CN105444666B - For the method and device of optical critical dimension measurement - Google Patents
For the method and device of optical critical dimension measurement Download PDFInfo
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Abstract
The present invention describes a kind of method and device for promoting curve of spectrum matching reliability and measuring accuracy in optical critical dimension (OCD) measuring apparatus.It includes carrying out sensitivity analysis in the theoretical spectral of all wavelength points to each structural parameters to be measured and obtains sensitivity with Wavelength distribution；The sensitivity of each structural parameters to be measured is normalized with Wavelength distribution；Systemization weight coefficient is flexibly set and systemization processing is carried out with Wavelength distribution to the normalized sensitivity；It sets to match weight coefficient and carry out evaluation to theoretical spectral and measure spectrum in each wavelength points in matching process of the theoretical spectral with measure spectrum and optimizes the matching degree for operating to judge the two；In this way, it realizes the optimization design of matching evaluation and has reached the promotion of structural parameters match value accuracy to be measured.
Description
Technical Field
The invention relates to measurement of optical Critical dimension of semiconductor manufacturing process, more specifically to a measurement method for improving spectral curve matching reliability and measurement stability in Optical Critical Dimension (OCD) measurement equipment.
Background
In the integrated circuit industry, along with the shrinking of process nodes and the complexity and diversification of device structures, the requirements of the manufacturing and production of extremely large scale integrated circuits on the precision and the sensitivity of measuring equipment are higher and higher. As an important critical dimension measurement technique, the ocd (optical critical dimension) measurement technique is increasingly dominant in the production of logic devices and memories at process nodes of 65nm and below.
With the development of the semiconductor integrated circuit manufacturing industry, the critical dimension in the process is smaller and smaller, the structural parameters of the device to be controlled are more and more, and the traditional optical imaging analysis method cannot meet the measurement of the critical dimension of the process. The new imaging technology is continuously applied to the measurement of the semiconductor process morphology, such as a scanning electron microscope and an atomic force microscope, and can realize the measurement of high-precision critical dimension and groove depth dimension, but the measurement process is complex, the sample to be measured is destructive, and the online measurement cannot be realized. An optical film gauge can measure the film thickness of multiple layers of different materials in unpatterned areas, but not patterned areas such as periodic grating structures. And the OCD measuring equipment acquires specific parameters of the structure through the acquired diffraction signal of the periodic structure of the measured area and the structure model. The OCD measurement technique can realize measurement of critical dimensions and other feature dimensions, and in a specific measurement case, a plurality of obtained process dimensions may be simultaneously and separately completed by a scanning electron microscope, an atomic force microscope, an optical thin film measurement instrument, and the like. Because of the advantages of non-contact, non-destructive, simultaneous measurement of multiple process characteristics, on-line measurement of processes, etc., OCD measurement technology is increasingly used in the semiconductor manufacturing industry and is rapidly developing towards faster and more accurate measurement of finer structures.
As a mainstream process control technology in the current semiconductor manufacturing process, the OCD measurement technology can be described as follows: (1) establishing a theoretical spectrum database corresponding to the appearance of the sample to be detected; (2) obtaining a measurement spectrum of a sample to be measured through OCD measurement equipment; (3) and searching a characteristic spectrum which is best matched with the measured spectrum from the theoretical spectrum database so as to determine the structural parameters to be measured of the sample to be measured.
And establishing a theoretical spectrum database corresponding to the appearance of the sample to be detected, namely calculating the theoretical spectrum of the sample to be detected described by the model according to the model of the grating. As an example, a representative electromagnetic field calculation method thereof is: rigorous Coupled Wave Analysis theory RCWA (Rigorous Coupled-Wave Analysis). The theoretical diffraction spectrum s (x, λ) of the sample to be measured can be calculated by modeling using a correlation theory (e.g., RCWA). In general, the available parameter vector x ═ x (x)0,x1,...,xL-1)T，xjJ ═ 0.,. L-1, which represents all the structural parameters of the structure to be measured, and if the model of the structure to be measured shown in fig. 1 includes the structural parameters CD, SWA, HT, the available parameter vector x ═ (CD, SWA, HT)TTo describe the model of the structure under test.
The process of obtaining the measurement spectrum of the sample to be measured by the OCD measurement device can be described as that the light source of the diffraction spectrometer is incident to the periodic structure area of the sample to be measured through the polarizer, and the diffraction of the sample to be measured includes information of the structure, material, etc. of the sample to be measured in each level of diffraction light. Typically the zero order diffracted light is received by the diffraction detector through an analyzer. The diffractometer processes the received diffracted light signal into a measurement spectrum containing information of the sample to be measured. The values of the measured spectrum are described in the form of the reflectance Rs,RpDescriptions of the polarization state changes tan ψ and cos Δ, fourier coefficients for polarization state analysis α, or direct output Mueller Matrix (Mueller Matrix) describing the diffraction process, and the like.
Further, searching a characteristic spectrum which is best matched with the measured spectrum from the theoretical spectrum database, and determining the structural parameters to be measured of the sample to be measured. In the spectrum matching process, a structural model of the periodic structure of the sample to be detected is established according to the manufacturing process information of the sample to be detected, and the structural model is determined by the structural parameters to be detected. From the principle of light diffraction of periodic structures, the diffraction theory spectrum of a structure model determined by a specific set of structure parameters can be calculated. By varying the parameters of the structural model, there will be different theoretical spectra. In the spectrum matching process, a group of structural parameters to be measured is searched, and the theoretical spectrum and the measured spectrum of the sample to be measured with the morphology of the parameters are optimally matched. Therefore, the actual morphology of the sample to be measured can be represented by the morphology determined by the group of parameters, and the measurement of the structural parameters such as the line width of the sample to be measured is realized.
