CN117153298A - Film parameter reverse optimization method based on ellipsometry - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000000572 ellipsometry Methods 0.000 title claims abstract description 30
- 238000005457 optimization Methods 0.000 title claims abstract description 30
- 238000005259 measurement Methods 0.000 claims abstract description 42
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
- G01B11/0616—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material of coating
- G01B11/0625—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material of coating with measurement of absorption or reflection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/55—Specular reflectivity
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/59—Transmissivity
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- G16C60/00—Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation
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Abstract
The invention discloses a film parameter reverse optimization method based on an ellipsometry method, which comprises the following steps of S1 cleaning a film sample to be detected; s2, dividing the region of the film sample to be measured, selecting a middle region grid and region grids adjacent to four sides of the middle region grid as measurement regions, and performing cross point measurement on each measurement region to obtain polarization angle parameters and rho light and S light reflection phase difference parameters of each measurement region and obtain each transmittance and each reflectance of each measurement region; s3, modeling and fitting the polarization angle parameters of each measuring area and the reflection phase difference parameters of rho light and S light to obtain the film thickness and extinction coefficient of each measuring area; s4, comparing the film thickness and the extinction coefficient of each measuring area, and calculating to obtain the average film thickness and the extinction coefficient; s, designing a film system according to the average thickness and the extinction coefficient of the calculated film layer, and controlling the reverse optimization of the design and the actual plating gap to achieve the consistency of the designed film thickness and the actual film thickness.
Description
[ technical field ]
The invention relates to a film parameter reverse optimization method based on an ellipsometry method.
[ background Art ]
The film technology is indispensable in daily life, and is a generic term for various technologies related to film preparation, testing and the like. At present, various thin film preparation methods exist in industry, and various modes for measuring optical parameters are also available. At present, in the traditional film plating and research and development, a physical vapor deposition method is generally used, so that the problem that the film plating and the design value are completely consistent is difficult to realize, the measurement center point of a sample to be measured is used as a standard when the optical parameters are measured, the film plating, the research and development and the design are inconsistent, the problem that the measurement is not accurate enough is solved, and the optimization of the plated film is difficult.
[ summary of the invention ]
The invention overcomes the defects of the prior art and provides a film parameter reverse optimization method based on an ellipsometry.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a film parameter reverse optimization method based on an ellipsometry is characterized by comprising the following steps of: comprises the following steps of
S1, cleaning a film sample to be tested;
s2, carrying out regional meshing on the film sample to be detected, carrying out meshing according to the size of the sample, and setting a d-dimensional data set X= { X 1 ,x 2 ,x 3 ,.....,x n Setting the value in the ith dimension to [ l ] i ,h i ]I=1, 2,.,. D, d-dimensional data space is: s= [ [ l ] 1 ,h 1 ]×[l 2 ,h 2 ]×.....×[l d ,h d ])]Dividing each dimension of the data space into equal and disjoint grid units, wherein the calculation formula of the grid is as follows:
the value of the grid dividing side length T can influence the measurement point, and too large can influence the measurement accuracy and too small can influence the measurement speed, so that the algorithm effect is better when alpha epsilon (0, 2); selecting a middle area grid, an upper area grid adjacent to the middle area grid, a lower area grid adjacent to the middle area grid, a left area grid adjacent to the middle area grid and a right area grid adjacent to the middle area grid as measurement areas, respectively carrying out cross point position measurement on each measurement area through an SE-VM-L wide spectrum full-Mueller matrix ellipsometer, and calculating to obtain polarization angle parameters and rho light and s light reflection phase difference parameters of each measurement area; respectively carrying out cross point measurement on each measuring area through a spectrometer to obtain the transmittance and the reflectivity of each measuring area;
s3, modeling and fitting the polarization angle parameters of each measuring area and the reflection phase difference parameters of rho light and S light to obtain the film thickness and extinction coefficient of each measuring area;
s4, comparing the film thickness and the extinction coefficient of each measuring area, and calculating to obtain the average film thickness and the extinction coefficient;
s5, designing a film system according to the average thickness and the extinction coefficient of the calculated film layer, and controlling the gap between the design and the actual plating to reversely optimize.
The film parameter reverse optimization method based on the ellipsometry is characterized by comprising the following steps of: and S1, cleaning the film sample to be tested through dust sweeping and alcohol wiping.
The film parameter reverse optimization method based on the ellipsometry is characterized by comprising the following steps of: s1 also comprises
S11, analyzing a film structure of the film sample to be tested, wherein the film structure comprises a single-layer film, a double-layer film and a three-layer film.
