CN117255941A - System and method for sample characterization by using hysteresis effect of graphene varactor - Google Patents

Abstract

Embodiments herein relate to systems and methods that utilize hysteresis as a sample analysis mechanism. A system for analyzing a fluid sample is included having a controller circuit and a chemical sensor element. The chemical sensor element may include one or more discrete binding detectors, which may include one or more graphene varactors. The system may include a measurement circuitry, which may include a voltage generator configured to generate an applied voltage at a plurality of voltage values to be applied to one or more graphene varactors. The system may include a measurement circuit having a capacitive sensor configured to measure a capacitance of the discrete binding detector caused by an applied voltage. The system for analyzing a fluid sample may be configured to measure a hysteresis effect associated with capacitance-voltage values obtained by one or more graphene varactors. Other embodiments are also included herein.

Description

System and method for sample characterization by using hysteresis effect of graphene varactor

The present application was filed on 4 months 15 of 2022 as PCT international patent application under the name of the designated applicant, university of minnesota board of all countries (REGENTS OF THE UNIVERSITY OF MINNESOTA), united states citizen Steven koster (Steven koster), chinese citizen Su Qun and united states citizen phillips pi ehypter josephsv boolean man (Philippe Pierre Joseph Buhlmann). The present application is also filed as PCT international patent application in the name of boston science international limited (Boston Scientific Scimed, inc.) of the applicant specified in all countries, chinese citizens screening of the applicant specified in all countries, us citizen Gu Siting-sierodon nielsen (Justin Theodore Nelson), us citizen grago J-swood (gregoriy j.sheawood). The present application claims priority from U.S. provisional application Ser. Nos. 63/175,670, filed on 4 months 16 of 2021, and U.S. application Ser. No.17/719,760, filed on 13 months 4 of 2022, the entire contents of which are incorporated herein by reference.

Technical Field

Embodiments herein relate to systems and methods that utilize hysteresis as a sample analysis mechanism. In particular, embodiments herein relate to systems and methods that utilize hysteresis as a mechanism to detect different volatile organic compounds in a sample.

Background

Early accurate disease detection may allow the clinician to provide appropriate therapeutic interventions and may lead to better therapeutic results. Many different techniques may be used to detect disease, including analysis of tissue samples, analysis of various bodily fluids, diagnostic scanning, gene sequencing, and the like.

Some disease states result in the production of specific compounds, including Volatile Organic Compounds (VOCs), which can be released into patient samples and may be a marker for certain diseases.

However, when using chemical sensors, characterizing a patient sample and/or sensing individual VOCs in complex gaseous samples can be a difficult task. Chemical sensors involve intricate environments that can produce a variety of response signals generated by the chemical sensor itself as well as binding of specific analytes to the chemical sensor.

Disclosure of Invention

In a first aspect, a system for analyzing a fluid sample is included. The system may include a controller circuit and a chemical sensor element, wherein the chemical sensor element may include one or more discrete combined detectors and the one or more discrete combined detectors may include one or more graphene varactors. The system may include a measurement circuitry, wherein the measurement circuitry may include a voltage generator, and the voltage generator is configured to generate an applied voltage at a plurality of voltage values to be applied to the one or more graphene varactors. The voltage value may fall within a range from a lower limit to an upper limit. The system may include a measurement circuit that may include a capacitive sensor, wherein the capacitive sensor is configured to measure a capacitance of the discrete binding detector caused by the applied voltage. A system for analyzing a fluid sample may be configured to measure hysteresis effects associated with a capacitive phase-voltage value (capacitance versus voltage valves) obtained by one or more graphene varactors.

In a second aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the applied voltage includes a voltage value starting from one of the lower or upper limits and moving to the other limit as part of a scan of different voltage values within the range of the lower limit to the upper limit.

In a third aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the hysteresis effect reflects a measurable gap associated with the capacitance of the graphene varactors, the measurable gap being caused by a sweep in a first direction between a lower limit and an upper limit relative to a sweep in a second direction between the lower limit and the upper limit, wherein the second direction is opposite to the first direction.

In a fourth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the first direction is a sweep from a lower voltage limit to an upper voltage limit, and the second direction is a sweep from an upper voltage limit to a lower voltage limit.

In a fifth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the first direction is a sweep from an upper voltage limit to a lower voltage limit, and the second direction is a sweep from a lower voltage limit to an upper voltage limit.

In a sixth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the applied voltage may be represented as a sum of AC voltage components superimposed on the DC bias voltage component.

In a seventh aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the AC voltage component comprises a sinusoidal waveform, a square waveform, a sawtooth waveform, a ramp waveform, or a triangular waveform.

In an eighth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the amplitude of the AC voltage component is from 25mV to 300mV.

In a ninth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the DC bias voltage component falls within a voltage range from a lower limit to an upper limit.

In a tenth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the scanning in the first direction is followed by the scanning in the second direction.

In an eleventh aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein scanning in the first direction is followed by a pause, followed by scanning in the second direction.

In a twelfth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the dwell length is from 1 millisecond to 5 seconds.

In a thirteenth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the lower voltage limit and the upper voltage limit are preset values.

In a fourteenth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the voltage lower limit and the voltage upper limit are dynamically determined values.

In a fifteenth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein scanning in the second direction is performed after scanning in the first direction constitutes a hysteresis measurement cycle, wherein the upper voltage limit and the lower voltage limit remain static between successive cycles.

In a sixteenth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein scanning in the second direction is performed after scanning in the first direction constitutes a hysteresis measurement cycle, wherein the upper voltage limit and the lower voltage limit change between subsequent cycles.

In a seventeenth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein the hysteresis effect comprises a change in one or more of the following: capacitance at a particular voltage, maximum slope of capacitance versus voltage, minimum capacitance, voltage at minimum capacitance (dirac voltage), full width half maximum/half maximum of capacitance-voltage curve, area of capacitance-voltage curve, difference between maximum capacitance and minimum capacitance, maximum capacitance and ratio of maximum capacitance to minimum capacitance.

In an eighteenth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the system is configured to characterize the fluid test sample based on the determined hysteresis effect.

In a nineteenth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the system is configured to utilize the determined hysteresis effect as a data input in a pattern matching operation, wherein a result of the pattern matching operation characterizes the fluid test sample and/or a patient providing the fluid test sample.

In a twentieth aspect, in addition to or in the alternatives to one or more of the preceding or following aspects, the system is configured to calculate a first dirac point voltage for a scan of the discrete combined detector in a first direction and a second dirac point voltage for a subsequent scan of the discrete combined detector in a second direction.

In a twenty-first aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the controller circuit is configured to measure a difference between the forward dirac voltage and the reverse dirac voltage.

In a twenty-second aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein the system for measuring the presence of an analyte in a fluid sample is configured to simultaneously apply a scan over a range of voltages to a plurality of discrete binding detectors.

In a twenty-third aspect, in addition to or alternatively to one or more of the preceding or following aspects, the controller circuit is configured to calculate a rate of change of the capacitance measured at a plurality of discrete applied voltages over a period of time.

In a twenty-fourth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the controller circuit is configured to calculate an average hysteresis change value of the property measured over a plurality of hysteresis measurement cycles.

In a twenty-fifth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein the chemical sensor element is pre-treated under vacuum at a temperature of 50 ℃ to 150 ℃ for at least 3 hours.

In a twenty-sixth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein the chemical sensor element remains in a controlled gas environment until exposed to the fluid test sample.

In a twenty-seventh aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the system may further comprise a flow control valve, wherein the flow control valve controls fluid communication between the upstream flow path and the chemical sensor element.

In a twenty-eighth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein the system is configured to determine the identity (characteristics, species) of one or more analytes present in the fluid sample by assessing hysteresis effects on one or more properties of one or more discrete binding detectors.

In a twenty-ninth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the system is configured to measure the presence of an analyte in the fluid sample by assessing a hysteresis change in one or more parameters of the capacitance-voltage data.

In a thirty-first aspect, in addition to or in the alternative to one or more of the preceding or following aspects, the system further comprises a temperature controller configured to control the temperature of the graphene varactors.

In a thirty-first aspect, in addition to or alternatively to one or more of the foregoing or following aspects, the system is configured to expose the graphene varactors to one or more temperature setpoints for a predetermined time.

In a thirty-second aspect, a method for evaluating a fluid sample is included. The method may include contacting a chemical sensor element comprising one or more discrete binding detectors with the fluid sample, wherein each discrete binding detector may comprise a graphene varactor. The method may include applying a voltage to the graphene varactor as part of a series of hysteresis measurement cycles over a period of time, wherein each hysteresis measurement cycle includes applying a voltage to the graphene varactor as part of a scan over a range of voltages in a first direction and then in a second direction, the second direction being opposite the first direction. The method may include measuring the capacitance of each discrete combined detector caused by the applied voltage, and determining a hysteresis effect associated with the measured capacitance value over the period of time.

In a thirty-third aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further comprise distinguishing the first unique fluid mixture from the second unique fluid mixture based on a measured hysteresis effect exhibited by each of the first unique fluid mixture and the second unique fluid mixture.

In a thirty-fourth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein the step of applying a voltage comprises applying a voltage to the graphene varactors at a plurality of discrete voltages within a voltage range, the voltage range being stepped (stepping) through in increments of 5mV to 100 mV.

In a thirty-fifth aspect, in addition to or in the alternative to one or more of the preceding or following aspects, wherein the applied voltage may be represented as comprising an AC excitation component and a DC bias component.

In a thirty-sixth aspect, in addition to or alternatively to one or more of the preceding or following aspects, the voltage of the DC bias component ranges from-3V to 3V.

In a thirty-seventh aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further comprise characterizing the fluid sample based at least in part on hysteresis effects determined with respect to the one or more parameters.

In a thirty-eighth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the hysteresis effect of the one or more parameters may include a change in one or more of: capacitance at a particular voltage, maximum slope of capacitance versus voltage, minimum capacitance, voltage at minimum capacitance (dirac point), maximum capacitance, full width half maximum/half maximum of capacitance-voltage curve, area of capacitance-voltage curve, difference between maximum capacitance and minimum capacitance, and ratio of maximum capacitance to minimum capacitance.

In a thirty-ninth aspect, in addition to or in the alternative to one or more of the foregoing or following aspects, the method may further comprise identifying a disease state of the individual providing the fluid sample based at least in part on the determined hysteresis effect.

In a fortieth aspect, in addition to or alternatively to one or more of the preceding or following aspects, wherein the method may further comprise identifying a disease state of the individual by matching data collected from the analysis fluid sample to a predetermined data pattern corresponding to the disease state, the collected data comprising data regarding hysteresis effects.

In a fortieth aspect, in addition to or alternatively to one or more of the preceding or following aspects, the method may further comprise determining one or more parameters of capacitance-voltage data of each of the discrete binding detectors caused by the applied voltage, and classifying the discrete analytes within the fluid sample based on the determined hysteresis effect and the combination of the one or more parameters of capacitance-voltage data.

In a forty-second aspect, in addition to or in the alternatives to one or more of the preceding or following aspects, wherein determining one or more parametric capacitance-voltage data comprises determining a forward dirac point voltage for each discrete combined detector caused by the applied voltage.

This summary is an overview of some of the teachings of the present application and is not intended to be an exclusive or exhaustive treatment of the present subject matter. Further details are found in the detailed description and the appended claims. Other aspects will become apparent to those skilled in the art upon reading and understanding the following detailed description and viewing the accompanying drawings, which form a part thereof, wherein each of the drawings is not to be taken in a limiting sense. The scope of this document is defined by the appended claims and their legal equivalents.

Drawings

The aspects may be more fully understood in conjunction with the following drawings, in which:

fig. 1 is a schematic diagram of various components of a system according to various embodiments herein.

Fig. 2 is a schematic top plan view of a chemical sensor element according to various embodiments herein.

Fig. 3 is a schematic diagram of a portion of a measurement zone according to various embodiments herein.

Fig. 4 is a schematic perspective view of a graphene varactor according to various embodiments herein.

Fig. 5 is a schematic cross-sectional view of a portion of a graphene varactor according to various embodiments herein.

Fig. 6 is a graph illustrating capacitance versus gate voltage of a graphene varactor according to various embodiments herein.

Fig. 7 is a graph illustrating capacitance versus gate voltage of a graphene varactor according to various embodiments herein.