Let the measured spectrum obtained by the diffractometer be sM(lambda), errors and system noise in the measurement process are not considered, and when the established model is completely consistent with the sample to be measured, the theoretical spectrum can be considereds (x, λ) and the measured spectrum sM(λ) s (x, λ) ═ sM(lambda). Wherein the theoretical spectrum s (x, λ) is obtained by establishing a structural model and calculating using a correlation electromagnetic field theory (such as RCWA), and the measured spectrum sM(λ) can be obtained by diffractometry. If x corresponding to s (x, lambda) can be known, the measurement parameters can be obtained, and the idea is as follows: if an x can be found*＝(x0 *,x1 *,...,xL-1 *)T，xjL-1, its theoretical spectrum s (x)*λ) and the measured spectrum sM(lambda) optimal match, the morphology of the sample to be measured can be determined using the parameter x0 *,x1 *,...,xL-1 *And (5) characterizing.
The matching process describes a basic idea of obtaining structural parameters of a sample to be measured by an OCD measurement method, however, how to make a matching result more accurate, or how to improve sensitivity and signal-to-noise ratio of OCD measurement becomes one of key factors for improving yield of chip manufacturing products and realizing continuous miniaturization of devices with development of the IC industry.
In the optical measurement process, engineers are pursuing high-precision control of system parameters of each OCD measuring device to the utmost extent, and deviation of diffraction light signals collected in measurement due to hardware errors (such as precision limit of moving parts and a precision positioning subsystem) is reduced, however, ideal zero error cannot be realized, and total spectral noise formed by system noise, uncertainty and random error is inevitable. The existence of noise causes the matching degree of the measured spectrum and the theoretical spectrum to be reduced, and causes the fitting value of the obtained structural parameter to be measured to deviate from the true value, and more importantly, the repeatability and the accuracy of industrial measurement are influenced.
Due to differences in semiconductor manufacturing processes and structural changes of devices to be measured, it is generally difficult to consider sensitivity differences of spectral signals at various wavelengths in a system parameter design process of a common OCD measuring device. In the evaluation process of matching the measured spectrum and the theoretical spectrum, the weights of all wavelength points participating in matching are used to adopt a non-difference matching mode, so that the improvement of sensitivity, signal-to-noise ratio and measurement result accuracy is restricted. According to the structure and the used materials of each specific device to be tested, sensitivity analysis is carried out on the spectral signals at each wavelength point, optimization is carried out in spectral matching and evaluation operation based on the sensitivity of each wavelength point one by one, weight coefficients are set for the spectral signals of each wavelength point participating in matching in a targeted mode, and the signal-to-noise ratio and the accuracy of measurement results can be effectively improved.
Disclosure of Invention
The OCD measuring device used in the semiconductor industry at present does not consider the wavelength-based sensitivity and noise difference of diffraction signals at different wavelengths when matching the measured spectrum with the theoretical spectrum, and in the environment configuration for calculating the theoretical spectrum, the spectrum matching in the wavelength dimension usually adopts an undifferentiated weight setting mode. The matching processing mode without weight difference at different wavelengths is used as an evaluation means, and is not beneficial to improving the reliability of the parameter fitting value of the structure to be measured and the accuracy of the measurement result. The invention aims to solve the problem that on the premise of established accuracy of system hardware, the accuracy of a measurement result is improved according to the structure and the used material of each specific device to be measured.
According to a first aspect of the present invention, there is provided a method of improving spectral curve matching reliability and measurement accuracy in an OCD measurement device, comprising the steps performed by the OCD measurement device of: acquiring spectral data of a nominal value and a neighboring value of a structural parameter of a simulation model of a corresponding sample to be measured at each measurement wavelength point to form a theoretical spectral database; carrying out sensitivity analysis on the theoretical spectra of all the wavelength points of each structural parameter to be detected and obtaining the sensitivity distribution of each structural parameter to be detected along with the wavelength; normalizing the sensitivity of each structural parameter to be measured along with the wavelength distribution and acquiring the normalized sensitivity along with the wavelength distribution; setting a systematization weight coefficient according to the attention degree of a user to the structural parameter to be detected and the influence degree of the structural parameter to be detected on the electrical characteristics of a final device and the product yield, carrying out systematization processing on the normalized sensitivity along with wavelength distribution, and acquiring the systematized sensitivity along with the wavelength distribution; according to the unified sensitivity distribution along with the wavelength, setting a matching weight coefficient at each wavelength point in the matching process of the theoretical spectrum and the corresponding measured spectrum and calculating the signal offset of the theoretical spectrum and the measured spectrum; and carrying out evaluation optimization operation on the theoretical spectrum and the corresponding measured spectrum and judging the matching degree of the theoretical spectrum and the measured spectrum.
Advantageously, the method further comprises: establishing the simulation model according to the material and structure information of a sample to be measured, and setting the structural parameters to be measured of the simulation model and configuring the nominal values of the optical parameters of the OCD measuring equipment; calculating spectral data of each wavelength point corresponding to the set combination parameters; and forming the theoretical spectrum database together according to the theoretical spectra formed by connecting the spectral data of each wavelength point.
Advantageously, the to-be-measured structure parameters of the simulation model include indexes for measuring the size and the appearance of the structure of the to-be-measured sample by using the OCD measuring equipment in the semiconductor manufacturing process and controlling related processes; the nominal values of the optical parameters include the spectral type, the averaged setting of the numerical aperture, the wavelength range and discrete wavelength sampling points, the slice division mode and precision, the convergence analysis order, and the combination of the incident angle and the azimuth angle.
Advantageously, in the sensitivity analysis of the structural parameters of the structure to be measured, the sensitivity formula is defined as follows:
wherein, Parameter is the nominal value of a certain structural Parameter, and can also be symbolized as xj；
Δ Parameter is a floating variation introduced for the nominal value of the corresponding structural Parameter, i.e., Δ xjThus, there are:
signal is a Signal value of a certain type of spectrum in a certain waveband range; Δ Signal is a nominal value x of a structural parameterjCauses an overall spectral signal shift in this band of wavelengths, which can be determined by the nominal value x of the structural parameterjIs a floating variation amount deltaxjThe spectral signal shift amounts caused at the selected whole wavelength points are obtained by statistical processing.
Meanwhile, Δ S (x, Δ x) is definedj,λi) Nominal value x representing a structural parameterjAt a certain wavelength point λiA spectral signal offset at (i ═ 1.. times, N). The following formula:
ΔS(x,Δxj,λi)＝s(x,Δxj,λi)-s(x,0,λi)
wherein, s (x, Δ x)j,λi) Representing structural parameters based on their nominal values xjFloating Δ xjAt wavelength point λiProcessing the generated spectral data, and taking corresponding nominal values of other structural parameters; s (x,0, λ)i) Representing a structural parameter as its nominal value xjAt wavelength point λiSpectral data generated at the point of wavelength λ when the overall structural parameters take their nominal valuesiThe spectral data generated.
