CN101393015A - On-line measurement method and device for micro/nano deep trench structure - Google Patents
On-line measurement method and device for micro/nano deep trench structure Download PDFInfo
- Publication number
- CN101393015A CN101393015A CNA2008101972791A CN200810197279A CN101393015A CN 101393015 A CN101393015 A CN 101393015A CN A2008101972791 A CNA2008101972791 A CN A2008101972791A CN 200810197279 A CN200810197279 A CN 200810197279A CN 101393015 A CN101393015 A CN 101393015A
- Authority
- CN
- China
- Prior art keywords
- mrow
- msub
- mtd
- msubsup
- groove
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000691 measurement method Methods 0.000 title description 6
- 238000001228 spectrum Methods 0.000 claims abstract description 57
- 238000000034 method Methods 0.000 claims abstract description 44
- 230000003287 optical effect Effects 0.000 claims abstract description 30
- 238000005259 measurement Methods 0.000 claims abstract description 28
- 230000010287 polarization Effects 0.000 claims abstract description 21
- 238000013528 artificial neural network Methods 0.000 claims abstract description 8
- 238000001914 filtration Methods 0.000 claims abstract description 8
- 238000010845 search algorithm Methods 0.000 claims abstract description 4
- 239000000523 sample Substances 0.000 claims description 24
- 239000011159 matrix material Substances 0.000 claims description 17
- 239000010409 thin film Substances 0.000 claims description 14
- 238000012549 training Methods 0.000 claims description 12
- 239000010408 film Substances 0.000 claims description 11
- 239000000463 material Substances 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 7
- 239000000758 substrate Substances 0.000 claims description 6
- 238000011049 filling Methods 0.000 claims description 5
- 238000013461 design Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 2
- 238000007781 pre-processing Methods 0.000 claims description 2
- 230000003595 spectral effect Effects 0.000 claims description 2
- 238000000605 extraction Methods 0.000 abstract description 7
- 238000004519 manufacturing process Methods 0.000 abstract description 2
- 230000005669 field effect Effects 0.000 abstract 1
- 238000005530 etching Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 4
- 229910052710 silicon Inorganic materials 0.000 description 4
- 239000010703 silicon Substances 0.000 description 4
- 239000002131 composite material Substances 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 238000003491 array Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 230000001066 destructive effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 229910021420 polycrystalline silicon Inorganic materials 0.000 description 2
- 229920005591 polysilicon Polymers 0.000 description 2
- 238000001055 reflectance spectroscopy Methods 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 238000002922 simulated annealing Methods 0.000 description 2
- 230000003321 amplification Effects 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 239000003990 capacitor Substances 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000012938 design process Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 238000011065 in-situ storage Methods 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 239000012212 insulator Substances 0.000 description 1
- 238000004377 microelectronic Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 239000002086 nanomaterial Substances 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 239000012788 optical film Substances 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 229920002120 photoresistant polymer Polymers 0.000 description 1
- 238000004886 process control Methods 0.000 description 1
- 238000004611 spectroscopical analysis Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention discloses an online measuring method and an online measuring device for a micro-nano deep groove structure. The method comprises the following steps: linearly polarized infrared beams are projected to the surface of a sample piece which is provided with the deep groove structure, and measured reflection spectra are obtained after interference signals which are formed by reflected light on various interfaces of the groove structure are subjected to filtration and so on; an equivalent optical model of the deep groove structure is established by the polarization-based equivalent medium theory, and theoretic reflection spectra of the equivalent optical model of the deep groove structure are calculated; and the width and the depth of the groove are quickly extracted by the quick parameter extraction method of combination of an artificial neural network and a local search algorithm and through fitting of the theoretic reflection spectra and the measured reflection spectra, and precise online measurement of geometrical shape parameters of the deep groove is realized. The device comprises an infrared source, an infrared polaroid sheet, an interferometer, a plane mirror, two off-axis parabolic mirrors and an infrared detector. The device can realize online measurement of the depth and the width of the deep groove structure with high depth-width ratio in a field effect tube and a dynamic RAM during the manufacturing procedure, and has the characteristics of nondestructiveness, quickness and low cost.
Description
Technical Field
The invention belongs to the measurement technology of Integrated Circuits (ICs) and Micro Electro Mechanical Systems (MEMS) devices, and particularly relates to an online measurement method and device for a micro-nano deep trench structure.
Background
In the design and manufacturing process of microelectronic and power semiconductor devices, dense three-dimensional structure arrays are widely adopted at present, for example, one or more layers of thin film structures are deposited on a silicon wafer substrate, a line groove array, a round hole or other groove arrays are etched on the substrate, then the groove structure is backfilled with a filling material, and the etching and filling steps are repeated to form a complex groove array structure. In the processing process of the groove array structures, the three-dimensional appearance, particularly the online and nondestructive measurement control of the geometrical feature dimensions such as the depth and the width of the groove, is particularly important. Among the numerous non-destructive measurement methods, optical measurement methods are particularly suitable for the application requirements, such as reflection spectroscopy, scattering spectroscopy, etc., which have been widely used for optical film thickness and composition measurements, and have been applied to grating trench structure measurements in some patents and literature.