Fig. 8 is a graph illustrating capacitance versus gate voltage of a graphene varactor according to various embodiments herein.

Fig. 9 is a schematic diagram of a passive sensor circuit and a portion of a read circuit according to various embodiments herein.

Fig. 10 is a schematic diagram of a circuit arrangement for measuring capacitance of a plurality of discrete graphene varactors according to various embodiments herein.

FIG. 11 is a schematic diagram of an exemplary portion of a measurement system and voltage sweep experiment according to various embodiments herein.

FIG. 12 is a schematic diagram of an exemplary gas measurement system according to various embodiments herein.

Fig. 13 is a graph of gas concentration applied to a graphene varactor versus time, according to various embodiments herein.

Fig. 14 is a graph illustrating capacitance versus gate voltage for a graphene varactor according to various embodiments herein.

Fig. 15 is a graph illustrating forward dirac voltage and reverse dirac voltage versus time for a graphene varactor according to various embodiments herein.

Fig. 16 is a graph illustrating hysteresis versus time of a graphene varactor according to various embodiments herein.

Fig. 17 is a graph illustrating an enlarged view of forward dirac voltage and reverse dirac voltage and hysteresis versus time presented in fig. 15 for ethanol coupled to a graphene varactor according to various embodiments herein.

Fig. 18 is a diagram illustrating an enlarged view of the forward dirac voltage and the reverse dirac voltage and hysteresis versus time presented in fig. 15 for oxygen incorporated into a graphene varactor according to various embodiments herein.

Fig. 19 is a graph of gas concentration applied to a graphene varactor versus time, according to various embodiments herein.

Fig. 20 is a graph illustrating forward dirac voltage, reverse dirac voltage, and hysteresis versus time for a graphene varactor according to various embodiments herein.

Fig. 21 is a graph of gas concentration applied to a graphene varactor versus time, according to various embodiments herein.

Fig. 22 is a graph illustrating forward dirac voltage, reverse dirac voltage, and hysteresis versus time for a graphene varactor according to various embodiments herein.

Fig. 23 is a graph of gas concentration applied to a graphene varactor over time according to various embodiments herein.

Fig. 24 is a graph illustrating forward dirac voltage, reverse dirac voltage, and hysteresis versus time for a graphene varactor according to various embodiments herein.

Fig. 25 is a graph of temperature and gas concentration versus time applied to a graphene varactor according to various embodiments herein.

Fig. 26 is a graph illustrating forward dirac voltage and reverse dirac voltage versus time for a graphene varactor according to various embodiments herein.

Fig. 27 is a graph showing a background-subtracted forward dirac voltage and reverse dirac voltage versus time for a graphene varactor according to various embodiments herein.

Fig. 28 is a graph illustrating hysteresis versus time for a graphene varactor according to various embodiments herein.

Fig. 29 is a graph of dirac voltage signal amplitude versus temperature applied to a graphene varactor according to various embodiments herein.

FIG. 30 is a graph of activation energy as a function of temperature related measurements inferred according to embodiments herein.

Fig. 31 is a graph of gate voltage scan range and gas concentration versus time applied to a graphene varactor according to various embodiments herein.

Fig. 32 is a graph illustrating forward dirac voltage and reverse dirac voltage versus time for a graphene varactor according to various embodiments herein.

Fig. 33 is a graph illustrating hysteresis versus time of a graphene varactor according to various embodiments herein.

Fig. 34 is a plot of variation of forward dirac voltage and reverse dirac voltage versus scan range for a graphene varactor according to various embodiments herein.

Fig. 35 is a plot of variation of forward dirac voltage and reverse dirac voltage versus scan range for a graphene varactor according to various embodiments herein.

Fig. 36 is a plot of gas concentration, forward dirac voltage, and reverse dirac voltage versus time applied to a graphene varactor according to various embodiments herein.

Fig. 37 is a graph of variation of forward dirac voltage, reverse dirac voltage, and hysteresis versus gas concentration according to various embodiments herein.

Fig. 38 is a diagram illustrating forward dirac voltage, reverse dirac voltage, and hysteresis versus gate scan range for a graphene varactor according to various embodiments herein.

Fig. 39 is a graph of principal component analysis of a forward dirac voltage response in accordance with various embodiments herein.

FIG. 40 is a graph of principal component analysis of hysteresis responses in accordance with various embodiments herein.

Fig. 41 is a graph of principal component analysis of combined forward dirac voltage and hysteresis response in accordance with various embodiments herein.

While the embodiments are susceptible to various modifications and alternative forms, details thereof have been shown by way of example and the accompanying drawings and will be described in detail. Nevertheless, it will be understood that the scope of the disclosure is not limited to the particular aspects described. On the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Detailed Description

In embodiments herein, a chemical sensor element having one or more discrete binding detectors may be configured to bind one or more analytes (e.g., volatile Organic Compounds (VOCs)) in a complex sample mixture (e.g., a gaseous sample mixture). The discrete binding detector may include a graphene-based quantum capacitance varactor ("graphene varactor") that may exhibit a capacitance change in response to an applied voltage due to the presence of one or more analytes, such as Volatile Organic Compounds (VOCs), on a surface of the graphene varactor. In this way, the gas sample may be analyzed by contacting the gas sample with a graphene varactor-based sensor element, providing a bias voltage, and measuring a capacitance or voltage value. In many cases, a graphene varactor-based sensor element may be exposed to a range of bias voltages in order to discern features such as the dirac point (or bias voltage when the varactor exhibits the lowest capacitance). The response signal generated by the discrete binding detector in the presence or absence of one or more analytes may be used to characterize the contents of the gaseous mixture. As such, each gaseous mixture may exhibit a unique set of response signals or "fingerprints" for any given array.

While graphene varactors exhibit high sensitivity to various analytes and are capable of characterizing the ability of the contents of a gaseous mixture, the response signal is also affected by hysteresis effects. Hysteresis is, in a broad sense, a dependency of the system state on its history. It has been found herein that graphene varactors can exhibit a significant hysteresis effect based on a previously applied voltage. The hysteresis or hysteresis effects herein may include hysteresis (lag), shift (shift), or other measurable change in one or more properties of the graphene varactors, and may be affected by analyte binding, temperature changes, and/or patterns of applied voltages (e.g., voltage sweeps over various voltage ranges). Without being bound by any particular theory, it is believed that hysteresis has been considered as annoying background noise in the various signals caused by the system. However, in the present case, it has been demonstrated that the benefits of measuring hysteresis alone or in combination with one or more parameters of capacitance-voltage data can provide significant benefits for the classification of analytes within a fluid sample.

According to embodiments herein, the hysteresis effect may be a specific feature that may be used to characterize the sample and/or identify the type and concentration of VOCs present in the sample, alone or in combination with other types of data.

Referring now to fig. 1, a schematic diagram of a system 100 for measuring the presence of an analyte in a gaseous sample is shown, according to various embodiments herein. The system 100 may include a sensing device 160, the sensing device 160 including a chemical sensor element having a plurality of discrete binding detectors for sensing an analyte in a gaseous mixture. The discrete combination detector may include a graphene-based variable capacitor (or graphene varactor), as will be described in more detail below with reference to fig. 3-5. The terms "discrete combination detector" and "graphene varactor" may be used interchangeably herein unless otherwise indicated or the context indicates otherwise.

In the embodiment shown in fig. 1, the sensing device 160 of the system 100 is depicted as a handheld form that may be used in the field, medical clinic, workplace, etc. It should be understood that the systems herein may also include desktop systems for medical clinics, hospitals, laboratories, and the like. However, it should be understood that many other forms for sensing device 160 and system 100 are also contemplated herein.

The sensing device 160 may include a housing 178 and an intake port 162. In some embodiments, the gas inlet port 162 may be in fluid communication with one or more gas sampling apparatus 102. In other embodiments, the gas inlet port 162 may be configured as a mouthpiece into which the subject 104 to be evaluated may blow a breath sample. In other embodiments, the gas inlet port 162 itself may be used as a gas sampling apparatus. The sensing device 160 may be configured to actively draw gas into the housing 178, or it may be configured to passively receive gas from the subject 104 or the gas sampling apparatus 102. In some embodiments, sensing device 160 may include a flow control valve in fluid communication with an upstream flow path relative to the chemical sensor element. In various embodiments, the flow control valve may control fluid communication between the upstream flow path and the chemical sensor element.

The sensing device 160 may also include a display screen 174 and a user input device 176 (e.g., a keyboard). The sensing device 160 may also include a gas outflow port 172. Aspects of the sensing system and apparatus are described in U.S. patent application publication number 2016/0109440A1, the contents of which are incorporated herein by reference. While fig. 1 shows a sensing device 160 adapted to receive gas or gas sampling devices from a subject, it should be understood that other types of gas sampling systems may also be used herein. For example, gas sampling apparatus for use with catheters and endoscope systems may also be used. Exemplary gas sampling apparatus in the context of a catheter or endoscopic apparatus are described in U.S. patent application publication No. 2017/0360337A1, the contents of which are incorporated herein by reference.

In some implementations, the system 100 may include a local computing device 182, where the local computing device 182 may include a microprocessor, input and output circuits, an input device, a visual display, a user interface, and the like. In some implementations, the sensing device 160 may communicate with the local computing device 182 to exchange data between the sensing device 160 and the local computing device 182. The local computing device 182 may be configured to perform various processing steps with data received from the sensing device 160, including but not limited to calculating various parameters of the graphene varactors described herein. However, it should be appreciated that in some embodiments, features associated with the local computing device 182 may be integrated into the sensing device 160. In some implementations, the local computing device 182 may be a laptop computer, a desktop computer, a server (real or virtual), a special-purpose computing device, or a portable computing device (including but not limited to a mobile phone, a tablet, a wearable device, etc.). Local computing device 182 and/or sensing device 160 may communicate with computing devices at remote locations over a data network 184, such as the internet or another network for exchanging data in packets, frames, etc.

In some implementations, the system 100 may also include a computing device, such as a server 186 (real or virtual). In some embodiments, server 186 may be located remotely from sensing device 160. The server 186 may be in data communication with a database 188. Database 188 may be used to store various subject information, such as described herein. In some embodiments, the database may specifically include electronic medical databases (which contain data regarding the health condition of the subject), data patterns related to various conditions and diseases (e.g., data generated from machine learning analysis of a large number of subject datasets), demographic data, and the like. In some implementations, the database 188 and/or the server 186, or a combination thereof, may store data generated by chemical sensor elements as well as data output generated by machine learning analysis.

Referring now to fig. 2, a schematic top plan view of a chemical sensor element 200 is shown, according to various embodiments herein. The chemical sensor element 200 may include a substrate 202. It should be appreciated that the substrate may be formed from many different materials including silicon, glass (glass), quartz, sapphire, polymers, metals, glass (glass), ceramics, cellulosic materials, composites, metal oxides, and the like. The thickness of the substrate may vary. In some embodiments, the substrate has sufficient structural integrity to be handled without excessive bending that could damage the components thereon.

The chemical sensor element herein may include a first measurement zone 204, a second measurement zone 206, and a third measurement zone 208 that can be disposed on a substrate 202. It should be understood that more than three measurement zones may be present on a chemical sensor element herein. In some embodiments, the first measurement zone 204 may define at least a portion of a first gas flow path. The first measurement zone 204 may include a plurality of discrete binding detectors capable of sensing analytes in a gaseous sample (e.g., a breath sample). The second measurement zone 206 may define at least a portion of a second gas flow path. In some embodiments, the second gas flow path may be completely separate from the first gas flow path, while in other embodiments, the second gas flow path may comprise a portion of the first gas flow path.

The second measurement zone 206 may also include a plurality of discrete binding detectors. The chemical sensor element may include a component 210 that stores reference data. The component 210 storing the reference data may be an electronic data storage device, an optical data storage device, a printed data storage device (e.g., a printed code), or the like. The chemical sensor elements described herein are described in more detail in U.S. publication No. 2016/0109440A1, the entire contents of which are incorporated herein by reference.