In general, Δ Signal processes the spectral variation value of the selected measurement band by means of root mean square error calculation, N represents the number of wavelength points included in the selected band, and λi(i ═ 1.. times.n), binding pair Δ S (x, Δ x, N), and binding pair Δ S (x, Δ x, N)j,λi) The definition of (A) is as follows,
correspondingly, the nominal value x of a certain structural parameter to be measured at each wavelength pointjSensitivity of (2)The following can be defined:
normalized sensitivity of a single structural parameter to be measured at each wavelength pointThe following can be defined:
advantageously, said sensitivity analysis comprises the calculation of said nominal value x of said structural parameter to be measured of said simulation model from said theoretical spectral databasejAnd the signal offset at each wavelength point between the theoretical spectra corresponding to the adjacent values, taking the Fourier coefficient α of polarization state analysis as the spectrum signal type for example, taking the nominal value x of the structural parameter to be measuredjUnder the condition that other structural parameters to be measured of the simulation model and the optical parameters and other parameters are fixed and unchanged, calculating the floating variation delta x of the structural parameters to be measured at each wavelength pointjCorresponding Δ S (x, Δ x)j,λi)，λi(i ═ 1.., N), where λiI is the wavelength at the point i, the wavelength point index.
Advantageously, said Δ S (x, Δ x)j,λi) Is calculated by the formula
Wherein x represents each structural parameter to be measured related to the simulation model in general, and xj(j is more than or equal to 0 and less than or equal to L-1) represents a nominal value of the structural parameter to be detected, j is the index of the structural parameter to be detected, and delta S+(x,Δxj,λi) And Δ S-(x,Δxj,λi) Respectively, at a wavelength point λiAt x respectivelyjChange + Δ x on the basis ofjAnd- Δ xjTime, calculated spectral intensity difference, Δ xjRepresents said xjα and β are polarization state analysis fourier coefficients that represent a typical spectral type.
Advantageously, the step of obtaining the sensitivity distribution over wavelength for each structural parameter to be measured further comprises calculating a sensitivity definition at each wavelength pointAnd said Δ S (x, Δ x)j,λi) The calculation formula of (2) calculates the sensitivity of each structural parameter to be measured at each wavelength point and obtains the distribution of the sensitivity of each structural parameter to be measured along with the wavelength point; defining sensitivity according to the contribution of the whole wavelength points to the defined full bandAnd said formulaTo obtain the sensitivity of the structural parameter to be measured in the defined full-band considering the contribution of all wavelength pointsWherein λi(i 1.. N) is the wavelength at point i, i is the wavelength point index, xjAnd (j is more than or equal to 0 and less than or equal to L-1) represents a nominal value of the structural parameter to be detected, j is the index of the structural parameter to be detected, and N is the total number of wavelength points.
Advantageously, said normalization process comprises a function of a formulaAnd acquiring the normalized sensitivity along with the wavelength distribution.
Advantageously, said normalization processing comprises a step of basing said normalized sensitivity of each of said structural parameters to be measured on a wavelength distribution according to said normalization weighting coefficientsCombined into said unified sensitivity profile with wavelength, w1,w2,...wnThe normalized sensitivity respectively representing the structural parameter to be measured is distributed at a wavelength point lambda along with the wavelengthiThe normalized weight coefficient of (b), whereiIs the wavelength at the point i, i is the wavelength point index.
Advantageously, Δ S (Sp) is defined here as the spectral type, for example taking Fourier coefficients α and β for polarization state analysisSimulate,SpMeasure,λi) Denotes at a certain wavelength point λiA signal offset between the theoretical spectrum and the measured spectrum at (i 1...., N). The following formula:
the signal offset of the theoretical spectrum and the measured spectrum when the contribution of all wavelength points is considered in the full waveband is as follows:
wherein SpSimulateRepresents the theoretical spectrum (corresponding to Signal, supra), SpMeasureRepresents the measured spectrum, whereiI is the wavelength at the point i, the wavelength point index.
Advantageously, said evaluation optimization operation further comprises a systematic sensitivity value SSt corresponding to each wavelength pointTotal(λi) The matching weight coefficient that is a contribution of each wavelength point to the reliability of spectral matching.
Advantageously, said evaluation optimization operation further comprises, at each of said wavelength points λiCalculating the signal offset of the theoretical spectrum and the corresponding measured spectrum and the wavelength point lambdaiThe matching weight coefficient SStTotal(λi) Sum of products divided by the matching weight coefficient SStTotal(λi) Sum ofSuch as
Wherein Δ S (Sp)Simulate,SpMeasure,λi) Representing said theoretical spectrum and a corresponding measured spectrum at said wavelength point λiSignal offset of (Sp)SimulateRepresents the theoretical spectrum (corresponding to Signal, supra), SpMeasureRepresents the measured spectrum, whereiIs the wavelength at the i point, i is the wavelength point index, N is the total number of wavelength points, SStTotal(λi) Is the matching weight coefficient.
Advantageously, said evaluation optimization operation further comprises, at each of said wavelength points λiTo calculate
Wherein SpMeasure(λi) Representing said measured spectrum at said wavelength point λiThe value of the spectral intensity ofiFor the wavelengths at the i point, i is the wavelength point index, N is the total number of wavelength points Sp is defined, taking Fourier coefficients α and β of polarization state analysis as examples of spectral typesMeasure(λi) Is composed of
Advantageously, the method further comprises acquiring the measurement spectrum according to a spectral measurement mode.
Advantageously, the spectral measurement mode is composed of a spectral type and system parameters of the OCD measurement device, including an incident angle, an azimuth angle, and the like; the spectrum types include analyzable ellipsometry spectrum, reflection spectrum, Mueller matrix and the like. The parameters of the spectrum type comprise a reflectivity parameter, a polarization state change parameter, a Fourier coefficient for polarization state analysis and a Mueller matrix for expressing a diffraction process.
