X-ray photoelectron spectroscopy processing method and X-ray photoelectron spectroscopy system

Abstract

The invention relates to the field of X-ray photoelectron spectroscopy detection, and discloses an X-ray photoelectron spectroscopy processing method and an X-ray photoelectron spectroscopy system. The X-ray photoelectron spectroscopy processing method comprises the following steps: receiving X-ray photoelectron spectroscopy data; and filtering the X-ray photoelectron spectroscopy data through a finite impulse response (FIR) filter to obtain filtered X-ray photoelectron spectroscopy data.

Description

Technical Field

[0001] The present disclosure relates to the field of X-ray photoelectron spectroscopy detection, and in particular to an X-ray photoelectron spectroscopy processing method and an X-ray photoelectron spectroscopy system. Background Art

[0002] X-ray photoelectron spectrometers are widely used in industrial measurement. When the instrument parameters are set the same, the photoelectron spectra obtained from different measurements of the same sample will be different. The main reasons for this difference are that the number of photoelectrons received by the detector follows the Poisson distribution, and the output of hardware such as the power supply also has uncertainty. In order to improve the stability of the operation of the X-ray photoelectron spectrometer, there are usually two measures: one is to increase the intensity of the X-ray, but this will reduce the life of the instrument; the other is to extend the spectrum acquisition time, but this will reduce work efficiency. Summary of the invention

[0003] The present disclosure provides a method for processing X-ray photoelectron spectroscopy, comprising:

[0004] receiving X-ray photoelectron spectroscopy data; and

[0005] The X-ray photoelectron spectroscopy data is filtered by a finite impulse response (FIR) filter to obtain filtered X-ray photoelectron spectroscopy data.

[0006] The present disclosure also provides an X-ray photoelectron spectroscopy system, comprising:

[0007] X-ray photoelectron spectrometer, used to collect X-ray photoelectron spectroscopy data; and

[0008] A processor is communicatively connected to the X-ray photoelectron spectrometer, and the processor is configured to execute the X-ray photoelectron spectrum processing method according to any one of the embodiments of the present disclosure to filter the X-ray photoelectron spectrum data collected by the X-ray photoelectron spectrometer to obtain filtered X-ray photoelectron spectrum data.

[0009] The present disclosure also provides a computer device, comprising:

[0010] A memory for storing at least one instruction; and

[0011] A processor is coupled to the memory and is used to execute at least one instruction to perform the X-ray photoelectron spectroscopy processing method according to any one of the embodiments of the present disclosure.

[0012] The present disclosure also provides a computer-readable storage medium for storing at least one instruction, which, when executed by a computer device, causes the computer to execute the X-ray photoelectron spectroscopy processing method according to any one of the embodiments of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only one embodiment of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0014] Figure 1 An example flow chart of a method for processing X-ray photoelectron spectroscopy according to some embodiments of the present disclosure is shown;

[0015] Figure 2 A logic block diagram of designing a filter according to some embodiments of the present disclosure is shown;

[0016] Figure 3A shows the X-ray photoelectron spectroscopy data before filtering obtained by measuring SiON;

[0017] Figure 3B The X-ray photoelectron spectroscopy processing method and system of some embodiments of the present disclosure are shown. Figure 3A The X-ray photoelectron spectroscopy data shown are X-ray photoelectron spectroscopy data after filtering.

[0018] Figure 4 A schematic diagram of an X-ray photoelectron spectroscopy system according to some embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0019] Some embodiments of the present disclosure will be described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only exemplary embodiments of the present disclosure, rather than all embodiments.