Each chemical sensor element herein may comprise one or more discrete binding detectors in the form of an array extending over the measurement zone. Referring now to fig. 3, a schematic diagram of a portion of a chemical sensor element is shown, according to various embodiments herein. A plurality of graphene varactors 302 may be disposed in an array on the first measurement zone 204 within the measurement zone. In some embodiments, the chemical sensor element may include a plurality of graphene varactors configured in an array. In some embodiments, the plurality of graphene varactors may include the same surface chemistry (surface chemistries, surface chemistry or chemical properties), while in other embodiments, the plurality of graphene varactors may include different surface chemistries from one another. In some embodiments, graphene varactors with the same surface chemistry may be present in duplicate, triplicate, or more, so that data obtained during a hysteresis measurement cycle may be averaged together to further refine the changes observed in the response signal. The graphene varactors described herein may be described in more detail in U.S. patent No. 9,513,244, the entire contents of which are incorporated herein by reference. It should be appreciated that any of the first measurement region, the second measurement region, the third measurement region, etc. may comprise one or more arrays of a plurality of graphene varactors as described herein.

In some embodiments, the graphene varactors may be heterogeneous in that their binding behavior or specificity to a particular analyte differs from one another (different in groups or different for individual graphene varactors). In some embodiments, some graphene varactors may be dual, triple, or more for verification purposes, but heterogeneous with other graphene varactors. However, in other embodiments, the graphene varactors may be homogenous. While the graphene varactors 302 of fig. 3 are shown as a plurality of square boxes organized in a grid, it should be understood that the graphene varactors may take many different shapes (including but not limited to various polygons, circles, ovals, irregular shapes, etc.), and conversely, the graphene varactors may be arranged in many different patterns (including but not limited to star patterns, zig-zag patterns, radial patterns, symbol patterns, etc.).

In some implementations, the order of the particular graphene varactors 302 across the length 312 and width 314 of the measurement zones may be substantially random. In other embodiments, the order may be specific. For example, in some embodiments, the measurement regions may be ordered such that a particular graphene varactor 302 configured for binding an analyte having a lower molecular weight is located farther from the incoming gas stream than a particular graphene varactor 302 configured for binding an analyte having a higher molecular weight (which is located closer to the incoming gas stream). As such, chromatographic effects (which can be used to provide separation between compounds of different molecular weights) can be exploited to provide optimal binding of chemical compounds to the corresponding graphene varactors.

The number of graphene varactors may be about 1 to about 100000. In some embodiments, the number of graphene varactors may be about 1 to about 10000. In some embodiments, the number of graphene varactors may be about 1 to about 1000. In some embodiments, the number of graphene varactors may be about 2 to about 500. In some embodiments, the number of graphene varactors may be about 10 to about 500. In some embodiments, the number of graphene varactors may be about 50 to about 500. In some embodiments, the number of graphene varactors may be about 1 to about 250. In some embodiments, the number of graphene varactors may be about 1 to about 50.

In some embodiments, each of the graphene varactors suitable for use herein may include at least a portion of one or more circuits. For example, in some embodiments, each graphene varactor may include all or a portion of one or more passive electronic circuits or active circuits. In some embodiments, the graphene varactors herein may include double ended graphene varactors. In some embodiments, the double ended graphene varactors may be adapted to each receive an independent signal from an electrical signal generator. In some implementations, graphene varactors may be formed such that they are integrated directly on an electronic circuit. In some implementations, graphene varactors may be formed such that they are wafer bonded to a circuit. In some implementations, the graphene varactors may include integrated readout electronics, such as readout integrated circuits (ROICs). The electrical properties of the electronic circuit, including resistance or capacitance, may change upon binding (e.g., specific and/or non-specific binding) to a compound from the biological sample. Many different types of circuitry may be used to collect data from the chemical sensor elements, as will be discussed below with reference to fig. 9 and 10.

Referring now to fig. 4, a schematic diagram of a graphene varactor 302 with two ends is shown, according to embodiments herein. It should be appreciated that graphene varactors having various geometries may be prepared in various ways, and that the graphene varactors shown in fig. 4 are but one example in accordance with various embodiments herein.

The graphene varactor 302 may include an insulator layer 402, a gate electrode 404 (or "gate contact"), a dielectric layer (component 504 in fig. 5), one or more graphene layers (e.g., graphene layers 408a and 408 b), and a contact electrode 410 (or "graphene contact"). In some embodiments, the graphene layers 408a-b may be continuous, while in other embodiments, the graphene layers 408a-b may be discontinuous. The gate electrode 404 may be deposited within one or more recesses formed in the insulator layer 402. The insulator layer 402 may be formed of an insulating material (e.g., silicon dioxide), formed on a silicon substrate (wafer), and so forth. The gate electrode 404 may be formed of a conductive material (e.g., chromium, copper, gold, silver, tungsten, aluminum, titanium, palladium, platinum, iridium, and any combination or alloy thereof) that may be deposited on top of the insulator layer 402 or embedded within the insulator layer 402. A dielectric layer (not shown in fig. 4) may be disposed on the surface of insulator layer 402 and gate electrode 404, as shown in more detail in fig. 5. Graphene layers 408a-b may be disposed on a dielectric layer.

The graphene varactor 302 includes eight gate electrode fingers 406a-406h. It should be appreciated that while the graphene varactor 302 shows eight gate electrode fingers 406a-406h, any number of gate electrode finger configurations are contemplated. In some embodiments, a single graphene varactor may include less than eight gate electrode fingers. In some embodiments, a single graphene varactor may include more than eight gate electrode fingers. In other embodiments, a single graphene varactor may include two gate electrode fingers. In some embodiments, a single graphene varactor may include 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more gate electrode fingers.

The graphene varactor 302 may include one or more contact electrodes 410 disposed on portions of the graphene layers 408a and 408 b. The contact electrode 410 may be formed of a conductive material (e.g., chromium, copper, gold, silver, tungsten, aluminum, titanium, palladium, platinum, iridium, and any combination or alloy thereof). Other aspects of exemplary graphene varactors may be found in U.S. patent 9,513,244, the entire contents of which are incorporated herein by reference.

Referring now to fig. 5, a schematic diagram of a portion of a cross section of an exemplary graphene varactor is shown, in accordance with various embodiments herein. The graphene varactor may include a substrate 502, such as a silicon substrate (wafer). The insulator layer 402 may be disposed on the substrate 502 and the gate electrode 404 may be recessed into the insulator layer 402. The gate electrode 404 may be formed by depositing a conductive material in a recess in the insulator layer 402, as discussed above with reference to fig. 4. A dielectric layer 504 may be formed on the surfaces of the gate electrode 404 and the insulator layer 402. In some examples, the dielectric layer 504 may be formed of a material such as silicon dioxide, aluminum oxide, hafnium oxide, zirconium dioxide, hafnium silicate, or zirconium silicate. The graphene layer 408 is disposed on the dielectric layer 504, and the contact electrode 410 may be disposed in contact with the graphene layer 408. In some examples, the dielectric layer 504 may include multiple layers of dielectric materials listed herein. In some embodiments, the dielectric layer 504 may comprise alternating layers of different dielectric materials. In some embodiments, the dielectric layer 504 may include alternating layers of aluminum oxide and hafnium oxide.

In some embodiments herein, to maintain the stability of the graphene varactors herein, the chemical sensor elements may be pre-treated under vacuum at a temperature of 50 ℃ to 150 ℃ for at least 3 hours. In various embodiments, the chemical sensor element may be pre-treated under vacuum at a temperature of 120 ℃ to 150 ℃ for 10 to 20 hours. In various embodiments, the chemical sensor element may be pre-treated under vacuum, the temperature may be greater than or equal to 50 ℃, 60 ℃, 70 ℃, 80 ℃, 90 ℃, 100 ℃, 110 ℃, 120 ℃, 130 ℃, 140 ℃, 150 ℃, 160 ℃, 170 ℃, 180 ℃, 190 ℃, or 200 ℃, or may be an amount falling within a range between any of the foregoing values. It should be appreciated that in some embodiments, one or more hysteresis effects may be temperature dependent. In some embodiments, the graphene varactors described herein may maintain a constant temperature for a constant period of time to reduce the effect of temperature variations on one or more hysteresis effects.

Furthermore, the chemical sensor element herein may be maintained in a controlled gaseous environment until it is exposed to the gaseous test sample. For example, the chemical sensor element may be maintained under a controlled gas environment, including oxygen, nitrogen, or an inert gas (e.g., argon, helium, xenon, krypton, or neon).

Without wishing to be bound by any particular theory, it is believed that one or more measurable parameters of the graphene varactors herein exhibit hysteresis effects, such as capacitance versus voltage value (capacitance-voltage value relationship) affected by various factors. Factors contributing to the measurable hysteresis effect may include changes in the voltage sweep rate and/or voltage sweep range applied to the graphene varactors, binding of the analyte to the graphene varactors, changes in the temperature applied to the graphene varactors, changes in the background and/or baseline gas environment, changes in the total number of voltage sweeps during measurement, surface chemistry on the graphene, composition/configuration of the dielectric layer, surface chemistry on the dielectric layer, or any combination of these factors. In some embodiments, one or more of these factors may be manipulated in order to enhance the sensed hysteresis effect. For example, in some embodiments, the voltage sweep rate, the speed of the voltage sweep, the range of the voltage sweep, and/or the temperature of the graphene varactors, among other factors, may be manipulated or controlled in order to enhance the sensed hysteresis effect.

In various embodiments, the systems herein may be configured to measure one or more hysteresis effects of some property of the system, including a change in measured value between a scan in a first direction (e.g., a low-to-high applied voltage or a high-to-low applied voltage) and a subsequent scan in a second direction (which may be a direction opposite the first direction). Some hysteresis effects determined in the system may include hysteresis effects of one or more of the following parameters: capacitance at a particular voltage, maximum slope of capacitance versus voltage, minimum capacitance, voltage at minimum capacitance (dirac voltage), forward dirac voltage, reverse dirac voltage, maximum capacitance, full width at half maximum of the capacitance-voltage curve, area of the capacitance-voltage curve, difference between maximum capacitance and minimum capacitance, and ratio of maximum capacitance to minimum capacitance.

The system herein may be configured to characterize a test sample, such as a fluid test sample, based on the determined hysteresis effect. The fluid test sample may include, but is not limited to, a liquid sample and a gaseous sample. The fluid test sample may include a liquid sample and a gaseous sample from a human body. It should be understood that the terms "fluid test sample" and "fluid sample" may be used interchangeably. In various embodiments, the system may be configured to utilize the determined hysteresis effect as a data input in a pattern matching operation, wherein the result of the pattern matching operation characterizes the fluid test sample and/or the patient providing the fluid test sample. In various embodiments, the system may determine the identity (characteristics, species) of one or more analytes present in the gaseous sample by determining a hysteresis effect on one or more properties of one or more discrete binding detectors. The hysteresis effects described herein will be mentioned in more detail below.

The change in the capacitance of the graphene varactor with respect to a parameter of the voltage value may be measured by passing an applied voltage to the graphene varactor over a range of voltages that starts at one limit and moves to another limit as part of a voltage sweep. Moving from one boundary to another may include moving continuously or in multiple discrete steps as part of scanning across multiple voltages. As an example, the measurement of the response may include measuring capacitance-voltage (i.e., C-V _g The method comprises the steps of carrying out a first treatment on the surface of the Wherein V is _g Is the gate voltage applied to the graphene varactor) curve, as will be discussed in more detail with reference to fig. 6-8. In various embodiments, measuring the presence of an analyte in a gaseous sample may include measuring a response in a resulting capacitance-voltage curve. In other embodiments, measuring the presence of an analyte in the fluid sample may include assessing a hysteresis change in one or more parameters of the capacitance-voltage data.

Various voltage sweeps of the graphene varactors described herein may be used to determine hysteresis effects that are affected by variations in the voltage sweep rate and/or the voltage sweep range applied to the graphene varactors. Referring now to FIG. 6, a capacitance versus voltage (i.e., C-V is shown in accordance with various embodiments herein _g ) Is illustrated in the exemplary line graph 600. Line graph 600 may include a forward scan C-V _g Curve 602 and reverse scan C-V _g Curve 604, where the scan range includes a voltage range from-2.0V to 2.0V. Additional values for scan range and scan time are discussed in more detail below. In the example line graph 600, the gate voltage may be scanned across the voltage range in either direction between each limit, as described elsewhere herein. Scanning C-V in the forward direction _g In curve 602, at a forward dirac voltage 606 (i.e., V _DF Or the voltage at which the varactor diode exhibits the lowest capacitance during forward scan), the capacitance of the varactor diode reaches a minimum capacitance C _min . Scanning C-V in reverse _g In curve 604, at a reverse dirac voltage 608 (i.e., V _DR Or the voltage at which the varactor diode exhibits the lowest capacitance during forward scan), the capacitance of the varactor diode reaches a minimum capacitance C _min 。V _DF And V _DR The difference between the values may be a representation of the sample being analyzed. For example, V _DF And V _DR The difference between the values may depend on the concentration of certain analytes and the type of analyte. V (V) _DF And V _DR The difference between the values may also depend on the range of the voltage sweep, the voltage sweep rate, the temperature applied to the graphene varactors, and other factors. V (V) _DF And V _DR The difference between the values is only one example of hysteresis effects herein.