The film parameter reverse optimization method based on the ellipsometry is characterized by comprising the following steps of: s1 also comprises
S12, analyzing the sample type of the film sample to be tested, wherein the sample type comprises a metal sample, a semiconductor sample and a medium sample.
The film parameter reverse optimization method based on the ellipsometry is characterized by comprising the following steps of: in S2, the polarization state change after the SE-VM-L broad spectrum full-Mueller matrix ellipsometer measuring light and each measuring area sample are interacted obtains the polarization angle parameter psi and the reflection phase difference parameter delta of rho light and S light, thus obtaining
Wherein r is p Is the vertical axis direction polarization of light, r s Is the polarization of the light in the longitudinal direction.
The film parameter reverse optimization method based on the ellipsometry is characterized by comprising the following steps of: the modeling model in S3 comprises a vibrator model and a B-spline model.
The film parameter reverse optimization method based on the ellipsometry is characterized by comprising the following steps of: the vibrator model comprises a Cauchy model, a Tauc Lorentz model, a Lorentz model and a Gaussian model.
The film parameter reverse optimization method based on the ellipsometry is characterized by comprising the following steps of: the Cauchy model is
Where n is the refractive index, A is the parameter controlling the deflection of the curve, and B and C are the parameters controlling the curvature.
The film parameter reverse optimization method based on the ellipsometry is characterized by comprising the following steps of: the dielectric constant epsilon of known thin film materials in Gaussian models is
ε＝ε 1 -iε 2
Wherein ε 1 And epsilon 2 The complex refractive index N1 of the material is as follows
N 1 ＝n-ik
Wherein n is refractive index, k is extinction coefficient, and the refractive index and extinction coefficient of the material are respectively
ε＝N 2 ＝ε 1 -iε 2 ＝(n 2 -k 2 )-2ink
From the above formula, the dielectric constant and refractive index of the material can be converted from each other, and the refractive index and extinction coefficient of the material can be obtained from the dielectric constant of the material.
The film parameter reverse optimization method based on the ellipsometry is characterized by comprising the following steps of: s3, after modeling, judging the mean square error of the fitting effect to be
Wherein K is the number of fitted curves; n (N) 2 The number of the fitting band points is the number; m is the number of fitting parameters; Γ is the spectral curve;is the difference between the simulated spectrum and the measured spectrum.
The beneficial effects of the invention are as follows:
the invention improves the optimizing and measuring method, proposes a cross measuring method, and carries out regional network on the film sample to be measuredGrid division is performed according to the sample size, and a d-dimensional data set X= { X is set 1 ,x 2 ,x 3 ,.....,x n Setting the value in the ith dimension to [ l ] i ,h i ]I=1, 2,.,. D, d-dimensional data space is: s= [ [ l ] 1 ,h 1 ]×[l 2 ,h 2 ]×.....×[l d ,h d ])]Dividing each dimension of a data space into equal and disjoint grid units, calculating grid side lengths T, selecting a middle area grid, an upper area grid adjacent to the middle area grid, a lower area grid adjacent to the middle area grid, a left grid adjacent to the middle area grid and a right grid adjacent to the middle area grid as measurement areas, respectively carrying out cross measurement on each measurement area through a SE-VM-L type wide-spectrum full-Mueller matrix ellipsometer and a spectrometer to obtain film thickness and optical parameters, carrying out modeling fitting on the measured data, finally obtaining data, taking an optimized average value of the data, enabling the measured film parameters to be more accurate, reversely optimizing the film parameters during plating through the tested film parameters, and realizing that the design is consistent with the actual design.
[ description of the drawings ]
FIG. 1 is a schematic diagram of a measurement point of a film sample to be measured according to the present invention;
FIG. 2 is a flow chart of ellipsometry reverse optimization in accordance with the present invention;
FIG. 3 is an ellipsometry graph of an example Ag metal film;
FIG. 4 is a graph of an example Corning plate ellipsometry test;
FIG. 5 is a graph showing transmittance data of a film sample to be tested according to an embodiment;
FIG. 6 is a schematic view of a modeling fit of example B-spline;
FIG. 7 is a graph of a film sample fit to be tested in an example;
FIG. 8 is a graph of the Nk plot of a film sample to be tested according to an embodiment;
FIG. 9 is a graph of NCS of a film sample to be tested in the examples.
Detailed description of the preferred embodiments
The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that all directional indicators (such as up, down, left, right, front, and rear …) in the embodiments of the present invention are merely used to explain the relative positional relationship, movement, etc. between the components in a particular posture (as shown in the drawings), and if the particular posture is changed, the directional indicator is changed accordingly. Furthermore, the description of "preferred," "less preferred," and the like, herein is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "preferred", "less preferred" may include at least one such feature, either explicitly or implicitly.