Advantageously, the controllable measurement accuracy can be calculated from the sensitivity analysis in the respective incident mode.
According to a second aspect of the present invention there is provided an OCD measurement device for carrying out the method of embodiments of the first aspect hereinbefore described.
And based on the structural model of the sample to be detected and different structural parameters to be detected, performing sensitivity analysis on all wavelength points one by one in the selected full waveband, and performing targeted matching weight coefficient setting on the spectrum matching at different wavelength points with sensitivity difference based on the sensitivity analysis result. Under the condition that the setting conditions of the wave band range, the wavelength point density and the like are not changed when the theoretical spectrum and the measured spectrum of the OCD measuring equipment are matched, the matching weight coefficient of each wavelength point in the spectrum matching process is set in a targeted mode based on the wavelength sensitivity analysis result, system noise is effectively suppressed in the matching process, the signal-to-noise ratio is improved, and the reliability and the accuracy of the obtained structural parameter value to be measured are related to the sensitivity and the matching weight coefficient of the corresponding wavelength. Based on the sensitivity and the system noise difference at different wavelength points, the matching weight coefficients of the spectrum signal intensities at different wavelength points are organically set, so that the accuracy of the measurement result of the OCD measuring equipment can be improved, and the process control capability is finally improved.
Drawings
The invention will be better understood and other objects, details and advantages thereof will become more apparent after a description of specific embodiments thereof has been given by reference to the following drawings. In the drawings:
FIG. 1 shows a schematic structural diagram of a polysilicon sample to be tested;
FIG. 2 is a flow chart diagram illustrating a measurement method of OCD measurement technique;
FIG. 3 is a flow chart illustrating optimization of a spectral matching process and improvement of accuracy of fit values of parameters of a structure under test based on sensitivity analysis;
FIG. 4 shows selected parameters of a structure under testSensitivity profile with wavelength;
FIG. 5 shows a normalized sensitivity versus wavelength profile of a selected structure parameter to be measured;
FIG. 6 shows a generalized sensitivity versus wavelength profile (w) of a selected structure parameter to be measured1＝w2＝w31); and
FIG. 7 shows selected parameters of a structure under testNormalized sensitivity versus wavelength profile (w)1＝30,w2＝2,w3＝2)。
Wherein like or similar reference numerals refer to like, similar or corresponding features or functions throughout the several views.
Detailed Description
As required, detailed embodiments of the present invention are disclosed herein. However, it is to be understood that the disclosed embodiments are merely exemplary of the invention, which may be embodied in various forms. Therefore, specific details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present invention in virtually any appropriately detailed manner, including employing various features disclosed herein in combination with features that may not be explicitly disclosed herein.
In the following detailed description of the preferred embodiments, reference is made to the accompanying drawings which form a part hereof. The accompanying drawings illustrate, by way of example, specific embodiments in which the invention may be practiced. The illustrated embodiments are not intended to be exhaustive of all embodiments according to the invention. It should be noted that although the steps of methods of the present invention are depicted in the drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results, but rather that the steps described herein can be performed in an order that varies. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
According to the invention, the matching weight coefficients of the spectral signals at different wavelengths in the matching process of the OCD measuring equipment in the spectral matching process can be optimally designed through sensitivity analysis of each structural characteristic of the sample to be measured, the signal-to-noise ratio of the equipment and the accuracy of the fitting numerical value of the structural parameter to be measured are improved, and the improvement of the on-line measuring accuracy and the monitoring requirement on the process parameter are realized under the existing hardware accuracy condition.
Fig. 1 shows a schematic structural diagram of a polysilicon sample to be tested, and the structure shown in the diagram is taken as an example to realize sensitivity analysis of the parameters of the structure to be tested one by one in the set full-area wavelength range, and based on the wavelength sensitivity analysis result, matching weights of a measured spectrum and a theoretical spectrum are organically set to realize optimization of spectrum matching and finally improve the accuracy of the parameter fitting value of the structure to be tested. The sidewall angle swa (side Wall angle), height ht (height), and critical dimension cd (critical dimension) shown in the figure are the structural parameters to be measured of the sample to be measured.
Fig. 2 is a flow chart showing a measurement method of the OCD measurement technique. As shown in fig. 2, in step B100, a simulation model of the periodic structure of the sample to be measured is established according to the process information of the sample to be measured, and configuration environment parameters to be subjected to theoretical spectrum calculation are set, including a spectrum type, a wavelength range, the number of wavelength points, a convergence order, slice division of a geometric structure, averaging of the diameters of the number holes, whether the wavelength is associated with the incident angle AOI, and the like. The simulation model is determined by the material and structure information of the sample to be tested, i.e. as described in steps S100 and S200 in fig. 3.
In step B200, sensitivity analysis is performed on the geometric parameters, optical parameters, and spectral wavelengths of the sample to be tested, and also targeted matching weight coefficient analysis is performed on the spectral matching at different wavelength points with sensitivity differences, and the specific matching weight coefficient analysis process is as described in steps S300 to S700 in fig. 3.
In step B300, the OCD measuring device determines the value range of the structural parameter to be measured and verifies the applicability of the simulation model. If the matching degree of the structural parameters to be measured and (or) the curve does not meet the predefined requirement, the geometric parameter modeling is carried out again until the predefined requirement is met; and if the range of the structural parameter to be measured is reasonable and the matching degree of the spectral curve meets the preset requirement, the step B400 is carried out, namely, a theoretical spectral database is calculated and established.
Then, in step B500, the theoretical spectrum and the measured spectrum are subjected to matching analysis to obtain a measurement result.
Fig. 3 shows a flow chart for optimizing the spectrum matching process and improving the accuracy of the fitting value of the parameter of the structure to be measured based on sensitivity analysis. Although the following description uses a sensitivity-versus-wavelength curve to represent various sensitivity analyses at all wavelength points, the present invention is not limited to the use of a sensitivity-versus-wavelength curve to represent various sensitivity analyses at all wavelength points, and may be represented, for example, as a function of sensitivity-versus-wavelength or in any other suitable manner.