It should be appreciated that the hysteresis effect may be affected by the voltage sweep applied to the graphene varactors. In some embodiments, a larger scan window between voltage limits (lower and upper) may be used to increase the magnitude of one or more hysteresis effects. In some embodiments, a smaller scan window between voltage limits may be used to reduce the magnitude of one or more hysteresis effects. In other embodiments, slower sweeps between voltage limits may reduce the amount of drift (drift) present in one or more hysteresis effects.

The data collected from the voltage scan of the graphene varactors described herein may be used to characterize a sample and/or determine the concentration of an analyte and to distinguish between analyte types in the sample. Referring now to fig. 7, response signals before and after exposure of a single graphene varactor to an exemplary gaseous mixture are shown on a plot of capacitance versus gate voltage, according to various embodiments herein. Response signal of graphene varactors, such as C-V, before exposure to gaseous mixtures _g Shown in curve 702. Response signal of same graphene varactor after exposure to gaseous mixture, such as C-V _g Shown by curve 704. The response signal (e.g., capacitance versus voltage curve shown in fig. 7) may be established by measuring the capacitance over a range of voltages before and after the graphene varactor is exposed to the gaseous mixture.

As the analyte in the sample mixture is sensed by the graphene varactors upon binding, several different parameters of the graphene varactors response signal may change from a baseline value to a higher or lower value and the shape of the response signal may change, both due to interactions between graphene and analyte and hysteresis affected by the particular analyte or condition in the system introduced by the previously applied voltage. Referring now to fig. 8, the response signals of individual graphene varactors (also shown in fig. 7) before and after exposure to the gaseous mixture are shown, but various annotations are provided to highlight the variation of different parameters of the graphene varactor response signals, which can be analyzed to characterize the content of the gaseous mixture. For example, these different parameters may include, but are not limited to, a shift in dirac voltage (i.e., a voltage when the capacitance of the graphene varactor is at a minimum), a change in the minimum capacitance of the graphene varactor, a change in the slope of the response signal or a change in the maximum capacitance of the graphene varactor, a change in capacitance at a particular bias voltage, and so forth (other examples of parameters will be described below). It should be appreciated that one or more hysteresis effects are affected by the baseline hysteresis of the graphene varactors themselves. In some implementations, the one or more hysteresis effects may be a function of an initial baseline hysteresis of each graphene varactor in the system. Baseline hysteresis can be measured in a controlled gas environment. It will be further appreciated that in various embodiments, the scan range may be delayed until all of the graphene varactors are in the gaseous sample of interest (e.g., breath sample from alveoli) to allow the graphene varactors to equilibrate in the gaseous sample of interest before they respond to the undesired gaseous sample (e.g., breath sample from the oral cavity).

In FIG. 8, the response signal of a graphene varactor before exposure to a gaseous mixture is shown as C-V _g Curve 702, while the response signal of the same graphene varactor after exposure to a gaseous mixture is shown as C-V _g Curve 704. The shift in dirac voltage before and after exposure is indicated by arrow 806. The change in minimum capacitance of the graphene varactors before and after exposure is represented by arrow 808. C-V prior to exposure to a gaseous mixture through a graphene varactor _g Slope 810 of curve 702 and C-V of graphene varactors after exposure to a gaseous mixture _g Comparison of the slope 812 of curve 704 to obtain a change in slope of the response signal. The change in the maximum capacitance of the graphene varactor is represented by arrow 814.

In some embodiments, the ratio of the maximum capacitance to the minimum capacitance may be used to characterize the contents of the gaseous mixture. In some embodiments, the ratio of the maximum capacitance to the shift of the dirac point may be used to characterize the content of the gaseous mixture. In other embodiments, the ratio of the minimum capacitance to the shift in slope of the response signal may be used to characterize the content of the gaseous mixture. In some embodiments, the ratio of any parameter (including shift in dirac point, change in minimum capacitance, change in response signal slope, or change in maximum capacitance) may be used to characterize the contents of the sample mixture. According to embodiments herein, the hysteresis effect observed for any of these values (as well as other types of values discussed) may be used to characterize the contents of the sample mixture.

In many cases, each graphene varactor can be tested using a number of different applied voltage(s), the resulting data forming a C-V _g A curve. The plurality of voltages may fall within a range from a lower voltage limit to an upper voltage limit. To observe the hysteresis effect, in many cases the voltage may start from a lower limit and then gradually increase to an upper limit, scanning across the range in a first direction and then scanning in an opposite (or second) direction (e.g., from the upper limit to the lower limit). Thus, in various embodiments, the first direction may include a sweep from a lower voltage limit to an upper voltage limit, and the second direction is a sweep from an upper voltage limit to a lower voltage limit. However, in other embodiments, the first direction may include a sweep from an upper voltage limit to a lower voltage limit, and the second direction is a sweep from a lower voltage limit to an upper voltage limit. In various embodiments, scanning in the second direction is performed after scanning in the first direction constitutes a hysteresis measurement cycle.

The values of the lower voltage limit and the upper voltage limit may be predetermined or may be dynamically determined. In various embodiments, the lower voltage limit and the upper voltage limit are preset values and may be selected from the following values: such as-3.0V or less, -2.9V, -2.8V, -2.7V, -2.6V, -2.5V, -2.4V, -2.3V, -2.2V, -2.1V, -2.0V, -1.9V, -1.8V, -1.7V, -1.6V, -1.5V, -1.4V, -1.3V, -1.2V, -1.1V, -1.0V, -0.9V, -0.8V, -0.7V, -0.6V, -0.5V, -0.4V, -0.3V 0.2V, -0.1V, 0V, 0.1V, 0.2V, 0.3V, 0.4V, 0.5V, 0.6V, 0.7V, 0.8V, 0.9V, 1.0V, 1.1V, 1.2V, 1.3V, 1.4V, 1.5V, 1.6V, 1.7V, 1.8V, 1.9V, 2.0V, 2.1V, 2.2V, 2.3V, 2.4V, 2.5V, 2.6V, 2.7V, 2.8V, 2.9V or 3.0V or higher, or a voltage value falling between any of the above values. In various embodiments, the lower voltage limit and the upper voltage limit are preset values, and may be selected from the following values of the range: -5V to 5V; -4V to 4V; -3V to 3V; -2V to 2V; -1.5V to 1.5V; or-1V to 1V.

While the instantaneous applied voltage herein may be considered as the sum of the DC bias component and the AC component, it should be understood that the particular applied voltage value referred to herein generally represents a DC voltage bias or offset (offset) value. This is because the average value of the AC component over a non-transient period will be zero. As such, unless otherwise indicated to the contrary or otherwise stated in the context, reference herein to a voltage value shall refer to a DC offset or offset component of an applied voltage, while it is understood that the corresponding instantaneous voltage value may vary based on the AC component. The waveform of the AC component may take many different forms. For example, they may be sinusoidal, square, triangular, trapezoidal, sloped, zig-zag, complex, etc.

In some embodiments, the lower voltage limit and the upper voltage limit are dynamically determined values. For example, the limits may be changed based on a previously applied excitation voltage and/or a previously observed value associated with the graphene sensor and/or a previously observed hysteresis effect.

In some embodiments, the upper and lower voltage limits are static between successive hysteresis measurement cycles. In other embodiments, the upper and lower voltage limits may vary between successive hysteresis measurement cycles. For example, in some embodiments, a first hysteresis measurement cycle may include using the widest range of excitation voltages, and successive hysteresis measurement cycles may use a narrower range of excitation voltages.

Various timing schemes may be used to scan across a range of voltages. In some embodiments, the scan in the first direction may be followed by a scan in the second direction. In other embodiments, scanning in the first direction may be followed by a pause, followed by scanning in the second direction. The duration of the pause between scans may comprise a length of from 1 millisecond (ms) to 5 seconds. In some embodiments, the duration of the pause between scans may be greater than or equal to 10ms, 20ms, 30ms, 40ms, 50ms, 60ms, 70ms, 80ms, 90ms, 100ms, 200ms, 300ms, 400ms, 500ms, 600ms, 700ms, 800ms, 900ms, or 1 second, 2 seconds, 3 seconds, 4 seconds, or 5 seconds, or may be an amount falling within a range between any of the foregoing values.

In some embodiments, the length of the duration of the pause between scans may be greater than 5 seconds. In various embodiments, the duration of the pause between scans may be greater than or equal to 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, 16 seconds, 17 seconds, 18 seconds, 19 seconds, 20 seconds, 21 seconds, 22 seconds, 23 seconds, 24 seconds, 25 seconds, 26 seconds, 27 seconds, 28 seconds, 29 seconds, 30 seconds, 31 seconds, 32 seconds, 33 seconds, 34 seconds, 35 seconds, 36 seconds, 37 seconds, 38 seconds, 39 seconds, 40 seconds, 41 seconds, 42 seconds, 43 seconds, 44 seconds, 45 seconds, 46 seconds, 47 seconds, 48 seconds, 49 seconds, 50 seconds, 51 seconds, 52 seconds, 53 seconds, 54 seconds, 55 seconds, 56 seconds, 57 seconds, 58 seconds, 59 seconds, or 60 seconds, or may be an amount falling within a range between any of the foregoing values. In other embodiments, the dwell time between scans may be greater than 1 minute.

The change in any one of the parameters of capacitance versus voltage value provides data that can reflect the binding state of the analyte to the graphene varactor and can be used to characterize the sample and/or to distinguish between various analytes and analyte concentrations in the sample. Various measurement circuitry (discussed with reference to fig. 9 and 10) may be used to measure the change in parameters of the capacitance-voltage curve of the graphene varactors.

Measurement circuitry suitable for use herein may include active sensing circuitry and passive sensing circuitry. Such a circuit arrangement may implement wired (direct electrical contact) sensing techniques or wireless sensing techniques. Referring now to fig. 9, a schematic diagram of a passive sensor circuit 902 and a portion of a read circuit 922 in accordance with aspects herein is shown. In some implementations, the passive sensor circuit 902 can include a metal oxide-graphene varactor 904 coupled to an inductor 910 (where RS represents a series resistance and CG represents a varactor capacitor). In some implementations, the read circuit 922 may include a read coil having a resistor 924 and an inductance 926.

The measurement circuitry herein may also include active sensing circuitry. In various embodiments, the measurement circuitry (measurement circuity) may include an electrical signal generator configured to generate a series of hysteresis measurement cycles over a period of time. This measurement circuit arrangement may comprise an electrical signal generator configured to generate and transmit an applied voltage, which generated and transmitted applied voltage can be represented as an alternating voltage (or excitation voltage) superimposed on the bias voltage. It should be appreciated that there are many ways to generate such an applied voltage.

In some embodiments, the measurement circuitry may include an electrical signal generator configured to generate and transmit an applied voltage including a sinusoidal waveform, square waveform, triangular waveform, trapezoidal waveform, ramp waveform, sawtooth waveform, or complex waveform alternating voltage superimposed on the bias voltage. In some embodiments, the electrical signal generator may be configured to generate an applied voltage at a plurality of voltages to be applied to the one or more graphene varactors, the voltages falling within a range from a lower voltage limit and an upper voltage limit, the voltages starting from one limit and moving to another limit as part of a scan across the multiple voltages. In some embodiments, the electrical signal generator may be configured to generate excitation currents at a plurality of voltages to be applied to the one or more graphene varactors, the voltages falling within a range from a lower limit and an upper limit, the voltages starting from one limit and moving to another limit as part of a voltage sweep.