As shown in FIGS. 1-2, the method for reverse optimization of film parameters based on ellipsometry comprises
S1, cleaning a film sample to be detected, namely cleaning the film sample to be detected through dust sweeping and alcohol wiping;
s11, analyzing a film structure of a film sample to be tested, wherein the film structure comprises a single-layer film, a double-layer film and a three-layer film;
s12, analyzing the sample type of the film sample to be tested, wherein the sample type comprises a metal sample, a semiconductor sample and a medium sample.
S2, carrying out regional grid division on the film sample to be detected, carrying out grid division according to the size of the sample, specifically dividing into regional grid division according to a nine-grid, and setting a d-dimension data set X= { X 1 ,x 2 ,x 3 ,.....,x n Setting the value in the ith dimension to [ l ] i ,h i ]I=1, 2,.,. D, d-dimensional data space is: s= [ [ l ] 1 ,h 1 ]×[l 2 ,h 2 ]×.....×[l d ,h d ])]Dividing each dimension of the data space into equal and disjoint grid units, wherein the calculation formula of the grid is as follows:
the method comprises the steps that alpha is a control parameter, the value of grid dividing side length T affects measurement point taking, the measurement accuracy is affected by too large grid dividing side length T, and the measurement speed is affected by too small grid dividing side length T, therefore, when alpha is E (0, 2), the algorithm effect is good, middle area grids, upper area grids adjacent to the middle area grids, lower area grids adjacent to the middle area grids, left area grids adjacent to the middle area grids and right area grids adjacent to the middle area grids are selected as measurement areas, cross point measurement is conducted on each measurement area through an SE-VM-L type wide spectrum full-Mueller matrix ellipsometer, and polarization angle parameters of each measurement area and reflection phase difference parameters of rho light and s light are calculated; respectively carrying out cross point measurement on each measuring area through a spectrometer to obtain the transmittance and the reflectivity of each measuring area;
s3, modeling and fitting the polarization angle parameters of each measuring area and the reflection phase difference parameters of rho light and S light to obtain the film thickness and extinction coefficient of each measuring area;
the modeling model comprises a vibrator model, a B-spline model and other models, wherein the vibrator model has a series of optical models which have physical significance and can be iterated by ellipsometry nk parameter modeling; every equidistant interval of a control point in the virtual line of the model Psi/Delta is forced matching of the model and the measurement solid line. Applied to unknown or known materials for the reconstruction nk fitting
The vibrator model comprises a Cauchy model, a Tauc Lorentz model, a Lorentz model and a Gaussian model.
The Cauchy model is also typically used in the transmissive region of the material
Where n is the refractive index, A is the parameter controlling the deflection of the curve, and B and C are the parameters controlling the curvature.
The Tauc-Lorentz model was developed based on the Lorentz model to describe the dispersion characteristics of amorphous materials, and the dielectric constants of the materials were described by five parameters (ε -Einf, A, C, en0, eg).
Lorentz model) establishes a classical electromagnetic theory, and the relationship between electrons and atomic nuclei is equivalent to a spring vibrator, the incident light is regarded as an external force, and the interaction between the incident light and the electrons and atomic nuclei is explained by Newton's second law.
Gaussian is a model of the vibrator based on a Gaussian function, and the characteristic of the imaginary part of the vibrator is expressed as a symmetrical state and is usually used together with Tauc-Lorentz.
The hole Model describes the measurement of the dispersion resulting from absorption outside the spectral range, being a zero-scattering oscillator, affecting only the real part of the dielectric constant.
S3, evaluating modeling fitting results, wherein the evaluation comprises the mutual matching degree of a measured spectrum and a model spectrum; whether the mean square error MSE is reasonable; whether the fitting result accords with the actual situation, such as the film thickness, the optical constant, the nanostructure parameters and the optical constant of the material accord with the physical rule.
Wherein, after modeling, the mean square error MSE of the fitting effect is judged to be
Wherein; k is the number of fitting curves; n (N) 2 The number of the fitting band points is the number; m is the number of fitting parameters; Γ is the spectral curve;is the difference between the simulated spectrum and the measured spectrum.
S4, comparing the film thickness and the extinction coefficient of each measuring area, and calculating to obtain the average film thickness and the extinction coefficient.
S5, designing a film system according to the average thickness and the extinction coefficient of the calculated film layer, and controlling the gap between the design and the actual plating to reversely optimize.
Hereinafter, a corning board substrate coated with a single Ag metal thin film will be described as an example.