The applicant proposes a micro-nano deep groove structure measuring method and device based on infrared reflection spectrum (with the publication number of CN101131317A) in 09/20 of 2007, the method projects infrared beams to the surface of a silicon wafer containing a deep groove structure, and analyzes interference light formed by reflection of each interface of the deep groove structure to obtain a measured reflection spectrum; the method comprises the steps of constructing a theoretical reflection spectrum of an equivalent multilayer thin film stack optical model of the deep groove structure by adopting an equivalent medium theory, fitting the measured reflection spectrum by utilizing a simulated annealing algorithm and a gradient-based optimization algorithm through the theoretical reflection spectrum, further extracting geometric characteristic parameters such as depth, width and the like of the groove, and realizing accurate measurement of dimensions such as width, depth and the like of the deep groove with the high depth-to-width ratio. The method can simultaneously measure the depth, the width and the film thickness of the groove. The realization device provided by the method focuses the incident light beam and projects the incident light beam on the surface of the object to be measured, and the slit diaphragm is arranged on the emergent light path to eliminate the influence of stray light on the back of the sample piece to be measured, so that the accurate reflection spectrum of the groove is measured and obtained.
The measurement method mentioned in the above patent document is based on the reflection spectrum of composite light, and the groove geometric modeling of the method is based on the equivalent medium theory of non-polarized light incidence. For different polarization directions, the equivalent precision of each polarization direction has larger difference, so the incident error of the composite light is larger than that of the polarized light. In the invention disclosed above, the parameter extraction adopts a method combining a simulated annealing algorithm and a gradient-based optimization algorithm, the method has less dependence on an initial value than the traditional method, and the parameters to be measured of the trench can be extracted and obtained under the condition of unknown measurement initial values. However, the parameter extraction method cannot meet the requirement of rapid extraction within seconds of online measurement. The implementation device provided by the method adopts a precise and complex light path structural design, ensures that the measured reflection spectrum is accurate, eliminates the influence of back stray light on a measurement structure, and simultaneously brings great difficulty to precise installation, debugging and calibration of the device due to the complex structural design.
Disclosure of Invention
The invention aims to provide an on-line measuring method of a micro-nano deep groove structure, which can accurately monitor the geometric shapes of the depth, the width and the like of a groove on line in an etching process, has the characteristics of non-contact, non-destructive, high speed and high precision, and also provides a device for realizing the method, which is simpler and more convenient and has lower cost.
The invention discloses an online measuring method of a micro-nano deep groove structure, which comprises the following steps:
2, after the incident light beam is reflected by each surface of the micro-nano deep groove structure, receiving each reflection signal by using an infrared detector to obtain an interference signal containing the geometric information of the groove;
step3, carrying out Fourier transform on the interference signal obtained in the step2 to obtain an infrared reflection spectrum based on wave number;
step4, low-pass filtering is carried out on the infrared reflection spectrum obtained in the step3, and a stray light spectrum on the back of the object to be measured is filtered out, so that a measurement reflection spectrum reflecting the structural characteristics of the groove is obtained;
5, establishing an equivalent multilayer thin film stack optical model according to the characteristics of the deep groove structure to be detected, calculating the reflection coefficient r of the equivalent thin film stack under each wavelength by using a formula (I), and obtaining the theoretical reflection spectrum of the groove structure by using the reflection coefficient r;
wherein, <math> <mrow> <mrow> <mfenced open='(' close=')'> <mtable> <mtr> <mtd> <msub> <mi>M</mi> <mn>11</mn> </msub> </mtd> <mtd> <msub> <mi>M</mi> <mn>12</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>M</mi> <mn>21</mn> </msub> </mtd> <mtd> <msub> <mi>M</mi> <mn>22</mn> </msub> </mtd> </mtr> </mtable> </mfenced> </mrow> <mo>=</mo> <msubsup> <mi>D</mi> <mn>0</mn> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mrow> <mo>[</mo> <munderover> <mi>Π</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msub> <mi>D</mi> <mi>l</mi> </msub> <msub> <mi>P</mi> <mi>l</mi> </msub> <msubsup> <mi>D</mi> <mi>l</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>]</mo> </mrow> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mi>II</mi> <mo>)</mo> </mrow> </mrow></math>
wherein in formula (II), M11、M12、M21、M22For intermediate variables of the multilayer optical propagation matrix, D0Is the optical characteristic matrix of the environment, DsIs a matrix of optical features of the substrate, PlIs a matrix function of the phase change angle of the l-th layer, DlIs a matrix function of the refractive index and angle of refraction of the first layer of the film stack, where DlCalculated according to formula (III) or (IV):
for the TE polarization direction:
for the TM polarization direction:
wherein, thetalAngle of refraction of the l layer, nTE2And nTM2The calculation formula is respectively formula (V) and formula (VI) for the equivalent refractive index of TE polarization and TM polarization direction of each equivalent layer:
wherein n isTE0And nTM0The zero order equivalent refractive indices for the TE and TM polarization directions, respectively, i.e. the zero order diffraction in scatterometry; λ is the probe beam wavelength, p is the trench array period length, f is the layer duty cycle, ngAnd nmRespectively, the refractive index of the trench material and the refractive index of the filling material therein;
and 6, fitting the theoretical reflection spectrum obtained in the step 5 with the measured reflection spectrum obtained in the step4, and extracting to obtain geometric morphology parameters of the micro-nano deep groove structure.