For example, referring now to fig. 10, a schematic diagram of an example of a measurement circuit arrangement 1000 for measuring capacitance of a plurality of graphene sensors according to various embodiments herein is shown. The measurement circuitry 1000 may include a capacitance-to-digital converter (CDC) 1002 in electrical communication with a Multiplexer (MUX) 1004. The multiplexer 1004 may provide selective electrical communication with a plurality of graphene varactors 1006. The connection to the other side of the graphene varactor 1006 may be controlled by a switch 1003 (controlled by a CDC) and may provide selective electrical communication with a first digital-to-analog converter (DAC) 1005 and a second digital-to-analog converter (DAC) 1007. The other side of the DACs 1005, 1007 may be connected to a Bus (Bus) device 1010, or in some cases to the CDC 1002. The circuit arrangement may also include a microcontroller 1012 (or controller circuit), which will be discussed in more detail below.

In this case, the signal from the CDC controls a switch 1003 between the output voltages of two programmable digital-to-analog converters (DACs) 1005 and 1007. The programmed voltage difference between the DACs determines the excitation amplitude (and represents the AC component of the applied voltage), provides an additional programmable scaling factor for the measurement, and allows for a wider range of capacitances to be measured than specified by the CDC. The bias voltage at the measurement capacitance is equal to the difference between the bias voltage at the CDC input (via a multiplexer, typically equal to VCC/2, where VCC is the supply voltage) and the average voltage of the stimulus signal, which is programmable. In some embodiments, a buffer amplifier and/or bypass capacitor may be used at the DAC output to maintain a stable voltage during switching or switching. It should be understood that the circuits of fig. 9 and 10 are merely exemplary. Many different approaches are contemplated herein.

The measurement circuitry may comprise a capacitive sensor configured to measure the capacitance of the discrete binding detector caused by the excitation voltage. The measurement circuitry may further comprise a controller circuit configured to determine a change in at least one of a measured capacitance relative to the voltage value and a calculated value based on the measured capacitance or the voltage over a period of time. In various embodiments, measuring the relationship of capacitance to voltage value may include one or more of: capacitance at a particular voltage, maximum slope of capacitance versus voltage, minimum capacitance, voltage at minimum capacitance (dirac voltage), ratio of maximum capacitance and maximum capacitance to minimum capacitance. In various embodiments, the controller circuit is configured to measure a difference between the forward dirac voltage and the reverse dirac voltage. In some implementations, the controller circuit is configured to calculate a rate of change of capacitance measured over a period of time at a plurality of discrete DC bias voltages. In some embodiments, the controller circuit is configured to calculate an average hysteresis change value of the property measured over a plurality of hysteresis measurement cycles. In various embodiments, the controller circuit is configured to determine a forward dirac point voltage and/or a reverse dirac point voltage.

In some implementations, another portion of the measurement circuitry or system herein may include a temperature controller configured to control the temperature of the graphene varactors. In some embodiments, the temperature controller may include a thermistor, thermocouple, resistive Thermal Device (RTD), or the like. In various embodiments, controlling the temperature of the graphene varactors includes exposing the graphene varactors to one or more temperature setpoints for a predetermined time. In some embodiments, a sequence may be used that includes increasing the temperature set point over a predetermined time period. In other embodiments, a sequence comprising decreasing the temperature set point over a predetermined time period may be used. In other embodiments, a sequence comprising increasing the temperature set point and then decreasing the temperature set point may be used.

The system for measuring the presence of an analyte in a gaseous sample may be configured to measure a difference in capacitance-voltage values when the applied voltage is scanned in a first direction between a lower voltage limit and an upper voltage limit relative to when scanned in a second direction between the upper voltage limit and the lower voltage limit. Thus, in various embodiments, the first direction is a sweep from a lower voltage limit to an upper voltage limit, and the second direction is a sweep from an upper voltage limit to a lower voltage limit. In various embodiments, the first direction is a sweep from an upper voltage limit to a lower voltage limit, and the second direction is a sweep from a lower voltage limit to an upper voltage limit.

Various values of voltages suitable for use in the range from the lower limit to the upper limit as contemplated herein are further described below. In various embodiments, each hysteresis measurement cycle includes delivering a DC bias voltage to a discrete combination detector at a plurality of discrete DC bias voltage values across a range of DC bias voltages, as discussed in more detail below.

The calculated values may be used for diagnosis. In some cases, the calculated values described above may be indicative of the identity and/or concentration of a particular volatile organic component of the gas sample. As such, each of the above calculated values may be used as a unique data portion forming part of a pattern for a given subject and/or a given gas sample. The pattern may then be matched with pre-existing patterns or real-time identified patterns derived from a large stored dataset by techniques such as machine learning or other techniques, where such patterns are determined to be characteristic of various conditions or disease states, as described elsewhere herein. The above-described computational aspects may also be used for other purposes, diagnostic or other purposes.

In some implementations, the calculations (such as those described above) may be performed by the controller circuit. The controller circuit may be configured to receive an electrical signal reflecting a capacitance or voltage of the graphene varactor. In some implementations, the controller circuit may include a microcontroller to perform these calculations. In some embodiments, the controller circuit may include a microprocessor in electrical communication with the measurement circuitry. The microprocessor system may include components such as address bus, data bus, control bus, clock, CPU, processing device, address decoder, RAM, ROM, etc. In some embodiments, the controller circuit may include a computing circuit (e.g., an application specific integrated circuit-ASIC) in electrical communication with the measurement circuitry.

Further, in some implementations, the system may include non-volatile memory. In some implementations, the nonvolatile memory may be configured to store measured capacitance values of the discrete combined detector across a range of DC bias voltages. In other embodiments, the non-volatile memory may be configured to store a baseline capacitance of the discrete combined detector across a range of DC bias voltages. In some implementations, the nonvolatile memory may be where sensitivity calibration information for the graphene varactors is stored.

For example, graphene varactors may be tested in a manufacturing facility where sensitivity to various analytes (e.g., VOCs) may be determined and then stored on EPROM or similar components. Additionally, or alternatively, the sensitivity calibration information may be stored in a central database and referenced to the chemical sensor element serial number when subject data is sent to a central location for analysis and diagnosis. These components may be included in any of the hardware described herein.

In some embodiments herein, the components may be configured to communicate over a network (e.g., the internet or similar network). In various embodiments, a central storage and data processing facility may be included. In some embodiments, data collected from sensors in the presence of a subject (locally) may be sent to a central processing facility (remote) via the internet or similar network, and patterns from particular subjects being evaluated may be compared to patterns of thousands or millions of other subjects, many of whom have been previously diagnosed with various conditions, and in which such condition data has been stored.

The pattern matching algorithm may be used to match the pattern of the current subject with a predetermined pattern that is related to (and thus can be used for) other subjects or health status categories (e.g., disease or condition specific categories). Each predetermined pattern may include a predetermined likelihood of having a given condition or disease state. Thus, in various embodiments herein, the system may use a pattern matching or pattern recognition algorithm to compare a data set reflecting a particular patient/individual (the data set including hysteresis data) to one or more previously determined patterns to determine a best matching pattern, wherein the particular previously determined pattern as the best matching is indicative of the health state of the patient.

For example, by evaluating a large number of patient data sets, a predetermined pattern reflecting a particular health state or a particular disease state may be identified by machine learning analysis or another similar algorithmic technique, where the health state and/or disease state is indicated in order to facilitate supervision of the machine learning method. For example, the training data set used herein to generate the predetermined pattern may include: 1. ) Information about hysteresis data and/or other characterization data of a fluid test sample of a group of patients, 2.) information about a particular diagnosis or other health status of the same group of patients, and/or 3.) other types of data described herein. Such training data sets may be processed with machine learning algorithms or similar algorithmic techniques to generate one or more patterns reflecting hysteresis data for volatile organic compounds as well as other data that can be used to identify certain diagnoses or health conditions.

Algorithms may be used herein to create new patterns/models using any of a number of machine learning techniques, or to apply the results of previously calculated models using these techniques (e.g., logistic regression, random forests, or artificial neural networks). Many different pattern matching or pattern recognition algorithms may be used. For example, in some embodiments, a least squares algorithm may be used to identify a particular predetermined pattern in which the combined dataset most closely matches. In various embodiments, standard pattern classification methods may be used, including but not limited to gaussian mixture models, clustering, hidden markov models, and bayesian methods, neural network models, and deep learning.

Following the pattern matching operations herein, a likelihood of having a given condition or disease state may be generated. For example, in some embodiments, this may be performed remotely and provided back to the facility where the subject is currently located via a data network. In other embodiments, such operations may be performed locally on a device of the system.

Referring now to fig. 11, a schematic diagram of an exemplary portion of a measurement system 1100 and an example of a DC voltage sweep experiment are shown, according to various embodiments herein. Measurement system 1100 shows a plurality of graphene varactors 1102, 1104, 1106, and 1108 as part of chemical sensor element 200. An applied voltage signal may be applied to each of the graphene varactors 1102, 1104, 1106, and 1108, and a capacitance-voltage value may be measured. The voltage signal shown in fig. 11 comprises two separate signals, including an ac voltage superimposed on a first input voltage 1110, and a second input voltage 1112. It should be appreciated that the second input voltages 1112 do not alternate. The first input voltage 1110 may be applied to a first end 1114 of each graphene varactor, and the second input voltage 1112 may be applied to a second end 1116 of each graphene varactor.

The difference between the offset of the applied second input voltage 1112, which remains constant during the survey scan, and the offset of the alternating voltage superimposed on the first input voltage 1110 is the DC bias voltage. In fig. 11, three DC bias voltages are shown and are represented as a first DC bias voltage 1124, a second DC bias voltage 1126, and a third DC bias voltage 1128. It should be appreciated that although only three DC biases are shown in fig. 11, any number of DC bias voltages are contemplated herein. It should be appreciated that the DC bias voltage may be increased or decreased during a survey scan, depending on the values of the applied input voltage and the applied ac voltage. The value of the DC bias voltage may be changed throughout the survey scan by increasing the ac voltages at the high and low levels of the DAC superimposed on the first input voltage 1110 while maintaining a constant difference between the high and low levels of the DAC in order to maintain a constant excitation amplitude 1118. It should be appreciated that while the example given in fig. 11 shows three AC cycles per DC bias voltage, the actual number of AC cycles applied at each DC bias voltage may include 1 to 10000 or more cycles. It should be appreciated that although the frequencies shown in fig. 11 are set to 205kHz, the frequencies may include those in the range from 10kHz to 1MHz discussed below.

It will be appreciated that in the schematic diagram shown in fig. 11, the CDC of the measurement circuitry controls the switch between the output voltages of the two programmable DACs (not shown). The programmed voltage difference between the DACs determines the excitation amplitude 1118 of the ac voltage superimposed on the first input voltage 1110, provides an additional programmable scaling factor for the measurement, and allows for a wider range of capacitances to be measured than specified by the CDC. The ac voltage superimposed on the first input voltage 1110 applied to the first terminal 1114 may include an ac voltage having a waveform in the shape of a sine waveform. In various embodiments, the waveform may include square waveforms, sawtooth waveforms, ramp waveforms, triangular waveforms, trapezoidal waveforms, and the like. The lower voltage limit 1120 and the upper voltage limit 1122 define the magnitude of the excitation amplitude 1118.

The excitation amplitude of the alternating voltage superimposed on the first input voltage 1110 applied to the first end 1114 of the graphene varactor may include an excitation amplitude of 5mV, 10mV, 15mV, 20mV, 25mV, 50mV, 75mV, 100mV, 125mV, 150mV, 175mV, 200mV, 225mV, 250mV, 275mV, or 300 mV.

The excitation amplitude of the voltages used in the methods herein may include excitation amplitudes within a range, wherein any of the aforementioned voltages may serve as a lower voltage limit or an upper voltage limit for the range, provided that the lower voltage limit of the range is a value less than the upper voltage limit of the range. It should be appreciated that the lower and upper voltage limits of the applied ac voltage may be set independently by each of the two DACs. It will be further appreciated that by dynamically increasing the values of the lower and upper voltage limits, the lower and upper voltage limits of the applied ac voltage may be varied during the measurement, but the excitation amplitude is maintained constant between the limits. In some embodiments, the excitation amplitude may be maintained at 100mV throughout the voltage sweep applied at multiple voltage values.