S1, preparing a sample to be tested, taking a corning board substrate coated with a single-layer Ag metal film as an example, wherein the size of the sample is 80mm 1.1mm, the thickness of the original film coated with the single-layer Ag metal film is 16.69nm, and the measuring range is as follows: 300nm to 1700nm, firstly cleaning the film sample to be tested by dust sweeping, alcohol wiping and the like;
s2, carrying out regional meshing on the Ag metal film sample, and carrying out meshing according to the size of the sample, wherein a 3-dimensional data set X= { X is set 1 ,x 2 ,x 3 Setting the value in the ith dimension to [ l ] i ,h i ]In i=1, 2, 3-dimensional data space is: s= [ [ l ] 1 ,h 1 ]×[l 2, h 2 ]×[l 3 ,h 3 ])]Dividing each dimension of the data space into equal and disjoint grid units, wherein the calculation formula of the grid is as follows:
the value of the grid dividing side length T can influence the measurement point, and too large the grid dividing side length T can influence the measurement accuracy and too small the measurement speed, so that the algorithm effect is good when alpha epsilon (0, 2). The present invention uses α=1.5.
Measuring centers of all measurement areas by using a cross measurement method, as shown in a schematic diagram of measurement points after the thin film sample to be measured is subjected to nine-grid area grid division in FIG. 1, measuring and analyzing the cross points by using a SE-VM-L wide spectrum full-Mueller matrix ellipsometer and spectrometer equipment, and respectively measuring Ag metal thin films, corning board substrate wide spectrum curves and the sample transmittance in the cross points of all the measurement areas, wherein measurement data are shown in FIGS. 3-5;
s3, modeling and fitting data measured by cross point positions of all measurement areas, taking an Ag metal film as an example to establish a sample model, wherein the metal film system is complex and has uncertainty, firstly, establishing a Kang Ningban substrate/Ag metal film/air structural model, trying to fit the model with large error and multiple solutions, and simultaneously introducing a spectrometer to measure the sample transmittance, and modeling by using a Gaussian model, wherein the dielectric constant of the known film material is as follows:
ε＝ε 1 -iε 2
wherein: epsilon is the dielectric constant of the material; epsilon 1 And epsilon 2 Is the real and imaginary parts of the dielectric constant. The complex refractive index N1 of a material can be expressed as:
N 1 ＝n-ik
wherein: n (N) 1 Is the complex refractive index of the material; n is the refractive index; k is the extinction coefficient. The refractive index and extinction coefficient of a material can be expressed as:
ε＝N 2 ＝ε 1 -iε 2 ＝(n 2 -k 2 )-2ink
from the above formula, the dielectric constant and refractive index of the material can be mutually converted, the real part and the imaginary part of the dielectric constant are fitted by modeling by using a B-spline model, and the refractive index and extinction coefficient of the material can be obtained by measuring the dielectric constant of the material, as shown in a B-spline modeling fitting diagram of FIG. 6.
And S2 is repeated to obtain a well-fitted sample Psi/Delta curve, a refractive index n and extinction coefficient k curve and an NCS fitting curve, wherein as shown in figures 7-9, the mean square error MSE of the test points of the five optimized measurement areas is 6.341, 4.905, 7.970, 6.128 and 5.345 respectively, and the film thickness is 20.50nm, 19.84nm, 20.33nm, 20.24nm and 20.22nm respectively.
S4, comparing optical constants such as film thickness and extinction coefficient obtained by cross point positions, slightly measuring points with difference, and taking average value to obtain the film thickness of 20.226nm, wherein the film thickness is more reasonable and accurate compared with the traditional measuring mode.
S5, comparing measured film parameter thickness, refractive index n and extinction coefficient k data with plated film data, finding a difference of 3.563nm between the thickness and the measured value, and carrying out reverse research and development and optimization on the control design and actual plating difference according to the measured refractive index and extinction coefficient data and the film system redesign as shown in FIG. 7.
The foregoing description of the preferred embodiments of the present invention should not be construed as limiting the scope of the invention, but rather should be understood to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the following description and drawings or any application directly or indirectly to other relevant art(s).
Claims (10)
1. A film parameter reverse optimization method based on an ellipsometry is characterized by comprising the following steps of: comprises the following steps of
S1, cleaning a film sample to be tested;
s2, carrying out regional grid division on the film sample to be detected, and setting a d-dimensional data set X= { X 1 ,x 2 ,x 3 ,.....,x n Setting the value in the ith dimension to [ l ] i ,h i ]I=1, 2,.,. D, d-dimensional data space is: s= [ [ l ] 1 ,h 1 ]×[l 2 ,h 2 ]×.....×[l d ,h d ])]Dividing each dimension of the data space into equal and disjoint grid units, wherein the calculation formula of the grid is as follows:
alpha is a control parameter, T is a grid dividing side length value, a middle area grid, an upper area grid adjacent to the middle area grid, a lower area grid adjacent to the middle area grid, a left area grid adjacent to the middle area grid and a right area grid adjacent to the middle area grid are selected as measurement areas, cross point position measurement is respectively carried out on each measurement area through an SE-VM-L type wide spectrum full-Mueller matrix ellipsometer, and a polarization angle parameter of each measurement area and a reflection phase difference parameter of rho light and s light are obtained through calculation; respectively carrying out cross point measurement on each measuring area through a spectrometer to obtain the transmittance and the reflectivity of each measuring area;
s3, modeling and fitting the polarization angle parameters of each measuring area and the reflection phase difference parameters of rho light and S light to obtain the film thickness and extinction coefficient of each measuring area;
s4, comparing the film thickness and the extinction coefficient of each measuring area, and calculating to obtain the average film thickness and the extinction coefficient;
s5, designing a film system according to the average thickness and the extinction coefficient of the calculated film layer, and controlling the gap between the design and the actual plating to reversely optimize.
2. The ellipsometry-based thin film parameter reverse optimization method of claim 1, wherein the method comprises the following steps: and S1, cleaning the film sample to be tested through dust sweeping and alcohol wiping.
3. The ellipsometry-based thin film parameter reverse optimization method of claim 1, wherein the method comprises the following steps: s1 also comprises
S11, analyzing a film structure of the film sample to be tested, wherein the film structure comprises a single-layer film, a double-layer film and a three-layer film.
4. The ellipsometry-based thin film parameter reverse optimization method of claim 1, wherein the method comprises the following steps: s1 also comprises
S12, analyzing the sample type of the film sample to be tested, wherein the sample type comprises a metal sample, a semiconductor sample and a medium sample.
5. The ellipsometry-based thin film parameter reverse optimization method of claim 1, wherein the method comprises the following steps: in S2, the polarization state change after the SE-VM-L broad spectrum full-Mueller matrix ellipsometer measuring light and each measuring area sample are interacted obtains the polarization angle parameter psi and the reflection phase difference parameter delta of rho light and S light, thus obtaining
Wherein the method comprises the steps of，r p Is the vertical axis direction polarization of light, r s Is the polarization of the light in the longitudinal direction.
6. The ellipsometry-based thin film parameter reverse optimization method of claim 1, wherein the method comprises the following steps: the modeling model in S3 comprises a vibrator model and a B-spline model.
7. The ellipsometry-based thin film parameter reverse optimization method of claim 6, wherein the method comprises the following steps: the vibrator model comprises a Cauchy model, a Tauc Lorentz model, a Lorentz model and a Gaussian model.
8. The ellipsometry-based thin film parameter reverse optimization method of claim 7, wherein the method comprises the following steps: the Cauchy model is
Where n is the refractive index, A is the parameter controlling the deflection of the curve, and B and C are the parameters controlling the curvature.
9. The ellipsometry-based thin film parameter reverse optimization method of claim 7, wherein the method comprises the following steps: the dielectric constant epsilon of known thin film materials in Gaussian models is
ε＝ε 1 -iε 2
Wherein ε 1 And epsilon 2 The complex refractive index N1 of the material is as follows
N 1 ＝n-ik
Wherein n is refractive index, k is extinction coefficient, and the refractive index and extinction coefficient of the material are respectively
ε＝N 2 ＝ε 1 -iε 2 ＝(n 2 -k 2 )-2ink
From the above formula, the dielectric constant and refractive index of the material can be converted from each other, and the refractive index and extinction coefficient of the material can be obtained from the dielectric constant of the material.
10. The ellipsometry-based thin film parameter reverse optimization method of claim 1, wherein the method comprises the following steps: s3, after modeling, judging the mean square error of the fitting effect to be
Wherein K is the number of fitted curves; n (N) 2 The number of the fitting band points is the number; m is the number of fitting parameters; Γ is the spectral curve;is the difference between the simulated spectrum and the measured spectrum.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117436355A (en) * | 2023-12-21 | 2024-01-23 | 东莞市钜欣电子有限公司 | Method for establishing optical film thickness model and related equipment |
| CN117436355B (en) * | 2023-12-21 | 2024-04-16 | 东莞市钜欣电子有限公司 | Method for establishing optical film thickness model and related equipment |
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