Before establishing a theoretical spectral database, an engineer usually performs general optimization analysis, that is, for a specific structure model to be measured, through system noise analysis, an optimal combination of a spectral pattern, an incident angle AOI and an azimuth angle phi is found, and optimal controllable measurement accuracy of the structure parameter to be measured under an optimized condition is predicted. And comparing the predicted precision value of the structural parameter to be measured with the tolerance of the structural parameter to be measured provided by the customer, so that whether the measurement system meets the requirement of process control can be measured, and the measurement system is improved in a targeted manner.
And setting a floating range for the structural parameter to be measured based on the selected better sensitivity measurement mode, and calculating to obtain a theoretical spectral curve. Calculating the corresponding delta Signal (lambda) of controllable measurement precision (such as delta CD) at each wavelength point by taking the nominal value of the structural parameter to be measured as the centeri) And further calculating the sensitivity of each wavelength, setting a matching weight coefficient of the spectrum at each wavelength point in the matching evaluation based on the wavelength sensitivity analysis (in the embodiment, the deviation of the signal intensity of the theoretical spectrum and the corresponding measured spectrum and a matching merit value are used as evaluation modes), and enhancing the reliability and the accuracy of the fitting result of the geometric structure parameters.
In step S100, the OCD measuring device establishes a simulation model according to the material and structure information of the sample to be measured, sets the structural parameters to be measured of the simulation model and configures the nominal values of the optical parameters of the OCD measuring device, and sets the proximity values thereof according to the nominal values.
The structural parameters to be measured of the simulation model comprise indexes of measurement and related process control of the size and the appearance of the structure of a sample to be measured by using OCD measuring equipment in the semiconductor manufacturing process; the nominal values of the optical system parameters include the spectrum type, the averaging setting of the numerical aperture, the wavelength range and number of wavelength points, the slice division mode and precision, the convergence analysis order, and the combination of the incident angle and the azimuth angle. It will be appreciated by those skilled in the art that the nominal values of the optical system parameters may also include other necessary parameters in addition to the above parameters.
In step S200, the OCD measuring device calculates the spectrum data of the nominal value of the structural parameter to be measured and the neighboring value thereof corresponding to the simulation model at each wavelength point, and the OCD measuring device forms the theoretical spectrum database together according to the theoretical spectra formed by connecting the spectrum data at each wavelength point.
In step S300, the OCD measurement device performs sensitivity analysis on the theoretical spectra of all the wavelength points of each structural parameter to be measured and obtains a sensitivity-to-wavelength distribution curve of each structural parameter to be measured.
Calculating signal offset between the nominal value of the structural parameter to be measured of the simulation model and the theoretical spectrum of the adjacent value according to the theoretical spectrum database by OCD measuring equipment, taking Fourier coefficient α of polarization state analysis as a spectrum signal type for example, calculating floating variation delta x of the nominal value of each structural parameter to be measured at each wavelength point under the structural parameter to be measured and the optical system parameter of the simulation model by taking the nominal value of the structural parameter to be measured as the centerjCorresponding Δ S (x, Δ x)j,λi)，λi(i ═ 1.., N), where λiI is the wavelength at the point i, the wavelength point index. The skill of the artIt will be understood by the skilled person that Δ S (x, Δ x) is calculatedj,λi) Other necessary parameters besides the structural parameters to be measured and the optical system parameters may also be included.
Advantageously, said Δ S (x, Δ x)j,λi) Is calculated by the formula
Wherein x represents each structural parameter to be measured related to the simulation model in general, and xj(j is more than or equal to 0 and less than or equal to L-1) represents a nominal value of the structural parameter to be detected, j is the index of the structural parameter to be detected, and delta S+(x,Δxj,λi) And Δ S-(x,Δxj,λi) Respectively, at a wavelength point λiAt x respectivelyjChange + Δ x on the basis ofjAnd- Δ xjTime, calculated spectral intensity difference, Δ xjRepresents said xjα and β are fourier coefficients of polarization state analysis that represent one of the spectral types.
Δ S (x, Δ x) calculated according to the formula (1) and the formula (2)j,λi) And calculating the sensitivity definition formula (3) of each wavelength point, and calculating the lambda of the structural parameter to be measured at each wavelength pointiThe sensitivity values are as follows:
and substituting the specific structural parameters CD, SWA and HT to be detected into a formula (3) to obtain:
wherein SSt in the formula (4)CD(λi)，SStSWA(λi) And SStHT(λi) Respectively represent at each wavelength point lambdaiAnd (3) sensitivity of three structural parameters to be tested, namely CD, SWA and HT.
Respectively calculating the lambda of each wavelength point according to the three structural parameters to be measured corresponding to the formulaiThe sensitivity of (A) can be obtained as shown in FIG. 4Sensitivity profile with wavelength point.
Definition of sensitivity based on consideration of the contribution of the whole set of wavelength points to the defined full bandAnd the aforementioned formulaTo obtain the sensitivity of the structural parameter to be measured in a defined full band taking into account the contributions of all the wavelength points, where λi(i 1.. N) is the wavelength at point i, i is the wavelength point index, xjAnd (j is more than or equal to 0 and less than or equal to L-1) represents a nominal value of the structural parameter to be detected, j is the index of the structural parameter to be detected, and N is the total number of wavelength points.
Therefore, combining equations (3) and (4) and the above definition of sensitivity for the full band, one can obtainAnd substituting the symbols of the three structural parameters to be measured, namely CD, SWA and HT into the symbols to obtain:
wherein,SensitivityCD，SensitivitySWAand SensitivityHTAnd the sensitivity of comprehensively counting the spectrum signals at all the wavelength points when the contribution of all the wavelength points is comprehensively considered is respectively expressed by the whole spectrums corresponding to the three structural parameters to be measured.
The sensitivity values of different structural parameters to be measured generally have larger difference along with the wavelength distribution curve. As shown in fig. 4In the profile, the sensitivity of CD is significantly better than SWA. Meanwhile, the sensitivity difference of each structural parameter to be measured at different wavelengths is different. In the OCD technology, when the spectrum matching is completed, all structural parameter values to be measured are fitted at the same time. At this time, how to simultaneously face a plurality of structural parameters to be measured is to quantitatively set weights for spectrum matching and matching evaluation of each wavelength point organically according to the interest and attention degree of users to different structural parameters to be measured and considering sensitivity distribution difference of all structural parameters simultaneously, which is a problem to be solved in the following steps.
In step S400, in the full-band spectral range, the sensitivity-wavelength-dependent curve of each structural parameter to be measured is normalized and a normalized sensitivity-wavelength-dependent curve is obtained.
An effective and well-defined method is: firstly for different structural parameters to be measuredThe distribution curves were normalized. The sensitivities of different structural parameters to be measured after normalization processing are relatively close in value, in this embodiment, three structural parameters to be measured, namely CD, SWA and HT, are respectively corresponding, and three pieces of normalized sensitivity values which are different in wavelength distribution but close in value level can be obtained through calculationA distribution curve.
Based on the above, the sensitivity distribution curve with wavelength pointPerforming a normalization process, i.e. based on
The sensitivity data of each wavelength point is normalized, and three different structural parameters to be measured related to the invention can be obtained according to a formula (7)
Wherein,andrespectively, at a wavelength point λiAnd (3) normalized sensitivity of three structural parameters to be detected, namely CD, SWA and HT. And three normalized sensitivity vs. wavelength profiles were plotted as shown in figure 5.
In step S500, according to the attention degree of the user to the structural parameter to be measured and the influence degree of the structural parameter to be measured on the electrical characteristics of the final device and the product yield, setting a normalization weight coefficient, performing normalization processing on the normalized sensitivity curve distributed along with the wavelength, and acquiring a normalized sensitivity curve distributed along with the wavelength;
the three normalized sensitivity vs. wavelength profiles shown in fig. 5 are combined into one based on equation (8) by a normalization process based on a mathematical equation:
wherein, w1,w2,w3Respectively representAndfor SStTotal(λi) The contribution normalized weight coefficient. In general, the attention degree and the interest degree of the default user to the whole structural variables to be measured are the same, namely w1＝w2＝w3In the case of 1, "SSt" as shown in fig. 6 can be plottedTotal(λi)～λi”(w1＝w2＝w3Distribution curve of 1).
However, in the actual semiconductor manufacturing process, multiple products and multiple processes are involved, different processes of different products involve monitoring different process structures and parameters of multiple structures to be tested, and the performance of different parameters of the structures to be tested has different effects on the electrical characteristics and product yield of the final device, so that the interest level and the emphasis of users on different parameters of the structures to be tested involved in the processes are different, such as the accuracy requirement of CD is generally higher and stricter, and accordingly, in the OCD measurement process, the W can be changed1,w2,w3The sensitivity of the matching process to CD is emphasized.
For example, when taking w1＝30,w2＝2,w3When the value is 2, the normalized sensitivity-dependent distribution curve of three structural parameters to be measured, namely CD, SWA and HT, is represented by the following formula (9):
accordingly, take w1＝30,w2＝2,w3"SSt" under 2 conditionsTotal(λi)～λi"the intensity of the sensitivity curve (as shown in FIG. 7) varies with the wavelength distribution, and the curve shape is different from that of FIG. 6
(w1＝w2＝w31) and the distribution in fig. 5, respectivelyThe shapes are very close, and the normalized weight coefficient of the CD is far larger than that of other structural parameters to be measured.
In step S600, according to the normalized sensitivity versus wavelength profile, a matching weight coefficient is set at each wavelength point in the matching process of the theoretical spectrum and the measured spectrum, and a signal offset of the theoretical spectrum and the measured spectrum is calculatedSimulate,SpMeasure,λi) Denotes at a certain wavelength point λiA signal offset between the theoretical spectrum at (i 1.. cndot., N) and the corresponding measured spectrum. The following formula:
the signal offset of the theoretical spectrum and the corresponding measured spectrum when the contribution of all wavelength points is considered in the full waveband is as follows:
wherein SpSimulateRepresents the theoretical spectrum, SpMeasureRepresents the measured spectrum, whereiI is the wavelength at the point i, the wavelength point index.
In step S700, an evaluation optimization operation is performed on the theoretical spectrum and the measured spectrum, and a matching degree between the theoretical spectrum and the measured spectrum is determined.
Specifically, one representative evaluation optimization operation is described, and the unified sensitivity value SSt corresponding to each wavelength point can be obtained by respectively counting the contribution of the sensitivity of each wavelength point to the accuracy of the fitting value of the structural parameter to be measuredTotal(λi) As a matching weight coefficient, the spectral signal contributes to the matching of the whole curve at each wavelength point. I.e. at each of said wavelength points λiCalculating the signal offset and wavelength point lambda of the theoretical spectrum and the measured spectrumiThe matching weight coefficient SStTotal(λi) Sum of products divided by the matching weight coefficient SStTotal(λi) Sum ofAs in formula (12)
Wherein,. DELTA.S (Sp)Simulate,SpMeasure,λi) Signal offset, Sp, representing the theoretical spectrum from the measured spectrumSimulateRepresenting the theoretical spectrum (corresponding to Signal), SpMeasureRepresents the corresponding measured spectrum, whereiIs the wavelength at the i point, i is the wavelength point index, N is the total number of wavelength points, SStTotal(λi) Is the matching weight coefficient.
In addition, the GOF (goodness of fit) of goodness of fit can also be used as another evaluation optimization operation, namely, as the formula (13)
Wherein, f1Optimization(SpSimulate,SpMeasure) Is according to the meter in the formula (12)And (4) obtaining the result through calculation. f1Optimization(SpSimulate,SpMeasure) The smaller the value of (a) indicates the higher the degree of matching between the measured spectrum and the theoretical spectrum. f2Optimization(SpSimulate,Spmeasure) A larger value of (a) indicates a higher degree of matching between the measured spectrum and the theoretical spectrum. The evaluation optimization operation is carried out by adopting the formula (12) or the formula (13), so that the system noise level determined by the action process depending on the spectrum type and the light and the structural parameter to be measured can be effectively reduced, the obtained fitting result is more accurate, and the reliability and the stability are extremely high.