The second input voltage 1112 applied to the second end 1116 of the graphene varactor may include a constant voltage maintained at 500mV, 1.0V, 1.1V, 1.2V, 1.3V, 1.4V, 1.5V, 1.6V, 1.65V, 1.7V, 1.8V, 1.9V, 2.0V, 2.1V, 2.2V, 2.3V, 2.4V, 2.5V, 2.6V, 2.7V, 2.8V, 2.9V, or 3.0V for a measurement duration. It should be understood that an input voltage as used in the methods herein may include passing the input voltage over a range, where any of the foregoing voltages may serve as a lower or upper limit of the range, so long as the lower limit of the range is a value less than the upper limit of the range. It should be appreciated that the second input voltage 1112 applied to the second end 1116 of the graphene varactor may include a constant voltage maintained at 3V or higher, depending on the thickness of the dielectric layer.

Many different ranges of input voltages may be used for each hysteresis measurement cycle. In some embodiments, the input voltage used in the methods herein may include-6V, -5V, -4V, -3V, -2.5V, -2.0V, -1.5V, -1.0V, -0.5V, 1.0V, 1.5V, 2.0V, 2.5V, 3.0V, 4V, 5V, or 6V. It should be understood that an input voltage as used in the methods herein may include delivering the input voltage over a range, where any of the foregoing voltages may serve as a lower or upper limit of the range, so long as the lower limit of the range is a value less than the upper limit of the range. In various embodiments, a voltage sweep range suitable for use herein may include a plurality of voltages ranging from-6V to 6V. In various embodiments, the voltage sweep range may include: -5V to 5V; -4V to 4V; -3V to 3V; -2V to 2V; -1.5V to 1.5V; or-1V to 1V.

The excitation signal may be applied to the graphene varactors at a frequency specified by the CDC. The frequency of the applied excitation signal may include a frequency that may be greater than or equal to 10kHz, 20kHz, 30kHz, 40kHz, 50kHz, 60kHz, 70kHz, 80kHz, 90kHz or 100kHz, 125kHz, 150kHz, 175kHz, 200kHz, 225kHz, 250kHz, 275kHz, 300kHz, 325kHz, 375kHz, 400kHz, 425kHz, 450kHz, 475kHz, 500kHz, 525, 550, 575, 600kHz, 625kHz, 650kHz, 675, 700kHz, 725, 750kHz, 775, 800kHz, 825, 850kHz, 875kHz, 900kHz, 925kHz, 950kHz, 975kHz or 1000MHz, or may be an amount falling within a range, wherein any of the foregoing frequencies may be used as the lower limit or upper limit of the range, so long as the lower limit of the range is a value that is less than the upper limit of the range.

Applied voltage/hysteresis measurement cycle

The hysteresis measurement cycle herein may include a voltage sweep in a first direction followed by a voltage sweep in the opposite direction to observe a change in a measurable parameter (as a hysteresis effect). Many different ranges of applied voltages may be used for each hysteresis measurement cycle. In some embodiments, the applied voltage used in the methods herein may include-6.0V, -5.0V, -4.0V, -3.0V, -2.5V, -2.0V, -1.5V, -1.0V, -0.5V, 1.0V, 1.5V, 2.0V, 2.5V, 3.0V, 4.0V, 5.0V, or 6.0V. It should be understood that the application of voltages as used in the methods herein may include delivering an application voltage within a range, where any of the foregoing voltages may serve as a lower or upper limit of the range, so long as the lower limit of the range is a value less than the upper limit of the range.

In various embodiments, a "sweep" across (within) a range of voltages may include a number of discrete measurements made at a number of discrete bias voltages within a range of voltages during the sweep. In some embodiments, the hysteresis measurement cycle herein may include a forward sweep (from a low applied voltage to a high applied voltage). In some embodiments, the hysteresis measurement cycle herein may include a reverse sweep (from a high applied voltage to a low applied voltage). In some embodiments, the hysteresis measurement cycle herein may include both forward and reverse scans. In some embodiments, the hysteresis measurement cycle herein may include forward scanning and reverse scanning, or any combination thereof.

In some embodiments, a voltage of 0V or 0.5V (or other "reset" voltage) may be applied at the end of one hysteresis measurement cycle and before the next hysteresis measurement cycle or at the end of all tests.

The length of time for each hysteresis measurement cycle may depend on various factors including the total number of capacitance measurements during the cycle, the total bias voltage range covered, the voltage step per measurement, the time per measurement, etc. In some embodiments, the time period of each hysteresis measurement cycle may be about 0.1, 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 20, 30, 45, 60, 120 seconds or more. It will be appreciated that the time period of each hysteresis measurement cycle may include a range wherein any of the aforementioned points in time may serve as a lower or upper limit for the range, provided that the lower limit of the range is a value less than the upper limit of the range.

In some embodiments, the total time of all hysteresis measurement cycles may be configured to match the total amount of time for testing the gaseous sample. In some implementations, the total time of all hysteresis measurement cycles may be configured to be equal to a predetermined time covering a time period of interest. In some embodiments, the total time of all hysteresis measurement cycles may be configured to be equal to or greater than the total amount of time of the non-steady state phase (or kinetic phase). In some embodiments, the controller circuit may be configured to determine the onset of the unsteady state response phase from each discrete combined detector by evaluating the rate of change of the measured capacitance over time, and initiate a hysteresis measurement cycle at that point. In some embodiments, the controller circuit may be configured to initiate a hysteresis measurement cycle upon receiving a signal indicative of a start of a particular test of the gaseous sample (e.g., receiving a signal from the flow sensor that sample gas begins to flow to the discrete binding detector). In some embodiments, the controller circuit may be configured to determine the end of the non-steady state phase by evaluating the rate of change of the measured capacitance over time and terminating the hysteresis measurement cycle at that point or reducing the frequency of the hysteresis measurement cycle at that point.

In various embodiments, the total time period for generating a series of hysteresis measurement cycles (total time for all hysteresis measurement cycles) may include from 10 seconds to 1200 seconds. In some embodiments, the period of time for generating a series of hysteresis measurement cycles may include from 30 seconds to 180 seconds. In some embodiments, the time period for generating the series of hysteresis measurement cycles may include 10, 15, 20, 25, 30, 40, 45, 60, 90, 120, 150, 180, 360, 540, 720, 1080, 1200 seconds or more. It will be appreciated that the time period for generating a series of hysteresis measurement cycles may comprise a range wherein any of the aforementioned points in time may serve as a lower or upper limit of the range, provided that the lower limit of the range is a value less than the upper limit of the range.

In some embodiments, stepping through the range of applied voltages may include stepping through the range of applied voltages in predetermined increments (e.g., 50mV increments). In some embodiments, stepping through the range of applied voltages may include stepping through the range of applied voltages in 10mV increments. The stepping through the range of applied voltages may be performed in voltage increments of 1mV, 5mV, 10mV, 25mV, 50mV, 75mV, 100mV, 125mV, 150mV, 200mV, 300mV, 400mV, or 500mV, or in step amounts falling within a range between any of the foregoing values. In various embodiments, stepping through the applied voltage range may include stepping through the applied voltage range in increments of 1mV to 500 mV. In various embodiments, stepping through the range of applied voltages may include stepping through the range of applied voltages in increments of 5mV to 300 mV.

Hysteresis effect and capacitance/voltage parameters

Based on the measured capacitance data, a number of different capacitance versus voltage related parameters can be calculated. Parameters of the resulting capacitance versus voltage curve may include, but are not limited to: capacitance at a particular voltage, maximum slope of capacitance versus voltage, minimum capacitance, voltage at minimum capacitance (dirac point), maximum capacitance, full width half maximum/half width of capacitance-voltage curve, area of capacitance-voltage curve, difference between maximum capacitance and minimum capacitance, forward dirac point voltage, reverse dirac point voltage, and ratio of maximum capacitance to minimum capacitance.

The change in any one of the parameters can be measured as a hysteresis effect due to analyte binding. For example, hysteresis effects may include changes in any of the following parameters: maximum slope of capacitance versus voltage, maximum slope of capacitance versus voltage versus baseline value, minimum slope of capacitance versus voltage versus baseline value, minimum capacitance versus baseline value, voltage at minimum capacitance (dirac voltage), voltage at minimum capacitance, maximum capacitance change, ratio of maximum capacitance to minimum capacitance, response time constant, and ratio of any of the foregoing between different graphene sensors (particularly ratio of any of the foregoing between different graphene sensors specific to different analytes).

Without wishing to be bound by any particular theory, it is believed that various mechanisms affect the relationship of capacitance to voltage (capacitance-voltage), depending on whether the molecules being bonded (bound) are weakly or tightly bonded. . In the case of weakly bound molecules, a transient reversible signal is observed in the measured data. Such reversible signals are believed to be due to the charge distribution of the bonding molecules that shift in response to an applied voltage during a voltage sweep. As the voltage sweeps, the charge distribution of the weakly bound molecules shifts with the fringe field, resulting in an increase in hysteresis in the system. In various embodiments, the reversible signal may be recovered during the voltage sweep by introducing a nitrogen sweep between the excitation signals.

In the case of tightly bound molecules, a slow accumulated drift signal is observed in the measured data. It is believed that the molecular orbitals of the molecules interact directly with the graphene and the dielectric layer to enable charge transfer with the graphene. During the voltage sweep, the drift signal may accumulate over time. As the voltage scans, a net flow of charge into or out of the graphene may occur. In various embodiments, the drift signal slowly returns to the baseline value.

The various analytes respond differently to the reversible signal and the drift signal, resulting in a hysteresis in the measured parameter. The response signal may also vary in response to the range of applied gate voltage sweeps, the duration of the gate voltage sweeps, and the applied temperature.

Method

Many different methods are contemplated herein, including but not limited to manufacturing methods, methods of use, and the like. Various aspects of the system/apparatus operations described elsewhere herein may be performed as operations according to one or more methods of various embodiments herein.

In one embodiment, a method for evaluating a fluid test sample is included, which may include contacting a chemical sensor element with the fluid test sample, which may include one or more discrete binding detectors, each of which may include a graphene varactor, asserting an applied voltage as part of a series of hysteresis measurement cycles over a period of time, wherein each hysteresis measurement cycle includes delivering the voltage to the discrete binding detector as a voltage sweep in a first direction and then in a second direction opposite the first direction, measuring capacitance from the hysteresis measurement cycle for each discrete binding detector, and determining a hysteresis effect related to a capacitance value measured over the period of time.

In one embodiment, the method may further comprise distinguishing the first unique fluid mixture from the second unique fluid mixture based on a hysteresis characteristic of each of the first unique fluid mixture and the second unique fluid mixture. It should be appreciated that the method may further include distinguishing a third unique fluid mixture, a fourth unique fluid mixture, a fifth unique fluid mixture, a sixth unique fluid mixture, a seventh unique fluid mixture, an eighth mixture unique fluid mixture, and so forth.

In one embodiment, the method may further include passing the applied voltage to the graphene varactor at a plurality of discrete voltages across (within) a voltage range, including stepping through the voltage range in 50mV increments.

In one embodiment of the method, the voltage range includes from-6V to 6V.

In one embodiment of the method, the voltage range includes from-3V to 3V.

In one embodiment of the method, the voltage range includes from-1.5V to 1.5V.

In one embodiment, the method may further comprise determining the identity of one or more analytes present in the fluid test sample.

In one embodiment, the method may further include identifying a disease state of the individual providing the fluid test sample based at least in part on the determined hysteresis effect on the measured capacitance value.

In various embodiments, the method may further comprise evaluating the fluid test sample at least in part by determining a hysteresis effect in one or more parameters of the one or more discrete binding detectors.

In various embodiments, the hysteresis effect on the one or more parameters may include one or more of the following: capacitance at a particular voltage, maximum slope of capacitance versus voltage, minimum capacitance, voltage at minimum capacitance (dirac voltage), ratio of maximum capacitance and maximum capacitance to minimum capacitance.

The aspects may be better understood with reference to the following examples. These examples are intended to represent particular embodiments, but are not intended to limit the overall scope of the embodiments herein.

Examples

Example 1: laboratory gas measurement system

An exemplary laboratory-based gas measurement system 1200 is shown in fig. 12. The gas measurement system 1200 includes nitrogen (N) ₂ ) Tank 1202 (99.9998% purity), the nitrogen tank 1202 is connected to two Mass Flow Controllers (MFCs) to form two independent gas flow channels. The first MFC 1204 is configured to transfer N via the first gas flow channel 1220 ₂ Enters bubbler 1206 and may generate water vapor or VOC-containing vapor depending on the bubbler contents. The second MFC 1208 is configured as a dilution channel to control the carrier N via the second gas flow channel 1222 ₂ Flow rate of gas. The third MFC 1210 is connected to an oxygen tank 1212 (industrial grade) and is configured to form a third gas flow passage 1224.