[0020] In the description of the present disclosure, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", "top", "bottom", "horizontal", "longitudinal" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present disclosure. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance. In the description of the present disclosure, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", and "coupled" should be understood in a broad sense, for example, it can be a fixed connection or a detachable connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal connection of two elements. In the description of the present disclosure, the distal end or the distal side refers to an end or a side that penetrates into a vacuum environment (e.g., a vacuum chamber), and the proximal end or the proximal side refers to an end or a side opposite to the distal end or the distal side (e.g., an end or a side that is away from the vacuum chamber, or an end or a side that is close to the vacuum chamber wall in the vacuum chamber, etc.). Alternatively, the end or the side that is close to the driving device is the proximal end or the proximal side, and the end or the side that is away from the driving device is the distal end or the distal side. For those of ordinary skill in the art, the specific meanings of the above terms in the present disclosure can be understood according to specific circumstances.

[0021] Figure 1 An example flow chart of an X-ray photoelectron spectroscopy (XPS) processing method 100 according to some embodiments of the present disclosure is shown. The X-ray photoelectron spectroscopy processing method 100 can be implemented or executed at least in part by hardware, software, or firmware. In some embodiments, the X-ray photoelectron spectroscopy processing method 100 can be at least in part by an X-ray photoelectron spectroscopy system (e.g., Figure 4 In some embodiments, the X-ray photoelectron spectroscopy processing method 100 can be implemented as computer-readable instructions. These instructions can be executed by a general-purpose processor or a special-purpose processor (e.g., Figure 4 The instructions may be read and executed by a processor 320 of the X-ray photoelectron spectroscopy system 300 shown in FIG. 1 . In some embodiments, the instructions may be stored on a computer-readable medium.

[0022] like Figure 1As shown, in some embodiments of the present disclosure, the processing method of X-ray photoelectron spectroscopy may include, at step 110, receiving X-ray photoelectron spectroscopy data. For example, an X-ray photoelectron spectrometer may measure a sample and collect X-ray photoelectron spectroscopy data. X-ray photoelectron spectroscopy data collected by an X-ray photoelectron spectrometer may be received. Those skilled in the art will appreciate that the sample may include various suitable embodiments, such as silicon oxynitride (SiON) samples, aluminum oxide (Al2O3) samples, and the like. 2 O 3 ) samples, titanium nitride (TiN) samples, etc.

[0023] like Figure 1 As shown, in some embodiments of the present disclosure, the method for processing X-ray photoelectron spectroscopy may include, in step 120, filtering the X-ray photoelectron spectroscopy data through a finite impulse response (FIR) filter to obtain filtered X-ray photoelectron spectroscopy data (step 130).

[0024] In some embodiments of the present disclosure, filtering the X-ray photoelectron spectroscopy data by using an FIR filter can take into account both the measurement efficiency and the measurement stability of the X-ray photoelectron spectroscopy, thereby improving the operating stability of the X-ray photoelectron spectrometer without affecting the service life of the X-ray photoelectron spectrometer and without extending the spectrum collection time.

[0025] In some embodiments of the present disclosure, the FIR filter may include N filter coefficients, where N is an integer greater than 1. Filtering the X-ray photoelectron spectroscopy data by the FIR filter (step 120) may include: performing a convolution operation on the N filter coefficients and the X-ray photoelectron spectroscopy data to obtain filtered X-ray photoelectron spectroscopy data.

[0026] In some embodiments of the present disclosure, the X-ray photoelectron spectroscopy data may include M values, where M is an integer greater than N. Convolution operations on N filter coefficients and the X-ray photoelectron spectroscopy data may include: calculating the convolution of the N filter coefficients and the N consecutive values ​​before the k-th value in the X-ray photoelectron spectroscopy data to obtain the k-th filtered value, where k is between 0 and M-1. Those skilled in the art will understand that in the present disclosure, "before" is a numerical interval including the present number. For example, in some embodiments of the present disclosure, the k-th filtered value y(k) may be calculated by formula (1):

[0027] y(k)=h(0)x(k-0)+h(1)x(k-1)+h(2)x(k-2)…+h(N-1)x(k-(N-1)) (1)

[0029] Wherein, in formula (1), h(i) represents the filter coefficient, x(ki) represents the ki-th received X-ray photoelectron energy spectrum value, and y(k) represents the k-th filtered X-ray photoelectron energy spectrum data value, wherein 0≤i≤N-1, 0≤k≤M-1, and i and k are both integers.