The device for realizing the method is characterized in that: the infrared light source, the infrared polaroid, the interferometer, the plane reflector and the first off-axis parabolic mirror are sequentially positioned on the same light path, the sample table is positioned on the reflected light path of the first off-axis parabolic mirror, and the reflected light of the first off-axis parabolic mirror forms an angle of 45 degrees with the surface of the sample table; the second off-axis parabolic mirror and the first off-axis parabolic mirror are symmetrically arranged relative to the incident point of the sample on the sample table, the infrared detector is positioned on a reflected light path of the second off-axis parabolic mirror, and the computer is connected with the infrared detector; and the computer receives the interference signal output by the infrared detector after preprocessing, performs Fourier transform processing to obtain the reflection spectrum of the groove structure, processes the interference signal according to the processes from the step4 to the step 6, and extracts the required geometric parameter value of the groove.
Compared with the existing measuring method, the method provided by the invention can realize the on-line, rapid and high-precision measurement of the micro-nano deep groove structure, and has wide application prospect in the fields of semiconductor measurement and process control. Specifically, the invention can obtain the following effects in the deep trench capacitor structure measurement of the DRAM:
(1) the online measurement of typical deep trench structures such as a DRAM conventional deep trench, an inclined sidewall deep trench, a bottle-shaped deep trench and a polysilicon filling trench is realized;
(2) the method realizes in-situ detection of DRAM deep trench defects, real-time monitoring of high-aspect-ratio micro-nano structure etching, online detection of bottle-shaped trench polysilicon refilling trench, rapid evaluation of full-field silicon wafer CD uniformity, and characterization of photoresist and dielectric films. Feedback of film epitaxial growth process, control of oxygen injection dosage in silicon on insulator processing and the like.
Drawings
FIG. 1 is a schematic diagram of a polarized red reflectance spectroscopy measurement optical path;
FIG. 2 is a schematic diagram of a slanted-wall deep trench structure and incident beam reflection;
FIG. 3 is a schematic diagram of an equivalent optical model of a deep trench structure with tilted walls and the reflection of an incident light beam;
FIG. 4 is a flow chart of fast automatic extraction of trench parameters;
FIG. 5 is a schematic diagram of a BP artificial neural network;
FIG. 6 is a diagram of an apparatus system according to an embodiment of the present invention.
Detailed Description
The principle and operation of the method of the present invention will be further described in detail below by taking the measurement process of the inclined-wall deep trench structure as an example and combining the drawings:
(1) projecting an infrared beam to the surface of an object to be detected containing a deep groove structure, wherein the wavelength of the infrared beam is within a mid-infrared wavelength range and is 2-20 um;
(2) after the incident beam is reflected by each surface of the groove structure, an infrared detector is adopted to receive each reflected signal, and an interference signal containing the geometric information of the groove is obtained;
as shown in fig. 1, an infrared beam emitted by an infrared light source 1 is polarized by an infrared polarizing film 2 to obtain linearly polarized light, the linearly polarized light enters an interferometer 3, is modulated by the interferometer 3, is converged after being reflected by a reflector, and is projected onto the surface of an object 4 to be measured, which comprises a groove structure, and reflected signals of all surfaces of the groove structure are reflected by the reflector 4 and then enter an infrared detector 6 in parallel.
As shown in fig. 2, the inclined-wall deep trench structure includes, from top to bottom, a mask layer 41, a trench layer 42, and a base layer 43. When the incident beam 11 is projected onto the surface of the trench structure, the incident beam is reflected on the surface of the mask layer, the interface between the mask layer and the trench layer, and the bottom of the trench, and the reflected beams 12, 13, 14 on the surfaces interfere with each other on the infrared detector, so as to obtain an interference signal containing the geometric information of the trench.
(3) Carrying out Fourier transformation on interference signals obtained by measurement of a detector to obtain an infrared reflection spectrum based on wave number;
(4) performing low-pass filtering on the reflection spectrum obtained in the step (3), and filtering out a stray light spectrum on the back of the object to be measured to obtain a measurement reflection spectrum reflecting the structural characteristics of the groove;
the reflection spectrum contains frequency components corresponding to the depths of all layers of the groove structure, wherein the back stray light is represented as a high-frequency signal, so that the influence of the back stray light can be eliminated through low-pass filtering. Compared with the traditional mode of eliminating the stray light on the back by hardware through a spatial filter, the filtering mode is simpler and has better impurity elimination effect.
(5) Establishing an equivalent multilayer film stack optical model according to the characteristics of the deep groove structure to be detected, and approximately describing the optical parameters and the infrared reflection characteristic of the groove structure;
the deep groove array to be measured can be regarded as a sub-wavelength grating structure, and the grating period length is far smaller than the wavelength of detection light waves, so that the deep groove array to be measured can be approximately equivalent to a multilayer uniform thin film stack model. The specific modeling process of the equivalent multilayer thin film stack optical model can refer to the method disclosed in CN 101131317A.
As shown in FIG. 3, the multilayer thin film structure is an equivalent multilayer thin film stack model of the inclined-wall deep trench structure in FIG. 2, and sequentially comprises a mask equivalent layer 511, a trench equivalent layer 521 and a substrate equivalent layer 531 from top to bottom, and the equivalent refractive indexes n of the equivalent layers in the TE polarization direction and the TM polarization direction are respectively calculated according to the formulas (1) and (2)TE2And nTM2。
Wherein n isTE0And nTM0The zero order equivalent refractive indices for the TE and TM polarization directions, respectively, i.e. the zero order diffraction in scatterometry. λ is the probe beam wavelength, p is the trench array period length, f is the layer duty cycle, ngAnd nmRespectively, the refractive index of the trench material and the material filled therein. Compared with the traditional equivalent modeling method based on the composite light, the equivalent modeling method based on the polarization has higher precision.
