interface to receive and enable contact between the analyte and the one or more nanochannels of at least one of the plurality of sensors.

31. The system of claim 27, wherein the array of multiple sensors is logically organized into a plurality of individually operable subsets of sensors, and wherein the system further comprises:

a controller operative to generate control signals to enable electrical operation of the subsets of the nanoelectronic devices; and

a device selection unit operative, in response to the control signals, to enable electrical sensing operation of a selected at least one of the subsets of the sensors to generate respective sensing output signals.

32. The system of claim 31 , wherein each subset of sensors including at least one of the multiple sensors configured to be biased by a drain source voltage to control the at least one of the multiple sensors' characteristics.

33. The system of claim 31, wherein the controller is configured to:

control sensitivity of any one or more of the subsets of sensors to any of the at least one analyte.

34. The system of claim 27, wherein the controller is further configured to cause sampled operation of the sensors of the selected subset to achieve reduced power

consumption as compared to continuous operation of the multiple sensors in the array.

35. The system of claim 27, wherein the controller is further configured to perform monitoring of at least one of the multiple sensors to determine accuracy of sensed output signals as being representative of actual analyte levels of the analyte.

36. The system of claim 27, wherein the controller configured to control the sensitivity of the one or more nanochannels is configured to:

cause voltage to be applied to at least one of the one or more nanochannels to cause conductance of the at least one of the one or more nanochannels to change.

37. A method comprising:

analyzing a sample including at least one analyte, the sample introduced into a sensor that includes one or more nanochannels constructed from semiconductor material and connected at their opposite ends to electrodes, the one or more nanochannels having at least one electrical property that varies based, at least in part, on an interaction with the at least one analyte contained in the sample introduced to the sensor; and

controlling sensitivity of the sensor to the presence of the at least one analyte.

38. The method of claim 37, wherein the one or more nanochannels of the sensor are a gate structure of a field effect transistor (FET), and the connected electrodes include drain and source of the FET.

39. The method of claim 37, further comprising:

treating at least one of the one or more nanochannels of the sensor with a

functionalizing agent to functionalize surfaces of the at least one of the one or more nanochannels such that the functionalized surfaces of the at least one of the one or more nanochannels are configured to interact with the at least one analyte.

40. The method of claim 37, wherein controlling the sensitivity of the sensor comprises:

causing voltage to be applied to at least one of the one or more nanochannels to cause conductance of the at least one of the one or more nanochannels to change.

41. The method of claim 37, wherein the sensor is disposed in an array of multiple sensors logically organized into a plurality of individually operable subsets of sensors, the method further comprising:

generating control signals to select at least one of the subsets of sensors; and selecting, in response to the generated control signals, the at least one of the subsets of the sensors to enable electrical sensing operation of the selected at least one of the subsets of sensors and to generate respective sensing output signals.

42. The method of claim 41, wherein each of subsets of sensors includes at least one of the multiple sensors configured to be biased by a drain source voltage to control the at least one of the multiple sensors' characteristics.

43. A nanoscale sensor comprising:

an array of a plurality of nanoelectronic devices having respective control surfaces individually or collectively functionalized with at least one analyte reactive substance, wherein one or more of the plurality of nanoelectronic devices is associated with a controllable sensitivity that is modulated based, at least in part, on controllable variable voltage applied to the one or more nanoelectronic devices; and

a fluid material interface structure configured to enable contact between the control surfaces and a common volume of a material being measured; wherein at least some of the plurality of nanoelectronic devices in the array are configured to perform multiple redundant measurements from two or more spatially distinct control surfaces.

44. The nanoscale sensor of claim 43, wherein the plurality of nanoelectronic devices includes control nanochannels placed on a single chip, wherein the control nanochannels are associated with respective conductance channels configured to be controllably opened, and wherein the control nanochannels are operative in keeping reference gate voltage grounded, and applying a negative source drain voltage to enable opening of the respective conductance channels to make the respective conductance channels suitable for surface potential change measurement

45. The nanoscale sensor of claim 44, wherein the control nanochannels are placed on the same chip and are further configured to engage in performance monitoring of the nanoelectronic devices to ascertain how accurately the sensing output signals reflect an actual analyte level of analytes in the material being measured.

46. The nanoscale sensor of claim 43, wherein binding is measured by a conversion factor used to determine an equilibrium constant of an enzymatic step.

47. The nanoscale sensor of claim 46, wherein the binding is measured by a conversion factor used to determine an "on" rate K_on, and/or and "off rate K_Qff of a binding between an analyte and the analyte reactive substance on the control surfaces.