The methods disclosed herein are described herein with reference to the accompanying drawings. It should be understood, however, that the order of steps shown in the drawings and described in the specification is merely exemplary, and that the method steps and/or actions may be performed in a different order and are not limited to the specific order shown in the drawings and described in the specification without departing from the scope of the claims.
The previous description of the disclosure is provided to enable any person skilled in the art to make or use the present invention. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the present invention is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (14)
1. A method of improving spectral profile matching reliability and measurement accuracy in an OCD measurement device, comprising the following steps performed by the OCD measurement device:
acquiring spectral data of a nominal value and a neighboring value of a structural parameter to be measured of the simulation model at each wavelength point to form a theoretical spectral database;
carrying out sensitivity analysis on the theoretical spectra of all the wavelength points of each structural parameter to be detected and obtaining the sensitivity distribution of each structural parameter to be detected along with the wavelength;
normalizing the sensitivity of each structural parameter to be measured along with the wavelength distribution and acquiring the normalized sensitivity along with the wavelength distribution;
setting a systematization weight coefficient according to the attention degree of a user to the structural parameter to be detected and the influence degree of the structural parameter to be detected on the electrical characteristics of a final device and the product yield, carrying out systematization processing on the normalized sensitivity along with wavelength distribution, and acquiring the systematized sensitivity along with the wavelength distribution;
according to the unified sensitivity distribution along with the wavelength, setting a matching weight coefficient at each wavelength point in the matching process of the theoretical spectrum and the measured spectrum and calculating the signal offset between the theoretical spectrum and the measured spectrum; and
and carrying out evaluation optimization operation on the theoretical spectrum and the measured spectrum and judging the matching degree of the theoretical spectrum and the measured spectrum.
2. The method of claim 1, further comprising:
establishing the simulation model according to the material and structure information of a sample to be measured, and setting the structural parameters to be measured of the simulation model and configuring the nominal values of the optical system parameters of the OCD measuring equipment;
the theoretical spectra formed from the spectral data sets for each of the wavelength points collectively form the theoretical spectral database.
3. The method of claim 2, wherein the structure parameters to be tested of the simulation model include dimensions and topography of the sample structure to be tested and indicators of related process controls; the nominal values of the optical system parameters include the spectrum type, the averaging setting of the numerical aperture, the wavelength range and the number of wavelength points, the slice division mode and precision, and the convergence analysis order and the combination of the incident angle and the azimuth angle.
4. The method of claim 1, wherein the sensitivity analysis comprises:
calculating the integral signal offset between the nominal value of the structural parameter to be measured of the simulation model and the theoretical spectrum of the adjacent value, which accounts for the contribution of all wavelength points contained in the selected waveband, according to the theoretical spectrum database; and calculating the nominal value x of each structural parameter to be measured at each wavelength point under the conditions of the structural parameter to be measured and the optical system parameter of the simulation model by taking the nominal value of the structural parameter to be measured as the centerjIs a floating variation amount deltaxjCorresponding spectral signal offset Δ S (x, Δ x)j,λi) Wherein λ isiI is the wavelength at the point i, the wavelength point index.
5. The method of claim 4, wherein Δ S (x, Δ x)j,λi) Is calculated by the formula
Wherein x represents each structural parameter to be measured related to the simulation model in general, and xjRepresents a nominal value of the structural parameter to be measured, j is the index of the structural parameter to be measured and is more than or equal to 0 and less than or equal to L-1, wherein lambda isiIs the wavelength at the point i, i being the index of said wavelength point, Δ S+(x,Δxj,λi) And Δ S-(x,Δxj,λi) Respectively, at a wavelength point λiAt xjChange + Δ x on the basis ofjAnd- Δ xjTime, calculated spectral intensity difference, Δ xjRepresents said xjα and β are fourier coefficients of polarization state analysis, which represent the spectral type.
6. The method of claim 1, wherein the step of obtaining the sensitivity distribution over wavelength for each structural parameter to be measured further comprises:
definition of sensitivity at each wavelength point from a calculated spectral signalAnd said Δ S (x, Δ x)j,λi) The sensitivity of each structural parameter to be measured at each wavelength point is calculated and the distribution of the sensitivity of each structural parameter to be measured along with the wavelength point is obtained, wherein, delta xjNominal value x representing a structural parameter to be measuredjJ is the index of the structural parameter to be measured, lambdaiThe wavelength at the point i is the index of the wavelength point, and x generally represents each structural parameter to be measured related to the simulation model; and
according toTo obtain the sensitivity of the structural parameter to be measured in calculating the contributions of all the wavelength points of the selected band, where λiIs the wavelength at the point i, i is the wavelength point index, xjAnd j represents a nominal value of the structural parameter to be detected, j is an index of the structural parameter to be detected, j is more than or equal to 0 and less than or equal to L-1, and N is the total number of wavelength points.
7. The method of claim 1, wherein the normalization process comprises:
according toAnd acquiring the normalized sensitivity along with the wavelength distribution.
8. The method of claim 1, wherein the unifying comprises
According to the normalized weight coefficient, the normalized sensitivity of each structural parameter to be measured is distributed along with the wavelength according to the normalized weight coefficient
Combined into said unified sensitivity profile with wavelength, w1,w2,...wnThe normalized sensitivity respectively representing each structural parameter to be measured is distributed at a wavelength point lambda along with the wavelengthiThe normalized weight coefficient of (b), whereiIs the wavelength at the point i, i is the wavelength point index.
9. The method of claim 1, wherein the theoretical spectrum is offset from the measured spectrum by a signal based on
Is calculated, wherein Δ S (Sp)Simulate,SpMeasure,λi) Signal offset, Sp, representing the theoretical spectrum from the measured spectrumSimulateRepresents the theoretical spectrum, SpMeasureRepresents the measured spectrum, whereiFor the wavelength at the i-point, i is the wavelength point index, α and β are the Fourier coefficients of polarization state analysis, which represent the spectral type.
10. The method of claim 1, wherein the evaluation optimization operation further comprises assigning a normalized sensitivity value SSt to each wavelength pointTotal(λi) The matching weight coefficient that is a contribution of each wavelength point to the reliability of spectral matching.