And calculating the polarization reflection spectrum of the equivalent optical model of the groove structure by using the multilayer film optical transmission theory. The reflection coefficient of the multilayer thin film stack can be calculated using an optical propagation matrix method. The optical propagation matrix of the multilayer thin film stack is shown in equation (3):
for the TE polarization direction:
for the TM polarization direction:
from this, the reflection coefficient of the thin film stack can be obtained
Wherein M is11、M12、M21、M22Intermediate variables of the multilayer optical propagation matrix, D0Is the optical characteristic matrix of the environment, DsIs a matrix of optical features of the substrate, DlIs a matrix function of the refractive index and angle of refraction, P, of the first layer of the film stacklIs a matrix function of the phase change angle of the l-th layer, thetalIs the l-th layer angle of refraction. The theoretical reflection spectrum of the trench structure can be obtained from the calculated reflection coefficients of the equivalent thin film stack at each wavelength.
(6) And (3) fitting the measured reflection spectrum obtained in the step (4) with a theoretical reflection spectrum obtained by the polarization-based equivalent optical model theoretical calculation of the groove structure, and further quickly extracting to obtain geometric shape parameters such as the depth and the width of the groove.
The monitoring of the groove etching process needs real-time geometric parameter measurement, and the inversion solving speed of the groove parameters is of great importance. The invention provides a rapid parameter extraction method based on an artificial neural network combined with a Levenberg-Marquardt local search algorithm, so as to realize real-time accurate measurement of groove parameters. The trench parameter extraction step is described in detail below with reference to fig. 4:
step 1: establishing a multilayer Artificial Neural Network (ANN) according to the reflection spectrum characteristics of the groove and the quantity of the parameters to be measured;
as shown in fig. 5, a three-layer feed-forward network (BP network) is created, comprising an input layer 71, a hidden layer 72 and an output layer 73. According to the reflection spectrum characteristics of the groove structure to be measured and the number of parameters to be measured, the number of nodes of the input layer 71 and the number of nodes of the output layer 73 are respectively determined, and then the number of nodes of the hidden layer 72 is determined according to an empirical formula and the number of nodes of the input layer and the output layer. The number of nodes of the input layer has great influence on the training time and precision of the BP network, and the input spectrum sequence can be determined by taking equal wavelength as the step length of the input spectrum sequence according to the reflection spectrum characteristic of the multilayer groove structure;
step 2: creating a BP network training sample set according to the groove structure theoretical modeling method in the step (5);
and selecting a multilayer film stack as an equivalent optical model according to the structural characteristics of the groove to be detected. And respectively determining the range of the groove depth and the range of the groove width of each layer of the groove structure according to the design and the processing process of the groove structure, thereby determining the range of the training sample set. According to the multilayer film optical transmission theory, calculating the reflection spectrum of the equivalent optical model under each groove and groove width to obtain a BP network training sample set (O)i，Ii) Wherein O isiIs the reflection spectral vector, IiThe geometric parameter vector to be measured of the groove comprises geometric parameters such as the depth and the width of the groove, wherein i is 1.
Step 3: training the BP network by using a training sample set created at Step2, wherein the training input is a reflection spectrum vector OiThe output is a geometric parameter vector I to be measured of the groovei；
In order to improve the output stability of the BP network, a certain amount of noise is randomly added into the reflection spectrum vector, the reflection spectrum containing the noise is used as input, the corresponding groove geometric parameter vector to be measured is used as output, and the BP network is trained.
Step 4: inputting the measurement spectrum filtered in the Step (4) into a neural network trained by Step3, and outputting a groove measurement initial value containing a certain error;
step 5: the output of Step4 is used as an initial value of a local iterative search algorithm, the theoretical reflection spectrum calculated in the Step (5) is used for fitting the measurement spectrum filtered in the Step (4), and then the high-precision groove geometric parameter value is extracted;
the BP network output is used as the initial value of the Levenberg-Marquardt local iterative algorithm, the preset iterative precision can be achieved within milliseconds, the difficulty that the initial value of the iteration needs to be selected in advance in the traditional fitting iterative algorithm is solved, and the rapid convergence of the iterative algorithm is ensured.
As shown in FIG. 6, the device of the invention comprises an infrared light source 1, an infrared polarizer 2, an interferometer 3, a plane reflector 41, first and second off-axis parabolic mirrors 42 and 43, a sample stage 91, an infrared detector 6 and a computer 8.
The infrared light source 1, the infrared polaroid 2, the interferometer 3, the plane reflector 41 and the first off-axis parabolic mirror 42 are sequentially located on the same light path, the sample stage 91 is located on the reflection light path of the first off-axis parabolic mirror 42, and the reflected light of the first off-axis parabolic mirror 42 forms an angle of 45 degrees with the surface of the sample stage 91. The second off-axis parabolic mirror 43 and the first off-axis parabolic mirror 42 are symmetrically arranged relative to the incidence point of the sample on the sample table 91, the infrared detector 6 is positioned on the reflected light path of the second off-axis parabolic mirror 43, and the computer 8 is connected with the infrared detector 6.