[0030] For the M values ​​in the X-ray photoelectron spectroscopy data, the convolution operation can be performed using formula (1) to obtain the corresponding filtered values. For example, y(0) is the 0th filtered value obtained by formula (1) (the first value in the sequence after filtering); y(1) is the first filtered value obtained by formula (1), ..., y(M-1) is the M-1th filtered value obtained by formula (1). M filtered values ​​can be obtained by formula (1): y(0), y(1), ..., y(M-1). Those skilled in the art can understand that, for example, when calculating y(0), padding is required.

[0031] In some embodiments of the present disclosure, X-ray photoelectron spectral data may be subjected to centralized filtering processing. For example, receiving X-ray photoelectron spectral data may include: receiving the values ​​in all X-ray photoelectron spectral data. X-ray photoelectron spectral data may also be stored. Convolution operations on N filter coefficients and X-ray photoelectron spectral data may include: reading X-ray photoelectron spectral data, and calculating the convolution of N filter coefficients and N consecutive values ​​before the k-th value in the X-ray photoelectron spectral data to obtain the k-th filtered value. This centralized filtering processing can be performed in parallel, which can significantly shorten the overall filtering processing time.

[0032] In some embodiments of the present disclosure, X-ray photoelectron spectral data may be subjected to real-time filtering processing. For example, receiving X-ray photoelectron spectral data may include: continuously receiving values ​​in the X-ray photoelectron spectral data. Convolution operation of N filter coefficients with X-ray photoelectron spectral data may include: real-time calculation of the convolution of N filter coefficients with N consecutive values ​​before the k-th value in the X-ray photoelectron spectral data to obtain the k-th filtered value. Real-time filtering processing may be performed in real time during the acquisition process of X-ray photoelectron spectral data, and rapid filtering processing of X-ray photoelectron spectral data may be achieved for subsequent use.

[0033] In some embodiments, formula (1) can be used to centrally or in real time calculate the convolution of N filter coefficients and the N consecutive values ​​before the kth value in the continuously received X-ray photoelectron spectrum data to obtain the kth filtered value, thereby obtaining all the filtered X-ray photoelectron spectrum data. Since the filtered value only depends on the value in the X-ray photoelectron spectrum data continuously received at the previous moment, the processing of the X-ray photoelectron spectrum data can be done in real time, which is convenient for subsequent data processing.

[0034] Figure 2 A logic block diagram 400 for designing a filter according to some embodiments of the present disclosure is shown.

[0035] like Figure 2 As shown, in some embodiments of the present disclosure, N filter coefficients may be determined based on a cutoff frequency and a predetermined order N of the FIR filter (block 450).

[0036] In some embodiments of the present disclosure, the N filter coefficients may be determined based on a cutoff frequency of the FIR filter and a sinc function.

[0037] Performing an inverse Fourier transform on the frequency response of an ideal filter can generate a time domain impulse response of an ideal filter. In order to adapt to computer processing, in some embodiments of the present disclosure, the time domain impulse response of the ideal filter is shifted to the right and the main lobe is used as the symmetry axis and the translation distance is used as the radius, and the ideal time domain impulse response is truncated to obtain a time domain impulse response of a positive index and a finite length. The specific expression is shown in formula (2):

[0038] h(i)=sin(2πf c i) / (πi) (2)

[0039] In formula (2), h(i) represents the filter coefficient, f c represents the cutoff frequency, 0≤i≤N-1, and i is an integer, and N represents the order of the filter. The order N can be preset or determined.

[0040] For example, when the predetermined order N of the filter is an odd number, the time domain impulse response of a finite length with a positive index is as shown in formula (3):

[0041]

[0042] In formula (3), h(i) is the filter coefficient, f c is the cut-off frequency, j=i-(N-1) / 2, 0≤i≤N-1, and i is an integer.

[0043] In some embodiments, because the impulse response of the FIR filter in the X-ray photoelectron spectroscopy processing method is of finite length and there is no feedback, the data processing operation is more stable.