11. The method of claim 1, wherein said evaluation optimization operation further comprises λ at each of said wavelength pointsiCalculating the signal offset of the theoretical spectrum and the measured spectrum and the wavelength point lambdaiThe matching weight coefficient ofSum of products divided by the matching weight coefficient SStTotal(λi) Sum of
Wherein Δ S (Sp)Simulat,eSpMeasu,reλi) Signal offset, Sp, representing the theoretical spectrum from the measured spectrumSimulateRepresents the theoretical spectrum, SpMeasureRepresents the measured spectrum, whereiIs the wavelength at the i point, i is the wavelength point index, N is the total number of wavelength points, SStTotal(λi) Is the matching weight coefficient.
12. The method of claim 11, wherein said evaluation optimization operation further comprises λ at each of said wavelength pointsiTo calculate
Wherein SpSimulateRepresents the theoretical spectrum, SpMeasure(λi) Represents the measured spectrum, whereiDefining Sp as the wavelength at the i point, i as the wavelength point index, N as the total number of wavelength points, taking Fourier coefficients α and β of polarization state analysis as the spectrum type as an exampleMeasure(λi) Is composed of
13. The method of claim 1, further comprising acquiring the measurement spectrum according to a spectral measurement mode.
14. The method of claim 13, wherein the spectral measurement mode consists of a spectral type and system parameters of an OCD measurement device, including an angle of incidence and an azimuth angle; the spectrum types comprise an ellipsometric spectrum, a reflection spectrum and a Mueller matrix which can be analyzed, and the parameters of the spectrum types comprise a reflectivity parameter, a polarization state change parameter, a Fourier coefficient for polarization state analysis and a Mueller matrix for representing a scattering process.
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|---|---|---|---|---|
| CN107843190B (en) * | 2016-09-21 | 2020-09-01 | 睿励科学仪器（上海）有限公司 | Optical critical dimension measuring system and method thereof |
| CN108897196A (en) * | 2018-07-11 | 2018-11-27 | 中国科学院微电子研究所 | Method for selecting measuring wavelength in overlay error measurement based on diffraction |
| CN110823089B (en) * | 2018-08-10 | 2021-06-04 | 睿励科学仪器（上海）有限公司 | Method and apparatus for measuring optical critical dimension of semiconductor device |
| US11422095B2 (en) * | 2019-01-18 | 2022-08-23 | Kla Corporation | Scatterometry modeling in the presence of undesired diffraction orders |
| CN113571437B (en) * | 2020-04-28 | 2023-09-08 | 长鑫存储技术有限公司 | Semiconductor device measuring method |
| CN111595812B (en) * | 2020-05-29 | 2021-06-22 | 复旦大学 | Measurement method and system of key parameters based on momentum space dispersion relation |
| CN111637849B (en) * | 2020-05-29 | 2021-11-26 | 上海精测半导体技术有限公司 | Method, device and equipment for measuring morphology parameters |
| CN111879236B (en) * | 2020-07-14 | 2021-09-24 | 上海精测半导体技术有限公司 | Method for determining parameters of sample to be measured from theoretical spectrum library and measuring equipment |
| CN113029024B (en) * | 2021-03-01 | 2021-11-16 | 长鑫存储技术有限公司 | Method and apparatus for measuring semiconductor structure |
| US12131111B2 (en) | 2021-03-01 | 2024-10-29 | Changxin Memory Technologies, Inc. | Method, apparatus and device for measuring semiconductor structure |
| CN113295090A (en) * | 2021-04-08 | 2021-08-24 | 睿励科学仪器（上海）有限公司 | Method and device for comparing spectra |
| CN113343182B (en) * | 2021-06-30 | 2024-04-02 | 上海精测半导体技术有限公司 | Optimization method and system of theoretical spectrum data, electronic equipment and measurement method |
| CN115014240B (en) * | 2022-07-14 | 2024-12-13 | 上海精测半导体技术有限公司 | A method for obtaining theoretical spectrum and a method for measuring morphological parameters |
| CN115391726B (en) * | 2022-07-26 | 2023-10-27 | 睿励科学仪器（上海）有限公司 | Fitting optimization method and related device for ellipsometry system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102142061A (en) * | 2010-02-01 | 2011-08-03 | 西门子公司 | Calibration of stream simulation tool and stream model |
| CN102141377A (en) * | 2011-01-30 | 2011-08-03 | 睿励科学仪器（上海）有限公司 | Method for self-defining outline by user in optical critical dimension detection device |
| CN102183212A (en) * | 2010-12-28 | 2011-09-14 | 睿励科学仪器（上海）有限公司 | Method and device for rapidly determining topography parameters of microperiodic structure |
| CN103049605A (en) * | 2012-12-13 | 2013-04-17 | 华中科技大学 | Alignment error extraction method based on Mueller matrix |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2002014840A2 (en) * | 2000-08-10 | 2002-02-21 | Sensys Instruments Corporation | Database interpolation method for optical measurement of diffractive microstructures |
| US7216045B2 (en) * | 2002-06-03 | 2007-05-08 | Timbre Technologies, Inc. | Selection of wavelengths for integrated circuit optical metrology |
| US9310296B2 (en) * | 2011-06-20 | 2016-04-12 | Kla-Tencor Corporation | Optimizing an optical parametric model for structural analysis using optical critical dimension (OCD) metrology |
-
2014
- 2014-05-29 CN CN201410234193.7A patent/CN105444666B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102142061A (en) * | 2010-02-01 | 2011-08-03 | 西门子公司 | Calibration of stream simulation tool and stream model |
| CN102183212A (en) * | 2010-12-28 | 2011-09-14 | 睿励科学仪器（上海）有限公司 | Method and device for rapidly determining topography parameters of microperiodic structure |
| CN102141377A (en) * | 2011-01-30 | 2011-08-03 | 睿励科学仪器（上海）有限公司 | Method for self-defining outline by user in optical critical dimension detection device |
| CN103049605A (en) * | 2012-12-13 | 2013-04-17 | 华中科技大学 | Alignment error extraction method based on Mueller matrix |
Non-Patent Citations (1)
| Title |
|---|
| Xin Wang.etc.OCD Sensitivity Study and Parameter Optimization for Oxide-Nitride Spacer.《ECS Transactions》.2013,第52卷(第1期),889-895页. * |
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