Parallel light beams emitted by the infrared light source 1 enter the polaroid 2 to obtain parallel polarized light beams, the polarized light beams are reflected by the plane reflector 41 after being modulated by the interferometer 3, and then are converged by the first off-axis parabolic mirror 42 to be projected onto the surface of an etching object to be detected in the etching reaction cavity 9 at an angle of 45 degrees, and reflected light beams are reflected by the off-axis parabolic mirror 43 and are parallelly shot into the infrared detector 6. The infrared detector 6 includes signal acquisition, amplification, filtering, digital-to-analog conversion, and other functions. The interference signal collected by the infrared detector is sent to the computer 8 after being preprocessed. The interference signal is subjected to Fourier transform processing by a computer 8 to obtain a reflection spectrum of the groove structure, and then the measurement spectrum is filtered and analyzed by the methods of the steps (4) to (7), so that a groove geometric parameter value is extracted and obtained.
Claims (3)
1. A micro-nano deep groove structure on-line measuring method comprises the following steps:
step 1, projecting an infrared light beam to the surface of an object to be detected containing a micro-nano deep groove structure, wherein the wavelength of the infrared light beam is 2-20 um;
2, after the incident light beam is reflected by each surface of the micro-nano deep groove structure, receiving each reflection signal by using an infrared detector to obtain an interference signal containing the geometric information of the groove;
step3, carrying out Fourier transform on the interference signal obtained in the step2 to obtain an infrared reflection spectrum based on wave number;
step4, low-pass filtering is carried out on the infrared reflection spectrum obtained in the step3, and a stray light spectrum on the back of the object to be measured is filtered out, so that a measurement reflection spectrum reflecting the structural characteristics of the groove is obtained;
5, establishing an equivalent multilayer thin film stack optical model according to the characteristics of the deep groove structure to be detected, calculating the reflection coefficient r of the equivalent thin film stack under each wavelength by using a formula (I), and obtaining the theoretical reflection spectrum of the groove structure by using the reflection coefficient r;
wherein, <math> <mrow> <mrow> <mfenced open='(' close=')' separators=' ,'> <mtable> <mtr> <mtd> <msub> <mi>M</mi> <mn>11</mn> </msub> </mtd> <mtd> <msub> <mi>M</mi> <mn>12</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>M</mi> <mn>21</mn> </msub> </mtd> <mtd> <msub> <mi>M</mi> <mn>22</mn> </msub> </mtd> </mtr> </mtable> </mfenced> </mrow> <mo>=</mo> <msubsup> <mi>D</mi> <mn>0</mn> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mrow> <mo>[</mo> <munderover> <mi>Π</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msub> <mi>D</mi> <mi>l</mi> </msub> <msub> <mi>P</mi> <mi>l</mi> </msub> <msubsup> <mi>D</mi> <mi>l</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>]</mo> </mrow> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mi>II</mi> <mo>)</mo> </mrow> </mrow></math>
wherein in formula (II), M11、M12、M21、M22For intermediate variables of the multilayer optical propagation matrix, D0Is the optical characteristic matrix of the environment, DsIs a matrix of optical features of the substrate, PlIs a matrix function of the phase change angle of the l-th layer, DlIs a matrix function of the refractive index and angle of refraction of the first layer of the film stack, where DlCalculated according to formula (III) or (IV):
for the TE polarization direction:
for the TM polarization direction:
wherein, thetalAngle of refraction of the l layer, nTE2And nTM2The calculation formula is respectively formula (V) and formula (VI) for the equivalent refractive index of TE polarization and TM polarization direction of each equivalent layer:
wherein n isTE0And nTM0The zero order equivalent refractive indices for the TE and TM polarization directions, respectively, i.e. the zero order diffraction in scatterometry; λ is the probe beam wavelength, p is the trench array period length, f is the layer duty cycle, ngAnd nmRespectively, the refractive index of the trench material and the refractive index of the filling material therein;
and 6, fitting the theoretical reflection spectrum obtained in the step 5 with the measured reflection spectrum obtained in the step4, and extracting to obtain geometric morphology parameters of the micro-nano deep groove structure.
2. The on-line measuring method of the micro-nano deep trench structure according to claim 1, characterized in that: and 6, extracting geometric morphology parameters of the micro-nano deep groove structure according to the process:
step 6.1: establishing a multilayer artificial neural network according to the reflection spectrum characteristics of the groove and the quantity of the parameters to be measured;
step 6.2: determining the range of the groove depth and the range of the groove width of each layer of the groove structure respectively according to the groove structure design and the processing process to obtain the range of a training sample set; calculating the reflection spectrum of the equivalent optical model under each groove and groove width by using the equivalent optical modeling method in the step 5 to obtain a training sample set (O) of the BP networki，Ii) Wherein O isiIs the reflection spectral vector, IiThe method comprises the steps of (1) obtaining a geometric parameter vector to be measured of a groove, wherein i is 1., and N is the number of created samples;
6.3, step: training the BP network by using the training sample set created in the step 6.2, wherein the training input is a reflection spectrum vector OiThe output is a geometric parameter vector I to be measured of the groovei；
6.4, step: inputting the measured reflection spectrum filtered in the step4 into the neural network trained in the step 6.3, and outputting a groove measurement initial value;
6.5, step: and (4) taking the initial groove measurement value output in the step 6.4 as an initial value of a local iterative search algorithm, fitting the measured reflection spectrum obtained in the step4 by using the theoretical reflection spectrum obtained in the step 5, and extracting to obtain the required geometric parameter value of the groove.