48. The nanoscale sensor of claim 43, wherein two or more markers measured by multiplexing are applied to diagnosing cardiac failure as acute myocardial infarction versus unstable angina.

49. The nanoscale sensor of claim 48, wherein the two or more markers measured by multiplexing applied to diagnosing cardiac failure as acute myocardial infarction versus unstable angina include one or more of: cardiac Troponin T, cardiac Troponin I, CK-MB, myoglobin, and BNF.

50. The nanoscale sensor of to claim 48, wherein the two or more markers measured by multiplexing applied to diagnosing risk to cardiac disease or failure as acute myocardial infarction are separately used to assess heart failure.

51. The nanoscale sensor of claim 43, wherein two or more markers measured by multiplexing are diagnostic for one or more of: a cancer indication, a treatment response decision, or staging, and monitoring of cancer.

52. The nanoscale sensor of claim 51 , wherein the two or more markers include one or more of: PSA, CA 12.5, Her2, and ovarian cancer markers.

53. The nanoscale sensor of claim 43, wherein two or more markers measured by multiplexing are used to evaluate drug response susceptibility determine by one or more of: SNP, mutation, a combinations of SNPs, DNA chromosomal deletions, amplifications, and copy number.

54. The nanoscale sensor of claim 43, wherein two or more markers measured by multiplexing are applied to one or more of diagnosing toxic proteins pathogens viruses or infectious agents in one or more of: an emergency room environment, and point-of-care environment.

55. The nanoscale sensor of claim 43, wherein two or more markers measured by multiplexing are for the surveying of toxic agents, including one or more of: surveying toxic agents to detect bioterrorism agents, and surveying toxic agents in food sources.

56. A nanoscale sensor comprising:

an array of nanoelectronic devices including respective control surfaces, the array being configured to allow for intimate contact between the control surfaces and an antigen carrying bodily fluid, the array of nanoelectronic devices being logically organized into a plurality of individually operable subsets of the nanoelectronic devices, each subset biased by a drain source voltage to attenuate sensor characteristics, at least one of the subsets functionalized using an analyte detection substance to chemical interact with an associated biomarker;

selection circuitry operative in response to control inputs to enable electrical sensing operation of a selected one of the subsets of the nanoelectronic devices to generate respective sensing output signals; and

controllable nanochannels associated with at least one of the subsets of the nanoelectronic devices, the controllable nanochannels operative to be actuated by control signals to enable electrical operation of the subsets of the nanoelectronic devices.

57. The nanoscale sensor of claim 56, wherein the controllable nanochannels are further operative to engage in performance monitoring of the nanoelectronic devices to ascertain how accurately output signals sensing reflect actual analyte level of different analytes in the antigen carrying bodily fluid.

58. The nanoscale sensor of claim 56, wherein the control nanochannels are further operative to engage in performance monitoring of the nanoelectronic devices to sense one or more of a binary determination, graded stepwise, or continuous distribution of analyte concentration

59. The nanoscale sensor of claim 56, wherein two or more markers measured by multiplexing are separately evaluated on one or more of the control surfaces, and the attenuation criteria are set so that the measurements of the two analytes may occur at dynamic ranges that are not overlapping, and may be separated by logarithms of

concentration and/or affinity.

60. A method to manufacture a nanoscale sensor array, the method comprising: applying a pre-determined pattern of a plurality of nanoscale sensors to a

semiconductor-based wafer, the pre-determined pattern of a plurality of nanoscale sensors including data for at least one nanoscale sensor representative of a pre-determined sensitivity to one or more analytes in a sample that is different from another pre-determined sensitivity of at least one other nanoscale sensor to the one or more analytes; and functionalizing at least one control surface of the plurality of nanoscale sensors on a resultant wafer with the applied pattern using an analyte detection substance to chemically interact with an associated biomarker;

wherein the pre-determined pattern further includes data for one or more of the plurality of nanoscale sensors associated with a controllable sensitivity that is modulated based, at least in part, on controllable variable voltage to be applied to the one or more of the plurality of the nanoscale sensors when a manufactured array is in use.

61. The method of claim 60, wherein applying the pattern comprises one or more of:

etching out the wafer with an anisotropic reactive-ion etch (RIE) material based on the pre-determined pattern; and

performing a lithography procedure based on the pre-determined pattern.

62. The method of claim 60, further comprising:

growing a layer of AI₂O₃ on control surfaces of the nanoscale sensors located on the resultant wafer with the applied pre-determined pattern