[0044] Since ringing and ripples may appear in the frequency response of the filter, especially near the edge of the frequency band, the performance of the filter after direct truncation is different from that of the ideal filter frequency response. In order to approach the characteristics of the ideal filter with no distortion in the passband and full suppression in the stopband, in some embodiments, the truncated low-pass filter is modified using a Blackman window function. The definition of the Blackman window function is shown in formula (4):

[0045] ω(i)=0.42-0.5cos(2πi / (N-1))+0.08cos(4πi / (N-1)) (4)

[0047] In formula (4), ω(i) represents the Blackman window function, N represents the filter length 0≤i≤N-1, and i is an integer. In the present disclosure, the filter length is equal to the filter order, and both are represented by the letter N in the present disclosure.

[0048] In some embodiments of the present disclosure, the FIR filter is designed to have a linear phase response, and the phase delay of different frequency components when passing through the FIR filter is linear, so signal distortion can be avoided to a large extent.

[0049] like Figure 2 As shown, in some embodiments of the present disclosure, the N filter coefficients are determined based on the cutoff frequency of the FIR filter and the product of the sinc function and the Blackman window function (block 460). For example, the time domain impulse response with a finite length having a positive index shown in formula (2) can be multiplied with the Blackman window function shown in formula (4) to obtain the optimized filter coefficients, as shown in formula (5):

[0050] h(i)=sin(2πf c i) / (πi)·[0.42-0.5cos(2πi / (N-1))+0.08cos(4πi / (N-1))] (5)

[0052] In formula (5), h(i) represents the optimized filter coefficient, f c is the cutoff frequency, N is the order of the filter, 0≤i≤N-1, and i is an integer.

[0053] In some embodiments of the present disclosure, the cutoff frequency of the FIR filter is predetermined based on previous X-ray photoelectron spectroscopy data.

[0054] like Figure 2 As shown, in some embodiments of the present disclosure, the cutoff frequency of the FIR filter is determined based on the difference between the relative standard deviation of the filtered X-ray photoelectron spectrum area and the relative standard deviation of the X-ray photoelectron spectrum area and the simulated standard deviation (block 440).

[0055] In some embodiments, the cutoff frequency of the FIR filter can be determined based on the difference between the relative standard deviation of the area of ​​the filtered X-ray photoelectron energy spectrum and the relative standard deviation of the area of ​​the X-ray photoelectron energy spectrum before filtering being approximately equal to the simulated standard deviation. For example, the cutoff frequency of the FIR filter can be determined based on the difference between the relative standard deviation of the area of ​​the filtered X-ray photoelectron energy spectrum and the relative standard deviation of the area of ​​the X-ray photoelectron energy spectrum before filtering being within an allowable range (e.g., equal to, slightly greater than, or slightly less than) relative to the simulated standard deviation.

[0056] like Figure 2 As shown, in some embodiments of the present disclosure, the simulated standard deviation is determined based on the relative standard deviation of the X-ray photoelectron spectroscopy areas of multiple sets of simulated X-ray photoelectron spectroscopy data generated from previous X-ray photoelectron spectroscopy data (block 430).

[0057] In some embodiments, the simulation standard deviation is the standard deviation of the relative standard deviation of the X-ray photoelectron spectroscopy area of ​​multiple sets of simulated X-ray photoelectron spectroscopy data generated from previous X-ray photoelectron spectroscopy data. For example, the simulation standard deviation can be calculated using the following formula (6):

[0058]

[0059] In formula (6), σ RSD represents the simulation standard deviation, μ represents the mean of the relative standard deviation of the X-ray photoelectron spectral area of ​​multiple sets of simulated X-ray photoelectron spectral data generated by the previous X-ray photoelectron spectral data, y represents the number of groups of simulated X-ray photoelectron spectroscopy data generated from previous X-ray photoelectron spectroscopy data, RSD(sv) y Represents the relative standard deviation of the X-ray photoelectron spectral area of ​​each set of simulated X-ray photoelectron spectral data generated from the previous X-ray photoelectron spectral data, where x is an integer from 1 to y.

[0060] In some embodiments of the present disclosure, the simulated standard deviation is the standard deviation of the relative standard deviation of the X-ray photoelectron energy spectrum areas of multiple groups of simulated X-ray photoelectron energy spectrum data, which can effectively measure the fluctuation level of the X-ray photoelectron energy spectrum. The simulated standard deviation is used to limit the filtering effect, which can not only effectively suppress noise but also fully maintain the original characteristics of the data.

[0061] like Figure 2 As shown, in some embodiments of the present disclosure, the relative standard deviation of the X-ray photoelectron spectral area of ​​each set of simulated X-ray photoelectron spectral data is determined based on the X-ray photoelectron spectral area of ​​each simulated X-ray photoelectron spectral data in each set of simulated X-ray photoelectron spectral data (box 420).

[0062] In some embodiments, the relative standard deviation of the X-ray photoelectron spectral area of ​​each set of simulated X-ray photoelectron spectral data can be calculated using formula (7):

[0063] RSD(sv) y =σ(sv) / μ(sv)×100% (7)

[0064] In formula (7), RSD(sv) y represents the relative standard deviation of the X-ray photoelectron spectral area of ​​each set of simulated X-ray photoelectron spectral data; μ(sv) represents the mean area of ​​each set of simulated X-ray photoelectron spectral data, z represents the number of simulated X-ray photoelectron spectroscopy data in each group of simulated X-ray photoelectron spectroscopy data, A r represents the energy spectrum area of ​​each set of simulated X-ray photoelectron energy spectrum data, r is an integer from 1 to z; σ(sv) is the area standard deviation of each set of simulated X-ray photoelectron energy spectrum data,

[0065] In some embodiments of the present disclosure, multiple groups of simulated X-ray photoelectron spectroscopy data are generated by generating multiple simulated X-ray photoelectron spectroscopy data according to a Poisson distribution based on any count spectrum in previous X-ray photoelectron spectroscopy data and averaging and grouping the multiple simulated X-ray photoelectron spectra.

[0066] In some embodiments, any count spectrum in the previous X-ray photoelectron spectroscopy data can be regarded as a p*1 matrix. If each element of this p*1 matrix is ​​used as the parameter λ of the Poisson distribution, and a random number that obeys the Poisson distribution is generated in the column direction, then any count spectrum in the previous X-ray photoelectron spectroscopy data can be used to generate a specified number of q simulated X-ray photoelectron spectroscopy spectra, and the p*1 matrix becomes a p*q matrix. Then, the generated q simulated X-ray photoelectron spectroscopy data are evenly grouped, for example, into y groups, to obtain y groups of simulated X-ray photoelectron spectroscopy data.

[0067] like Figure 2 As shown, in some embodiments of the present disclosure, the X-ray photoelectron spectral area of ​​each simulated X-ray photoelectron spectral data is calculated after subtracting the spectral background of each simulated X-ray photoelectron spectral data (block 410).

[0068] In some embodiments of the present disclosure, the energy spectrum background may include an energy spectrum background based on polynomial fitting, and the X-ray photoelectron energy spectrum area is calculated based on multiple energy spectrum parameters determined by a sum function of a Gaussian function and a Lorentz function.

[0069] In some embodiments, a section can be selected on both wings of the target peak, and then the background of the energy spectrum can be fitted using a polynomial, and then the signal part can be obtained by deducting the background from the original energy spectrum. Using the sum function of the Gaussian function and the Lorentz function as the fitting function, various parameters of the signal can be given, wherein the sum function of the Gaussian function and the Lorentz function is defined as shown in formula (8):

[0070] F(x)=a·m·Lx+a·(1-m)·Gx (8)

[0071] In formula (8), Lx represents the Lorenz function, Gx is a Gaussian function, m, a, b, and c represent parameters, where m can adjust the ratio of the Gaussian function to the Lorentz function, a represents the peak height, b represents the peak position, and c represents the full width at half maximum.

[0072] The integral of the sum of the Gaussian function and the Lorenz function on the real number interval is shown in formula (9):

[0073]

[0074] In formula (9), S represents the area of ​​X-ray photoelectron spectrum.

[0075] In some embodiments, a count spectrum (vertical axis unit: counts) in the previous X-ray photoelectron spectral data is taken, 6000 spectra are generated according to the Poisson distribution, and the 6000 spectra are divided into 200 groups of simulated X-ray photoelectron spectral data in groups of 30. The X-ray photoelectron spectral area Ar of each simulated X-ray photoelectron spectral data in each group of simulated X-ray photoelectron spectral data can be calculated using formula (9). According to formula (7), the relative standard deviation RSD (sv) of the X-ray photoelectron spectral area of ​​each group of simulated X-ray photoelectron spectral data can be calculated: y According to formula (6), the simulated standard deviation σ of the X-ray photoelectron spectral area of ​​200 sets of simulated X-ray photoelectron spectral data generated by the previous X-ray photoelectron spectral data can be calculated: RSD. The simulated standard deviation of the X-ray photoelectron energy spectrum area of ​​200 sets of simulated X-ray photoelectron energy spectrum data can effectively measure the fluctuation level of the X-ray photoelectron energy spectrum. In some embodiments, when the difference between the relative standard deviation of the filtered X-ray photoelectron energy spectrum area and the relative standard deviation of the X-ray photoelectron energy spectrum area before filtering is approximately equal to the simulated standard deviation, the cutoff frequency of the FIR filter can be determined. Then, based on the cutoff frequency of the FIR filter and the predetermined order of the filter, the filter coefficient can be determined according to formula (5). For example, in some embodiments, the order can be set to 9th or 11th order to calculate the filter coefficient.

[0076] Those skilled in the art will understand that taking a count spectrum (vertical axis unit: counts) from previous X-ray photoelectron spectral data, generating 6000 spectra according to Poisson distribution, and dividing these 6000 spectra into 200 groups of simulated X-ray photoelectron spectral data in groups of 30 is merely exemplary, and other suitable numbers of spectra may also be generated according to Poisson distribution, for example, 4000 spectra, 5000 spectra, 7000 spectra or 10000 spectra, etc. may be generated according to Poisson distribution, and divided into multiple groups of simulated X-ray photoelectron spectral data in groups of 20, 40, 50, etc., for example, 80 groups, 100 groups, 175 groups, 250 groups, 350 groups, 500 groups, etc. may be divided into simulated X-ray photoelectron spectral data.

[0077] Those skilled in the art will appreciate that the 9th-order filter coefficients and the 11th-order filter coefficients are merely exemplary, and filter coefficients of other orders may also be selected as needed.

[0078] The X-ray photoelectron spectroscopy processing method according to any one of the embodiments of the present disclosure may be applied to an existing X-ray photoelectron spectroscopy system.

[0079] Figure 4 A schematic diagram of an X-ray photoelectron spectroscopy system 300 according to some embodiments of the present disclosure is shown.

[0080] like Figure 4 As shown, in some embodiments of the present disclosure, the X-ray photoelectron spectroscopy system 300 may include an X-ray photoelectron spectrometer 310 and a processor 320. The X-ray photoelectron spectrometer 310 is used to collect X-ray photoelectron spectroscopy data. The processor 320 is connected to the X-ray photoelectron spectrometer in communication. The processor is configured to execute the X-ray photoelectron spectroscopy processing method according to any one of the embodiments of the present disclosure to filter the X-ray photoelectron spectroscopy data collected by the X-ray photoelectron spectrometer 310 to obtain filtered X-ray photoelectron spectroscopy data.

[0081] like Figure 4As shown, in some embodiments of the present disclosure, the X-ray photoelectron spectroscopy system 300 may further include a vacuum chamber 330, the X-ray photoelectron spectrometer 310 is at least partially vacuum-sealed and connected to the vacuum chamber 330, and the sample 400 is placed in the vacuum chamber 330 so as to be analyzed by the X-ray photoelectron spectrometer 310.

[0082] Those skilled in the art will understand that Figure 4 For exemplary purposes only, the processor 320 may also be disposed in an X-ray photoelectron spectrometer to form an integrated X-ray photoelectron spectrometer system.

[0083] The X-ray photoelectron spectroscopy system 300 according to any one of the embodiments of the present disclosure can be used in various appropriate analyses, for example, including, but not limited to, elemental composition analysis, chemical state analysis, surface component depth analysis, chemical bonding state analysis, etc.

[0084] In some embodiments, the X-ray photoelectron spectroscopy system 300 may be used for, for example, silicon oxynitride (SiON) metrology.

[0085] Figure 3A The figure shows the X-ray photoelectron spectroscopy data (N1s peak) obtained by measuring SiON before filtering. Figure 3B The X-ray photoelectron spectroscopy processing method and system of some embodiments of the present disclosure are shown. Figure 3A The X-ray photoelectron spectroscopy data shown are X-ray photoelectron spectroscopy data after filtering (N1s peak).

[0086] from Figure 3A and 3B It can be seen that the X-ray photoelectron spectroscopy processing method according to any one of the embodiments of the present disclosure, or the X-ray photoelectron spectroscopy system using a processor configured to execute the X-ray photoelectron spectroscopy processing method according to any one of the embodiments of the present disclosure, can effectively suppress the noise of the X-ray photoelectron spectroscopy of SiON and improve the measurement stability. In addition, the X-ray photoelectron spectroscopy processing method or X-ray photoelectron spectroscopy system using some embodiments of the present disclosure has the advantages of high efficiency, accuracy and real-time response.

[0087] In some embodiments of the present disclosure, a computer device may include a memory and a processor. The memory is used to store at least one instruction. The processor is coupled to the memory and is used to execute at least one instruction to perform the X-ray photoelectron spectroscopy processing method according to any one of the embodiments of the present disclosure, for example, Figure 1 Part or all of the steps of the X-ray photoelectron spectroscopy processing method shown.

[0088] In some embodiments of the present disclosure, a computer-readable storage medium may be used to store at least one instruction. When the at least one instruction is executed by a computer device, the computer executes the method for processing X-ray photoelectron spectroscopy according to any one of the embodiments of the present disclosure, for example, Figure 1 Some or all of the steps of the method for processing X-ray photoelectron spectroscopy shown. Examples of computer-readable storage media include storage of computer programs (instructions), such as read-only memory (ROM), random access memory (RAM), compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device.

[0089] It should be pointed out that the above are only exemplary embodiments of the present disclosure and are not intended to limit the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A method for processing X-ray photoelectron spectroscopy, characterized in that: include: receiving X-ray photoelectron spectroscopy data; as well as The X-ray photoelectron spectroscopy data is filtered by a finite impulse response (FIR) filter to obtain filtered X-ray photoelectron spectroscopy data.

2. The method for processing X-ray photoelectron spectroscopy according to claim 1, characterized in that: The FIR filter comprises N filter coefficients, where N is an integer greater than 1, Filtering the X-ray photoelectron spectrum data by using an FIR filter includes: performing a convolution operation on the N filter coefficients and the X-ray photoelectron spectrum data to obtain filtered X-ray photoelectron spectrum data.

3. The method for processing X-ray photoelectron spectroscopy according to claim 2, characterized in that: The X-ray photoelectron spectroscopy data includes M values, where M is an integer greater than N. Performing a convolution operation on the N filter coefficients and the X-ray photoelectron energy spectrum data includes: calculating the convolution of the N filter coefficients and the N consecutive values ​​before the k-th value in the X-ray photoelectron energy spectrum data to obtain the k-th filtered value, where k is between 0 and M-1.

4. The method for processing X-ray photoelectron spectroscopy according to claim 3, characterized in that: Receiving X-ray photoelectron spectrum data includes: continuously receiving values ​​in the X-ray photoelectron spectrum data; and The convolution operation of the N filter coefficients and the X-ray photoelectron spectrum data includes: calculating the convolution of the N filter coefficients and the N consecutive values ​​before the kth value in the X-ray photoelectron spectrum data in real time to obtain the kth filtered value.

5. The method for processing X-ray photoelectron spectroscopy according to claim 2, characterized in that: The N filter coefficients are determined based on a cutoff frequency and a predetermined order N of the FIR filter.

6. The method for processing X-ray photoelectron spectroscopy according to claim 5, characterized in that: The N filter coefficients are determined based on a cutoff frequency of the FIR filter and a sinc function.

7. The method for processing X-ray photoelectron spectroscopy according to claim 6, characterized in that: The N filter coefficients are determined based on a cutoff frequency of the FIR filter and a product of a sinc function and a Blackman window function.

8. The method for processing X-ray photoelectron spectroscopy according to claim 5, characterized in that: The cutoff frequency of the FIR filter is predetermined based on previous X-ray photoelectron spectroscopy data.

9. The method for processing X-ray photoelectron spectroscopy according to claim 8, characterized in that: The cutoff frequency of the FIR filter is determined based on the difference between the relative standard deviation of the filtered X-ray photoelectron spectrum area and the relative standard deviation of the X-ray photoelectron spectrum area and the simulated standard deviation.

10. The method for processing X-ray photoelectron spectroscopy according to claim 9, characterized in that: The simulated standard deviation is determined based on a relative standard deviation of X-ray photoelectron spectroscopy areas of a plurality of sets of simulated X-ray photoelectron spectroscopy data generated from the previous X-ray photoelectron spectroscopy data.

11. The method for processing X-ray photoelectron spectroscopy according to claim 10, characterized in that: The relative standard deviation of the X-ray photoelectron spectral area of ​​each set of simulated X-ray photoelectron spectral data is determined based on the X-ray photoelectron spectral area of ​​each simulated X-ray photoelectron spectral data in each set of simulated X-ray photoelectron spectral data.

12. The method for processing X-ray photoelectron spectroscopy according to claim 10, characterized in that: The multiple groups of simulated X-ray photoelectron spectroscopy data are generated by generating multiple simulated X-ray photoelectron spectroscopy data according to Poisson distribution based on any one count spectrum in the previous X-ray photoelectron spectroscopy data and averaging and grouping the multiple simulated X-ray photoelectron spectroscopy spectra.

13. The method for processing X-ray photoelectron spectroscopy according to claim 12, characterized in that: The X-ray photoelectron energy spectrum area of ​​each simulated X-ray photoelectron energy spectrum data is calculated after deducting the energy spectrum background of each simulated X-ray photoelectron energy spectrum data.

14. The method for processing X-ray photoelectron spectroscopy according to claim 13, characterized in that: The energy spectrum background includes an energy spectrum background based on polynomial fitting, and the X-ray photoelectron energy spectrum area is calculated based on a plurality of energy spectrum parameters determined by a sum function of a Gaussian function and a Lorentz function.

15. An X-ray photoelectron spectroscopy system, characterized in that: include: X-ray photoelectron spectrometer, used to collect X-ray photoelectron spectrum data; as well as A processor is communicatively connected to the X-ray photoelectron spectrometer, and the processor is configured to execute the X-ray photoelectron spectrum processing method according to any one of claims 1-14 to filter the X-ray photoelectron spectrum data collected by the X-ray photoelectron spectrometer to obtain filtered X-ray photoelectron spectrum data.

16. A computer device, characterized in that: The computer device comprises: A memory for storing at least one instruction; and A processor is coupled to the memory and is used to execute the at least one instruction to perform the X-ray photoelectron spectroscopy processing method according to any one of claims 1-14.

17. A computer-readable storage medium for storing at least one instruction, characterized in that: When the at least one instruction is executed by a computer device, it causes the computer to execute the X-ray photoelectron spectroscopy processing method according to any one of claims 1-14.

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