3. An apparatus for implementing the method of claim 1, wherein:
the infrared light source (1), the infrared polaroid (2), the interferometer (3), the plane reflector (41) and the first off-axis parabolic mirror (42) are sequentially arranged on the same light path, the sample stage (91) is positioned on a reflection light path of the first off-axis parabolic mirror (42), and the reflection light of the first off-axis parabolic mirror (42) forms an angle of 45 degrees with the surface of the sample stage (91); the second off-axis parabolic mirror (43) and the first off-axis parabolic mirror (42) are symmetrically arranged relative to the incidence point of a sample on the sample table (91), the infrared detector (6) is positioned on a reflected light path of the second off-axis parabolic mirror (43), and the computer (8) is connected with the infrared detector (6); and the computer (8) receives the interference signal output by the infrared detector (6) after preprocessing, performs Fourier transform processing to obtain the reflection spectrum of the groove structure, processes the interference signal according to the processes from the step4 to the step 6, and extracts and obtains the required geometric parameter value of the groove.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2008101972791A CN101393015B (en) | 2008-10-17 | 2008-10-17 | On-line measurement method and device for micro/nano deep trench structure |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2008101972791A CN101393015B (en) | 2008-10-17 | 2008-10-17 | On-line measurement method and device for micro/nano deep trench structure |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101393015A true CN101393015A (en) | 2009-03-25 |
| CN101393015B CN101393015B (en) | 2010-06-16 |
Family
ID=40493433
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2008101972791A Active CN101393015B (en) | 2008-10-17 | 2008-10-17 | On-line measurement method and device for micro/nano deep trench structure |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101393015B (en) |
Cited By (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2489722A (en) * | 2011-04-06 | 2012-10-10 | Precitec Optronik Gmbh | Apparatus and method for determining a depth of a trench or via in the surface of a semiconductor wafer |
| CN103824788A (en) * | 2012-11-19 | 2014-05-28 | 上海华虹宏力半导体制造有限公司 | Groove bottom particle detection method |
| CN105023856A (en) * | 2014-04-17 | 2015-11-04 | 应用材料公司 | Accurate film thickness control in gap-fill technology |
| US9494409B2 (en) | 2011-06-17 | 2016-11-15 | Precitec Optronik Gmbh | Test device for testing a bonding layer between wafer-shaped samples and test process for testing the bonding layer |
| US9500471B2 (en) | 2013-06-17 | 2016-11-22 | Precitec Optronik Gmbh | Optical measuring device and method for acquiring in situ a stage height between a support and an edge region of an object |
| CN106247976A (en) * | 2016-07-12 | 2016-12-21 | 北京理工大学 | The auxiliary device of a kind of high inclination-angle micro-nano structure surface measuring three-dimensional morphology and method |
| CN106441143A (en) * | 2016-10-12 | 2017-02-22 | 哈尔滨工业大学 | Method for measuring depth of groove sample by using optical microscopic mode |
| CN106796105A (en) * | 2014-10-16 | 2017-05-31 | 科磊股份有限公司 | The measurement of multiple Patternized technique |
| US9677871B2 (en) | 2012-11-15 | 2017-06-13 | Precitec Optronik Gmbh | Optical measuring method and measuring device having a measuring head for capturing a surface topography by calibrating the orientation of the measuring head |
| CN106996749A (en) * | 2017-03-31 | 2017-08-01 | 西安理工大学 | The narrow groove geometric parameter detection means of pipe inner circumferential annular and detection method |
| WO2018146683A1 (en) * | 2017-02-09 | 2018-08-16 | Ramot At Tel-Aviv University Ltd. | Method and system for characterizing a nanostructure by machine learning |
| CN109427609A (en) * | 2017-08-30 | 2019-03-05 | 台湾积体电路制造股份有限公司 | System and method of the semiconductor wafer in X -ray inspection X |
| CN109465541A (en) * | 2017-09-06 | 2019-03-15 | 株式会社迪思科 | Height detecting device and laser processing device |
| US10234265B2 (en) | 2016-12-12 | 2019-03-19 | Precitec Optronik Gmbh | Distance measuring device and method for measuring distances |
| US10466357B1 (en) | 2018-12-04 | 2019-11-05 | Precitec Optronik Gmbh | Optical measuring device |
| CN111094919A (en) * | 2017-09-19 | 2020-05-01 | 横河电机株式会社 | Fourier spectrum analysis device |
| CN111288900A (en) * | 2020-03-30 | 2020-06-16 | 哈尔滨工业大学 | Edge positioning method for groove width fixed value |
| CN111587478A (en) * | 2018-06-28 | 2020-08-25 | 应用材料公司 | Training spectrum generation for machine learning systems for spectral monitoring |
| CN111902924A (en) * | 2018-03-13 | 2020-11-06 | 应用材料公司 | Machine learning system for monitoring of semiconductor processing |
| CN112097645A (en) * | 2020-08-31 | 2020-12-18 | 南京理工大学 | High depth-width ratio micro-structure reflection type interference microscopic nondestructive measuring device |
| CN112384749A (en) * | 2020-03-13 | 2021-02-19 | 长江存储科技有限责任公司 | System and method for semiconductor chip hole geometry metrology |
| CN113607084A (en) * | 2021-08-11 | 2021-11-05 | 浙江大学 | Method for measuring submillimeter groove structure based on white light interference and SPGD |