The first, second, and third gas flow channels converge in the mixing chamber 1226 to form a gas mixture containing the analyte at a point just prior to the gas mixture being fed into the gas flow chamber 1214. The gas flow chamber 1214 is configured to receive the chemical sensor element 200, the chemical sensor element 200 comprising a plurality of graphene varactors. The upstream side of the gas flow entering the gas flow cell 1214 is connected to a proportional-integral-derivative (PID) heater 1216 that controls the temperature of the gaseous sample. An inductive, capacitive, resistive meter 1218 (e.g., an Agilent 4284A LCR meter) is connected to the gas flow cell 1214 and is used to measure any number of capacitance versus gate voltage (C-Vg) curves used to monitor the behavior of one or more graphene varactors on the chemical sensor element.

Example 2: electric response of bare graphene varactors in the presence of ethanol and oxygen

Using the gas measurement system described in example 1, the electrical response of various graphene varactors was evaluated in the presence of ethanol and oxygen. Prior to the experiment, bare graphene varactors were grown in high vacuum (10 ^-6 Torr) at 120 ℃ for 12-18 hours to remove any possible adsorbates from the graphene surface. To eliminate the effect of residual air in the system, 400 standard cubic centimeters per minute (sccm) of N was used ₂ Flow the gas flow channels and flow cells of the gas measurement system were pre-purged for 10 minutes. The graphene varactors are scanned 80-120 times between-2V and 2V for stabilization before recording any data.

To observe the transient response of the graphene varactors and any possible memory effects due to exposure to various analytes, respectively, the chemical sensor elements were repeatedly exposed to 20 cycles of 10,000 parts per million (ppm) oxygen and 2105ppm of volatile ethanol (4% saturation, diluted in N ₂ ) In 40 cycles. Each complete hysteresis measurement cycle consists of: at N ₂ Background chemical sensor element is exposed to oxygen or ethanol for 400-600 seconds of a series of forward and reverse scans followed by a series of pure N ₂ Forward and reverse scans of the same length. The total flow rate was maintained at a constant level of 1000sccm under all conditions. In each gas exposure, ten C-V were measured from-2V to 2V in steps of 20mV _g A curve. All flow switching between forward scanning in the first direction and reverse scanning in the second direction occurs at V _g ＝-2V。

Referring now to fig. 13, a plot of analyte concentration as a function of time for gas delivered to the flow cell (oxygen top plot, ethanol bottom plot) is shown. During this time, the LCR meter measures the chemical sensor element capacitance, V _g Continuously scan from-2V to 2V and back to-2V. Forward C-V collected during a time frame marked by dashed box 1302 in FIG. 13 _g (see FIG. 14) kojiThe line indicates repeated O ₂ Exposure to V _DF Significantly shifted in the positive direction, while repeated ethanol exposure significantly shifted V _DF Shifted in the negative direction. For simplicity, only the 0 to 2V portion of the forward scan is depicted in fig. 14.

V for the whole experiment _DF 、V _DR And hysteresis values are extrapolated and plotted against time. Referring now to FIG. 15, extrapolated V over time is plotted _DF And V _DR Values. (V) _DF –1502；V _DR -1504). Referring now to fig. 16, extrapolated hysteresis values over time are plotted. Notably, both oxygen and ethanol produce two superimposed sets of signals: one set is a transient reversible signal that can be recovered by a subsequent nitrogen purge; and a set of drift signals that accumulate over each exposure cycle, but are much larger in amplitude. Oxygen induced drift causes V _DF And V _DR Both of which are displaced in the positive direction. The oxygen exposure gradually reduces the hysteresis of the chemical sensor element. Conversely, the drift caused by ethanol causes V _DR Shift negatively while increasing hysteresis.

Referring now to fig. 17, a detailed line graph of ethanol reversible signals acquired during a first time 1506 as shown in fig. 15 is shown. As shown in fig. 17, V _DF And V _DR Both move in the negative direction, but V _DF The amplitude of the shift of (2) is greater than V _DR The magnitude of the shift indicates that ethanol induces increased chemical sensor element hysteresis. Referring now to FIG. 18, a detailed line graph of oxygen reversibility signals acquired during a second time 1508 as shown in FIG. 15 is shown. As shown in fig. 18, for V _DF And V _DR The amplitude of the shift is almost the same and therefore indicates that the hysteresis signal in response to oxygen is small.

Example 3: electric response of bare graphene varactors in the presence of ethanol or water and oxygen

V described in example 2 was repeated using methanol or water as volatile organic compound instead of ethanol _DF And V _DR And (5) experiment. As described in example 2, prior to the experiment, the bare graphene varactor was grown under high vacuum (10 ^-6 Torr) is baked at 120 ℃ for 12-18 hours to remove any possible adsorbates from the graphene surface. To eliminate the effect of residual air in the system, 400 standard cubic centimeters per minute (sccm) of N was used ₂ Flow the gas flow channels and flow cells of the gas measurement system were pre-purged for 10 minutes. The chemical sensor is scanned 80-120 times between-2V and 2V for stabilization before any data is collected.

Referring now to fig. 19, a plot of analyte concentration as a function of time for gas delivered to the flow cell (oxygen top graph, water bottom graph) is shown. Repeated exposure of graphene varactors to O ₂ (10,000 ppm) and H ₂ O (1251 ppm,4% saturation) and circulated as shown in example 2. The line graph shown in fig. 20 shows the resulting extrapolated V of a bare graphene varactor exposed to oxygen and water _DF 2002、V _DR 2004 and hysteresis response 2006.

Referring now to FIG. 21, a plot of analyte concentrations of oxygen (upper plot) and methanol (lower plot) delivered to a flow cell as a function of time is shown. Repeated exposure of graphene varactors to O ₂ (10,000 ppm) and methanol (6684 ppm,4% saturation) and recycled as shown in example 2. The resulting extrapolated V of the bare graphene varactor exposed to oxygen and methanol is shown by the graph shown in fig. 22 _DF 2204、V _DR 2204 and hysteresis response 2206.

Both water and methanol produced the same trend in terms of drift and reversible signal as ethanol, as described in example 2. That is, the drift caused by methanol or water combination causes V _DR Negative shift and at the same time increase hysteresis.

Example 4: tetraphenylporphyrin manganese (III) chloride functionalized graphene varactors in the presence of ethanol and oxygen Electrical response of a tube

The electrical response of various graphene varactors functionalized with tetraphenylporphyrin manganese (III) chloride (Mn (III) TPPCl) was evaluated in the presence of ethanol and oxygen to monitor the functionalization vs V according to the same experimental parameters of example 2 _DF 、V _DR And hysteresis value.

Chemical sensor elements with graphene varactors functionalized with Mn (III) TPPCl are exposed to high vacuum (10 ^-6 Torr), baking at 120 ℃ for 12-18 hours to remove any possible adsorbates from the graphene surface. To eliminate the effect of residual air in the system, 400 standard cubic centimeters per minute (sccm) of N was used ₂ The flow pre-purges the gas flow channels and flow cells of the gas measurement system for 10 minutes.

Referring now to FIG. 23, a plot of oxygen (upper plot) and ethanol (lower plot) analyte concentrations delivered to a flow cell as a function of time is shown. Repeated exposure of graphene varactors functionalized with Mn (III) TPPCl to O ₂ (10,000 ppm) and ethanol (2105 ppm, N ₂ 4% saturation of the dilution) and recycled as shown in example 2. The graph shown in FIG. 24 shows the resulting extrapolation V of Mn (III) TPPCl functionalized graphene varactors exposed to oxygen and methanol _DF 2402、V _DR 2404 and hysteresis response 2406.

Graphene functionalized with Mn (III) TPPCl has the same general trend in ethanol binding as bare graphene, with only one difference. In particular, the magnitude of the drift signal on the functionalized samples is typically the same as that of bare graphene, but the reversible signal induced by ethanol shows a significant improvement compared to bare graphene.

Example 5: temperature dependent response of graphene varactors

The temperature-dependent response of various graphene varactors was measured to determine temperature versus V _DF 、V _DR And hysteresis. Bare graphene varactor diode under high vacuum (10 ^-6 Torr) is baked at 120 ℃ for 12-18 hours to remove any possible adsorbates from the graphene surface. The baked graphene varactor was continuously exposed to 10,000ppm oxygen for two cycles and then 1251ppm H ₂ O (4% relative humidity) three cycles. Each sensing cycle is followed by one N ₂ The cycle is resumed to observe the reversible signal. At a temperature of 20 ℃ to 80 DEG CSeveral temperature setpoints within the range repeat the above exposure sequence.

Referring now to fig. 25, the variation of analyte gas concentration and temperature over time is shown. The upper, middle and lower graphs show the temperature set point, O, respectively ₂ Concentration and H ₂ Relationship between O concentration and time. The increasing temperature ramp sequence (sequence) is followed by a decreasing temperature ramp sequence to help distinguish the trend in the chemical sensor element that is temperature dependent due to long term changes. All C-Vg curves were measured between-2V and 2V, and the total flow rate was maintained at 1000sccm.

FIG. 26 shows V extracted from the measurements _DF (solid line) and V _DR (dashed line) value. Continuous exposure of graphene varactors to O ₂ And H ₂ O causes V _DF And V _DR Drift as indicated by arrow 2602. Fig. 28 depicts the change in the hysteresis degree with time, in which an increasing trend is observed with an increase in temperature. Without being bound by any particular theory, it is believed that as the temperature increases, each condition favors the charging or discharging of the oxide well within the metal-oxide dielectric layer, thereby contributing to hysteresis. This trend provides evidence that the device temperature is at the first O ₂ The set point is reached and then remains stable as the cycle of exposure.

FIG. 27 shows V after background subtraction _DF And V _DR Any deviation of the two curves from zero represents a reversible signal, as indicated by reference numeral 2702. After subtracting the background V _DR The graph of (C) shows that as the temperature increases, O ₂ The reversible response increases. However, by V after subtracting the background _DF Measured H ₂ The O reversible signal decreases significantly, accompanied by a sustained decrease in hysteresis. At each temperature stage, a first O ₂ Or H ₂ The O exposure cycle produces an abnormally large signal due to artifacts caused by imperfect background fit. The dependence of methanol, ethanol and Methyl Ethyl Ketone (MEK) signals on temperature was also analyzed using the same experimental setup (data not shown), and it is shown at V _DF And V _DR Value aspect and H ₂ O-like trends because they show hysteresis andV _DR is reduced.

From the data of fig. 27, the energy terms of the various gas interactions are extracted according to the following equation:

wherein S is _{Physical properties} And S is _{Chemical chemistry} The magnitude of the physisorption and chemisorption induced signals, respectively. E (E) _d And E is _a The desorption energy of physisorption and the activation energy of chemisorption, respectively, and k _B Is the boltzmann constant.

For reversible O ₂ And H ₂ O signal for all V for the last sense cycle at each temperature _DR The data points are summed. From H ₂ The O-induced drift signal is determined by comparing V at the beginning and end of three consecutive exposures _DR Values, the magnitudes of which are indicated by arrows 2602 in fig. 26. All signal amplitudes are plotted against 1/T (where T is temperature) on a logarithmic scale, as shown in fig. 29. The reversible signal is calculated by averaging the last three data points last exposed in fig. 27, as indicated by arrow 2702. The solid line represents the fit result and the slope from the linear fit can be converted to an energy term as shown in equation 1. The negative sign of the fitted energy term indicates that the signal is from a chemisorbed-like interaction. The positive sign of the fitted energy term indicates that the signal is from a physisorbed-like interaction. As summarized in fig. 30, from VOC and H ₂ The extrapolated activation energy of the O-drift signal is negative. For reversible signals, H ₂ The O interaction has a positive energy term (desorption energy) and the results for ethanol, methanol and methyl ethyl ketone are close to zero, resulting in larger errors due to long-term reduction of hysteresis.

Comparison H ₂ O, methanol and ethanol (which all contain hydroxyl groups), the resulting desorption energy decreases with increasing molecular size. The only exception is O ₂ A reversible signal having a negative energy term. The difference in sign of the activation energy associated with the reversible signal indicates O ₂ Interactions are similar to chemisorption, while VOCsAnd H ₂ The interaction of O with graphene is similar to physical adsorption.

Example 6: voltage dependent response of graphene varactors

In the presence of oxygen and water, V was studied _g The effect of both drift in the system and reversible signal of the function of the scan range. As shown in fig. 31 (middle and lower panels), the device is sequentially exposed to O ₂ And H ₂ O, the purge was resumed with nitrogen to separate the two sets of signals. At different V _g The range is scanned (upper plot in fig. 31), and the flow sequence is repeated. V (V) _g The scanning window is always centered at 0V, and the step size is adjusted to maintain a constant exposure time in each cycle, thereby minimizing measurement-induced drift. The total flow rate was maintained at a constant value of 1000 sccm.

FIG. 32 shows the resulting V _DF And V _DR Data. Notably, V _DF 3202 and V _DR 3204 measured drift signal and O ₂ The reversible signal increases with the expansion of the scanning range. However, for H ₂ O reversible response, enlarging the Vg scan range results in V _DF Signal increases, but V _DR The signal drops. Fig. 33 tracks the change in hysteresis. Hysteresis along with V _g The scan range increases due to the increase in hysteresis, which may be caused by the charge and discharge of the oxide well in the dielectric layer.

Fig. 34 and 35 show H from fig. 32, respectively ₂ Calculated reversible and drift signal intensities obtained from the O exposure data, which indicate V for reversible response _DF And V _DR The signal has a pair V _g Opposite dependence of scan range, but for drift response V _DF And V _DR Both signals are enhanced. The results show that the VOC and H ₂ The reversible and drift signal caused by O has a value of V _g Different dependencies of the scan range. In some cases, when V _g V of reversible response when the sweep amplitude is sufficiently large _DR The signal changes its sign.

For O ₂ For the reversible signal (FIG. 32), at V _DF And V _DR In both, an increase in amplitude was observed, indicating a chemisorption mechanism. Thus, O ₂ Drift is related to cumulative response caused by multiple exposures, but may be interrupted by nitrogen purges. Analysis was repeated using ethanol, methanol and methyl ethyl ketone (data not shown), with similar trends observed. In the presence of pyr-CH ₂ Similar trends were also observed on OH functionalized graphite-like sensors, as well as on samples after vacuum baking (data not shown). The results show that the VOC and H ₂ The reversible and drift signal caused by O has a value of V _g Different dependencies of the scan range.

Analysis shows that for a small Vg scan range, the charge modulation in graphene is small, and therefore the centroid shift of the molecular charge is also small. For a large Vg scan range, the charge modulation in graphene is large, resulting in a larger redistribution of molecular charges.

Example 7: concentration-dependent response of graphene varactors

Study of H ₂ Influence of O concentration. Exposing bare graphene varactors to having different H' s ₂ H of O concentration ₂ O/N ₂ And (3) a mixture. V from-2V to 2V _g The scan range is applied to the bare graphene varactor. FIG. 36 shows H in a chamber as a function of time ₂ O varies while the total flow rate remains constant at 1000 sccm. The data shows that the device produces a greater V when exposed to higher concentrations of analyte _DF And V _DR A signal. Calculating the hysteresis, V, from each exposure by averaging the last three data points after subtracting the background _DF And V _DR Measured signal amplitude (fig. 37). Sensitivity in mV/ppm was then extrapolated by linear fitting, as shown in solid line. By different V _g Scan range (including 3V, 4V, 5V, 6V, 5V, 4V, and 3V), repeat the measurement. Shown in FIG. 38 as V _g The resulting sensitivity of the function of the scan range. The calculation result shows that V _DF And absolute amplitude of hysteresis sensitivity increases with increasing scan range, while V _DR Sensitivity is in the whole rangeThe sign is changed.

Example 8: gas characterization using hysteresis and forward dirac points

The utility of hysteresis effects in characterizing fluid samples was also investigated. Four arrays of 120 discrete graphene varactors with 37 different surface chemistries were first grown in high vacuum (10 ^-6 Torr) is baked at 100 ℃ for 12-18 hours to remove any possible adsorbates from the graphene surface. To eliminate the effect of residual air in the system, 400 standard cubic centimeters per minute (sccm) of N was used ₂ Flow the gas flow channels and flow cells of the gas measurement system were pre-purged for 3 minutes.

The array is first exposed to 1000sccm N ₂ Flow for 30 seconds, simultaneously measuring several forward and reverse C-V _g A curve. A scan range of-1.5V to 1.5V was used, with a step size of 50mV. The array was then exposed to the gas sample for 40 seconds while measuring more of several forward and reverse C-V' s _g A curve. The gas sample tested was 2-butanone (at N ₂ 1026, 10,263, 51,316 and 102,631ppm) hexanal (in N ₂ 148, 1482, 7408 and 14,815 ppm), ethanol (under N) ₂ 587, 5872, 29,361 and 58,722 ppm) and N in the background ₂ . C-V in response to different gases was observed _g Change of curve, and extract V _DF And a hysteresis signal.

Principal Component Analysis (PCA) is used to reduce the dimensions to determine if signals from different gas samples are unique. From V _DF And delayed signals are analyzed separately and in combination. FIG. 39 is when only V is included in the feature set _DF A comparison of the main component 1 (PC 1) with respect to the main component 2 (PC 2) at the time of signal. Each point represents V from all 120 discrete varactors in the sensor array _DF A signal. Four arrays were tested for each gas concentration. The concentration of some hexanal and ethanol can be clearly distinguished, but most of the gas samples overlap significantly, reducing the accuracy of gas classification.

Fig. 40 is a comparison diagram of PC1 with respect to PC2 when only a hysteresis signal is included in the feature set. Each dot represents the hysteresis signal from all 120 discrete varactors in the sensor array. Four arrays were tested for each gas concentration. Some hexanal concentrations can be clearly distinguished, but most of the gas samples overlap significantly, reducing the accuracy of gas classification.

FIG. 41 is when only V is included in the feature set _DF And a comparison of PC1 versus PC2 for both hysteresis signals. Each point represents V from all 120 discrete varactors in the sensor array _DF And a hysteresis signal. Four arrays were tested for each gas concentration. Since no overlap was observed between any of the gas samples, the gas classification was significantly improved. These data provide a way to combine hysteresis effects with V _DF Evidence of improved gas classification is used in combination.

It should be noted that, as used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the content clearly dictates otherwise. Thus, for example, reference to a composition containing "a compound" or "a compound" includes a mixture of two or more compounds. It should also be noted that the term "or" is generally employed in its sense including "and/or" unless the content clearly dictates otherwise.

It should also be noted that, as used in this specification and the appended claims, the phrase "configured" describes a system, apparatus, or other structure constructed or arranged to perform a particular task or to employ a particular configuration. The phrase "configured" may be used interchangeably with other similar phrases such as arrangement and configuration, construction and arrangement, construction, manufacture and arrangement, and the like.

All publications and patent applications in this specification are indicative of the level of skill of those skilled in the art to which this invention pertains. All publications and patent applications are herein incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference.

As used herein, a numerical range recited by an endpoint shall include all values subsumed within that range (e.g., 2 to 8 includes 2.1, 2.8, 5.3, 7, etc.).

The title is used herein to keep pace with the recommendation at 37cfr 1.77 or otherwise provide organizational cues. These headings should not be construed as limiting or characterizing the invention as set forth in any claims that may be presented in this disclosure. For example, although the headings refer to "technical fields," such claims should not be limited by the language chosen under the headings to describe the so-called technical fields. Furthermore, the description of a technology in the "background" does not constitute an admission that the technology is prior art to any invention in this disclosure. Neither should the "summary of the invention" be considered a characterization of the invention as set forth in the issued claims.

The embodiments described herein are not intended to be exhaustive or to limit the invention to the precise forms disclosed in the following embodiments. Rather, the embodiments are chosen and described so that others skilled in the art may appreciate and understand the principles and practices. Aspects have been described, by themselves, with reference to various specific and preferred embodiments and techniques. However, it should be understood that many variations and modifications may be made while remaining within the spirit and scope of the disclosure.

Claims (15)

1. A system for analyzing a fluid sample, comprising:

a controller circuit;

a chemical sensor element comprising one or more discrete binding detectors comprising one or more graphene varactors; and

a measurement circuit arrangement, the measurement circuit arrangement comprising:

a voltage generator, wherein the voltage generator is configured to generate an applied voltage at a plurality of voltage values to be applied to the one or more graphene varactors, the voltage values falling within a range from a lower limit to an upper limit; and

a measurement circuit comprising a capacitive sensor, wherein the capacitive sensor is configured to measure a capacitance of the discrete binding detector caused by an applied voltage,

wherein the system for analyzing a fluid sample is configured to measure a hysteresis effect related to capacitance-voltage values obtained by the one or more graphene varactors.

2. The system of any of claims 1 and 3-9, wherein the applied voltage comprises a voltage value starting from one of a lower limit or an upper limit and moving to the other limit as part of a scan of different voltage values ranging from the lower limit to the upper limit; and is also provided with

Wherein the hysteresis effect reflects a difference in measurable values related to capacitance of the graphene varactors, the difference resulting from a comparison of a scan in a first direction between the lower and upper limits to a scan in a second direction between the lower and upper limits, wherein the second direction is opposite the first direction.

3. The system of any of claims 1-2 and 4-9, wherein scanning in the first direction is followed by a pause, followed by scanning in the second direction.

4. The system of any of claims 1-3 and 5-9, wherein scanning in the second direction after scanning in the first direction constitutes a hysteresis measurement cycle in which an upper voltage limit and a lower voltage limit are varied between successive cycles.

5. The system of any one of claims 1-4 and 6-9, wherein the system is configured to utilize the determined hysteresis effect as a data input in a pattern matching operation, wherein a result of the pattern matching operation characterizes the fluid test sample and/or a patient providing the fluid test sample.

6. The system of any one of claims 1-5 and 7-9, wherein the system is configured to calculate a first dirac voltage for a scan of the discrete combination detector in the first direction and a second dirac voltage for a subsequent scan of the discrete combination detector in the second direction.

7. The system of any of claims 1-6 and 8-9, wherein the controller circuit is configured to calculate an average hysteresis change value of the property measured over a plurality of hysteresis measurement cycles.

8. The system of any one of claims 1-7 and 9, wherein the system is configured to determine the identity of one or more analytes present in the gaseous sample by assessing a hysteresis effect of one or more properties of the one or more discrete binding detectors.

9. The system of any one of claims 1-8, wherein the system is configured to measure the presence of an analyte in a fluid sample by assessing a hysteresis change in one or more parameters of capacitance-voltage data.

10. A method for evaluating a fluid sample, comprising:

contacting a chemical sensor element comprising one or more discrete binding detectors with the fluid sample, wherein each discrete binding detector comprises a graphene varactor;

applying a voltage to the graphene varactor as part of a series of hysteresis measurement cycles over a period of time, wherein each hysteresis measurement cycle includes applying a voltage to the graphene varactor as part of a sweep in a first direction and then in a second direction, the second direction being opposite the first direction, over a range of voltages;

Measuring the capacitance of each discrete binding detector caused by the applied voltage; and

determining a hysteresis effect associated with the measured capacitance value over the period of time.

11. The method of any one of claims 10 and 12-15, further comprising distinguishing a first unique fluid mixture from a second unique fluid mixture based on a measured hysteresis effect exhibited by each of the first unique fluid mixture and the second unique fluid mixture.

12. The method of any one of claims 10-11 and 13-15, further comprising characterizing the fluid sample based at least in part on a hysteresis effect of the determined one or more parameters.

13. The method of claims 10-12 and 14-15, further comprising identifying a disease state of the individual by matching data collected from the analysis fluid sample to a predetermined data pattern corresponding to the disease state, the collected data comprising data regarding hysteresis effects.

14. The method of claims 10-14 and 15, further comprising

Determining one or more parameters of capacitance-voltage data for each discrete combined detector resulting from the applied voltage, and;

Classifying discrete analytes within the fluid sample based on the determined hysteresis effect and the combination of the one or more parameters of the capacitance-voltage data.

15. The method of claims 10-14, wherein determining one or more parameters of the capacitance-voltage data comprises determining a forward dirac point voltage for each discrete combined detector caused by the applied voltage.