| CN114295908A (en) * | 2021-12-01 | 2022-04-08 | 昆山毅普腾自动化技术有限公司 | Rapid detection method for internal microstructure of nano electronic device based on F-SRU network |
| CN114770224A (en) * | 2022-05-25 | 2022-07-22 | 北京理工大学 | Ultra-precision machining tool mark on-site detection method |
| US11460577B2 (en) | 2017-11-09 | 2022-10-04 | Precitec Optronik Gmbh | Distance measuring device |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4927485A (en) * | 1988-07-28 | 1990-05-22 | Applied Materials, Inc. | Laser interferometer system for monitoring and controlling IC processing |
| CN100587394C (en) * | 2007-09-20 | 2010-02-03 | 华中科技大学 | Method and device for measuring micro-nano deep groove structure |
-
2008
- 2008-10-17 CN CN2008101972791A patent/CN101393015B/en active Active
Cited By (43)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2489722A (en) * | 2011-04-06 | 2012-10-10 | Precitec Optronik Gmbh | Apparatus and method for determining a depth of a trench or via in the surface of a semiconductor wafer |
| US9297645B2 (en) | 2011-04-06 | 2016-03-29 | Precitec Optronik Gmbh | Apparatus and method for determining a depth of a region having a high aspect ratio that protrudes into a surface of a semiconductor wafer |
| GB2489722B (en) * | 2011-04-06 | 2017-01-18 | Precitec Optronik Gmbh | Apparatus and method for determining a depth of a region having a high aspect ratio that protrudes into a surface of a semiconductor wafer |
| US9494409B2 (en) | 2011-06-17 | 2016-11-15 | Precitec Optronik Gmbh | Test device for testing a bonding layer between wafer-shaped samples and test process for testing the bonding layer |
| US9677871B2 (en) | 2012-11-15 | 2017-06-13 | Precitec Optronik Gmbh | Optical measuring method and measuring device having a measuring head for capturing a surface topography by calibrating the orientation of the measuring head |
| US9982994B2 (en) | 2012-11-15 | 2018-05-29 | Precitec Optronik Gmbh | Optical measuring method and measuring device having a measuring head for capturing a surface topography by calibrating the orientation of the measuring head |
| CN103824788A (en) * | 2012-11-19 | 2014-05-28 | 上海华虹宏力半导体制造有限公司 | Groove bottom particle detection method |
| US9500471B2 (en) | 2013-06-17 | 2016-11-22 | Precitec Optronik Gmbh | Optical measuring device and method for acquiring in situ a stage height between a support and an edge region of an object |
| TWI638131B (en) * | 2013-06-17 | 2018-10-11 | 普雷茨特光電有限公司 | Optical measuring device for acquiring differences in distance and optical measuring method |
| CN105023856B (en) * | 2014-04-17 | 2019-08-16 | 应用材料公司 | Accurate plastics thickness control in clearance filled technology |
| CN105023856A (en) * | 2014-04-17 | 2015-11-04 | 应用材料公司 | Accurate film thickness control in gap-fill technology |
| US10215559B2 (en) | 2014-10-16 | 2019-02-26 | Kla-Tencor Corporation | Metrology of multiple patterning processes |
| CN106796105A (en) * | 2014-10-16 | 2017-05-31 | 科磊股份有限公司 | The measurement of multiple Patternized technique |
| CN106796105B (en) * | 2014-10-16 | 2020-01-31 | 科磊股份有限公司 | Metrology of multiple patterning processes |
| CN106247976A (en) * | 2016-07-12 | 2016-12-21 | 北京理工大学 | The auxiliary device of a kind of high inclination-angle micro-nano structure surface measuring three-dimensional morphology and method |
| CN106247976B (en) * | 2016-07-12 | 2020-04-10 | 北京理工大学 | Auxiliary device and method for measuring three-dimensional morphology of surface of large-dip-angle micro-nano structure |
| CN106441143B (en) * | 2016-10-12 | 2019-03-08 | 哈尔滨工业大学 | A method of groove sample depth is measured using optical microphotograph mode |
| CN106441143A (en) * | 2016-10-12 | 2017-02-22 | 哈尔滨工业大学 | Method for measuring depth of groove sample by using optical microscopic mode |
| US10234265B2 (en) | 2016-12-12 | 2019-03-19 | Precitec Optronik Gmbh | Distance measuring device and method for measuring distances |
| WO2018146683A1 (en) * | 2017-02-09 | 2018-08-16 | Ramot At Tel-Aviv University Ltd. | Method and system for characterizing a nanostructure by machine learning |
| CN106996749A (en) * | 2017-03-31 | 2017-08-01 | 西安理工大学 | The narrow groove geometric parameter detection means of pipe inner circumferential annular and detection method |
| CN109427609A (en) * | 2017-08-30 | 2019-03-05 | 台湾积体电路制造股份有限公司 | System and method of the semiconductor wafer in X -ray inspection X |
| CN109465541A (en) * | 2017-09-06 | 2019-03-15 | 株式会社迪思科 | Height detecting device and laser processing device |
| CN109465541B (en) * | 2017-09-06 | 2021-11-19 | 株式会社迪思科 | Height detection device and laser processing device |
| CN111094919A (en) * | 2017-09-19 | 2020-05-01 | 横河电机株式会社 | Fourier spectrum analysis device |
| US11460577B2 (en) | 2017-11-09 | 2022-10-04 | Precitec Optronik Gmbh | Distance measuring device |
| CN111902924A (en) * | 2018-03-13 | 2020-11-06 | 应用材料公司 | Machine learning system for monitoring of semiconductor processing |
| CN111587478A (en) * | 2018-06-28 | 2020-08-25 | 应用材料公司 | Training spectrum generation for machine learning systems for spectral monitoring |
| JP2021528861A (en) * | 2018-06-28 | 2021-10-21 | アプライド マテリアルズ インコーポレイテッドＡｐｐｌｉｅｄ Ｍａｔｅｒｉａｌｓ，Ｉｎｃｏｒｐｏｒａｔｅｄ | Generation of training spectra for machine learning systems for spectroscopic image monitoring |
| JP7532262B2 (en) | 2018-06-28 | 2024-08-13 | アプライド マテリアルズ インコーポレイテッド | Generating training spectra for machine learning systems for spectroscopic image monitoring |
| US12020159B2 (en) | 2018-06-28 | 2024-06-25 | Applied Materials, Inc. | Training spectrum generation for machine learning system for spectrographic monitoring |
| US10466357B1 (en) | 2018-12-04 | 2019-11-05 | Precitec Optronik Gmbh | Optical measuring device |
| CN112384749A (en) * | 2020-03-13 | 2021-02-19 | 长江存储科技有限责任公司 | System and method for semiconductor chip hole geometry metrology |
| US11674909B2 (en) | 2020-03-13 | 2023-06-13 | Yangtze Memory Technologies Co., Ltd. | Systems and methods for semiconductor chip hole geometry metrology |
| CN111288900B (en) * | 2020-03-30 | 2022-01-14 | 哈尔滨工业大学 | Edge positioning method for groove width fixed value |
| CN111288900A (en) * | 2020-03-30 | 2020-06-16 | 哈尔滨工业大学 | Edge positioning method for groove width fixed value |
| CN112097645A (en) * | 2020-08-31 | 2020-12-18 | 南京理工大学 | High depth-width ratio micro-structure reflection type interference microscopic nondestructive measuring device |
| CN112097645B (en) * | 2020-08-31 | 2021-12-10 | 南京理工大学 | High depth-width ratio micro-structure reflection type interference microscopic nondestructive measuring device |
| CN113607084A (en) * | 2021-08-11 | 2021-11-05 | 浙江大学 | Method for measuring submillimeter groove structure based on white light interference and SPGD |
| CN114295908A (en) * | 2021-12-01 | 2022-04-08 | 昆山毅普腾自动化技术有限公司 | Rapid detection method for internal microstructure of nano electronic device based on F-SRU network |
| CN114295908B (en) * | 2021-12-01 | 2023-09-26 | 昆山毅普腾自动化技术有限公司 | Rapid detection method for internal microstructure of nano electronic device based on F-SRU network |
| CN114770224A (en) * | 2022-05-25 | 2022-07-22 | 北京理工大学 | Ultra-precision machining tool mark on-site detection method |
| CN114770224B (en) * | 2022-05-25 | 2024-03-08 | 北京理工大学 | Ultra-precise machining tool mark in-situ detection method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101393015B (en) | 2010-06-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101393015B (en) | On-line measurement method and device for micro/nano deep trench structure | |
| US7612891B2 (en) | Measurement of thin films using fourier amplitude | |
| CN100587394C (en) | Method and device for measuring micro-nano deep groove structure | |
| KR101590389B1 (en) | Rotating-element spectroscopic ellipsometer and method for measurement precision prediction of rotating-element spectroscopic ellipsometer, and recording medium storing program for executing the same, and recording medium storing program for executing the same | |
| CN102082108A (en) | Method and device for rapidly measuring sidewall appearance of micro-nano deep groove structure | |
| WO2016154780A1 (en) | Laser interference wavelength lever-type absolute distance measurement apparatus and method | |
| KR20000061037A (en) | Method and Apparatus for Three Dimensional Thickness Profile Measurement of Transparent Dielectric Thin-Film by White-Light Scanning Interferometry | |
| CN105352915B (en) | A kind of dynamic measurement method of refractive index Two dimensional Distribution | |
| CN105066889A (en) | A portable thin film thickness measuring device and a film thickness measuring method thereof | |
| CN107121080A (en) | A kind of method for measuring ordered porous nano film thickness | |
| CN114543690A (en) | Optical characteristic modeling method, photoacoustic measurement method and device | |
| CN109540007A (en) | The measurement method and measuring device of super thick film | |
| Ku et al. | Characterization of high density through silicon vias with spectral reflectometry | |
| Bae et al. | Optical method for simultaneous thickness measurements of two layers with a significant thickness difference | |
| CN106123805B (en) | Plated film device three-dimensional topography measurement method based on white light scanning interference | |
| Vellekoop et al. | Determination of the diffusion constant using phase-sensitive measurements | |
| CN105158165A (en) | Ultrafast ellipsometer and measuring method | |
| CN111076668B (en) | Differential reflection spectrum measurement method for nano-thickness SiO2 thickness | |
| Taudt | Development and Characterization of a dispersion-encoded method for low-coherence interferometry | |
| CN104655029B (en) | A kind of position phase reinforced membranes method for measuring thickness and system | |
| CN114184583B (en) | Optical measurement and evaluation method for depth consistency of high aspect ratio microstructure | |
| CN113405486B (en) | Film morphology detection system and method based on white light interference time-frequency domain analysis | |
| Lo et al. | Polarization scanning ellipsometry method for measuring effective ellipsometric parameters of isotropic and anisotropic thin films | |
| Bass et al. | An angular spectrum approach to inverse synthesis for the characterization of optical and geometrical properties of semiconductor thin films | |
| Lo et al. | An approach for measuring the ellipsometric parameters of isotropic and anisotropic thin films using the Stokes parameter method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |