Remote plasma source working point judgment method, device, equipment and medium

Abstract

The invention relates to the technical field of plasmas, in particular to a remote plasma source working point judgment method, device and equipment and a medium. The mass spectrum dissociation rate is calculated according to the first mass spectrum and the second mass spectrum; calculating a spectral dissociation rate according to the spectrogram; performing correction calculation on the mass spectrum dissociation rate and the spectral dissociation rate based on the initial prior Gaussian distribution model to obtain a corrected dissociation rate; when the corrected dissociation rate meets the dissociation rate required by the process, calculating an actual reaction rate according to the spectrogram and a preset emission peak height threshold value; when the actual reaction rate is equal to the reaction rate threshold value, a feedback signal reaching the process working point is generated; mass spectrum data and spectral data are mutually verified in real time, the contradiction between single-mode detection precision and process compatibility is overcome, errors such as signal attenuation, interference and peak overlapping are reduced, the reliability of dissociation rate detection is remarkably improved, meanwhile, a working point is judged in combination with correction of the dissociation rate and the actual reaction rate, stability control is enhanced, and the process precision and the yield are improved.

Description

Technical Field

[0001] The present invention relates to the field of plasma technology, and particularly relates to a method, device, equipment and medium for judging the working point of a remote plasma source. Background Art

[0002] A remote plasma source is a device for generating plasma, also known as a remote high-density plasma generator, and is commonly used in surface treatment-related processes in the fields of semiconductor equipment, aerospace, display equipment, and medical equipment. Different from traditional plasma sources, there is a physical separation between the plasma generation region and the processing region in a remote plasma source. After the plasma is generated, it is transmitted to the processing region, and active particles (such as free radicals, ions, and neutral particles) diffuse during the transmission process.

[0003] The dissociation rate of a remote plasma source is the core index for judging its working state, directly determining the plasma chemical reaction efficiency and process stability. Among the current mainstream detection methods, the mass spectrometry method is convenient to operate; however, as the semiconductor process cavities in advanced processes show diverse geometric structures (such as deep trench aspect ratio design), the gas transport kinetics of different processes are not consistent, resulting in the attenuation of the mass spectrometry signal; secondly, the improvement requirements of the power of advanced processes will cause the secondary electron effect to interfere with the ion collection accuracy; specific processes (such as negative photoresist cleaning) will generate particles with the same m / z value, causing the characteristic peaks to overlap, so that in some cases, the detection error of the dissociation rate by the mass spectrometry method exceeds 15%. Although the gradually popularized spectroscopy method has high accuracy, it faces the inherent defect that some spectral emission curves are adjacent (such as ArI 750.4 nm and OII 751.1 nm) and difficult to separate, and it relies on expensive high-resolution spectrometers. The above single-mode detection methods have an inherent contradiction between accuracy and process compatibility, and incorrect dissociation rate judgment will directly lead to inaccurate judgment of the working point of the remote plasma source, and then cause the decline of process accuracy and stability. Summary of the Invention

[0004] In order to solve the above-mentioned disadvantages in the prior art, the present invention proposes a method for judging the working point of a remote plasma source.

[0005] To solve the above technical problems, the technical solutions adopted by the present invention are as follows: A method for judging the working point of a remote plasma source, comprising: obtaining a mass spectrum to obtain a first mass spectrum and a second mass spectrum; calculating a mass spectrum dissociation rate according to the first mass spectrum and the second mass spectrum; obtaining a spectrogram and calculating a spectral dissociation rate according to the spectrogram; constructing an initial prior Gaussian distribution model based on a preset first database; performing correction calculation on the mass spectrum dissociation rate and the spectral dissociation rate based on the initial prior Gaussian distribution model to obtain a corrected dissociation rate; judging whether the corrected dissociation rate meets a preset process requirement dissociation rate; when the corrected dissociation rate meets the process requirement dissociation rate, calculating an actual reaction rate according to the spectrogram and a preset emission peak height threshold; judging whether the actual reaction rate is equal to a preset reaction rate threshold; when the actual reaction rate is equal to the reaction rate threshold, generating a feedback signal indicating that the process working point is reached. By obtaining the mass spectrum and the spectrogram of the remote plasma source, calculating the mass spectrum dissociation rate and the spectral dissociation rate respectively, and performing correction calculation based on the initial prior Gaussian distribution model, real-time cross-verification of mass spectrum and spectral data is achieved; this multi-data-source fusion method overcomes the inherent contradiction between the accuracy and process compatibility of single-modal detection methods, effectively reduces errors caused by problems such as mass spectrum signal attenuation, interference in ion collection accuracy, overlapping of characteristic peaks, and difficulty in separating adjacent spectral emission curves, and greatly improves the reliability of dissociation rate detection; in terms of working point judgment, only when both the corrected dissociation rate and the actual reaction rate meet the requirements, it is determined that the process working point is reached and a feedback signal is generated, which helps to ensure that the remote plasma source is always in the best working state under complex process conditions, significantly enhances the stability control ability, thereby improving the process accuracy and stability, and improving the yield of related processes during the long-term operation of the remote plasma source.

[0006] Further, the obtaining the spectrogram and calculating the spectral dissociation rate according to the spectrogram includes: The sensitivity is calculated according to a preset second database and a preset sensitivity correction curve to obtain a first relative sensitivity and a second relative sensitivity; a proportionality constant is calculated according to a preset third database and a preset condition for ignoring electron quenching; a spectrogram is obtained; the spectrogram is subjected to feature analysis to obtain spectral emission peak data; a first measured emission intensity and a second measured emission intensity are obtained from the spectral emission peak data; a density ratio is calculated according to the first measured emission intensity, the second measured emission intensity, the first relative sensitivity, the second relative sensitivity, and the proportionality constant; relative carrier gas particle data, relative reactive gas particle data, carrier gas flow rate, and reactive gas flow rate are obtained; a percentage calculation is performed according to the relative carrier gas particle data, the relative reactive gas particle data, the carrier gas flow rate, the reactive gas flow rate, and the density ratio to obtain a spectral dissociation rate. By calculating key parameters such as relative sensitivity and proportionality constant through a preset database and specific conditions, the influence of spectral hardware characteristics and complex physical and chemical conditions on the measurement of spectral dissociation rate is fully considered; in the process of calculating the spectral dissociation rate, information from multiple aspects such as spectral emission intensity, relative particle data, and flow rate data is comprehensively used, effectively reducing the error caused by a single measurement factor, significantly improving the accuracy of spectral dissociation rate detection, and being able to provide more reliable data support for the judgment of the dissociation rate of a remote plasma source; by participating in the calculation of the spectral dissociation rate with relative carrier gas particle data, relative reactive gas particle data, and flow rate data, the influence of different reaction conditions on the dissociation rate can be intuitively reflected, providing a strong basis for optimizing process parameters and helping to improve the stability of the process.

[0007] Further, the sensitivity calculation based on the preset second database and the preset sensitivity correction curve to obtain the first relative sensitivity and the second relative sensitivity includes: obtaining the emission wavelengths of the reactive gas and the carrier gas from the second database to obtain the first emission wavelength and the second emission wavelength; performing sensitivity calculation on the first emission wavelength and the second emission wavelength to obtain the first sensitivity and the second sensitivity; correcting the first sensitivity and the second sensitivity according to the sensitivity correction curve to obtain the first relative sensitivity and the second relative sensitivity. Using the open-source spectral database to obtain the emission wavelength and combining with the sensitivity correction curve for correction can reduce the influence of hardware errors, making the obtained relative sensitivity more accurately reflect the actual situation of the reactive gas and the carrier gas in spectral detection. This helps to more precisely judge the working state of the remote plasma source, enabling the system to adapt to a variety of different reactive gas and carrier gas combinations, providing reliable data support for subsequent process control, and thus improving the accuracy and quality of the entire process; in actual industrial production or scientific research applications, the remote plasma source may use a variety of different gases for process operations. Through the sensitivity curve correction method, the spectral sensitivities of different gases can be conveniently and accurately measured and corrected without the need for complex system adjustments for different gas combinations, improving the versatility of the system and its adaptability to different process conditions.

[0008] Further, the calculation of the proportionality constant based on the preset third database and the preset condition for ignoring electron quenching includes: obtaining the collision coefficients of the reactive gas and the carrier gas from the third database to obtain the first collision coefficient and the second collision coefficient; obtaining the branching ratios at the first emission wavelength and the second emission wavelength to obtain the first branching ratio and the second branching ratio; obtaining the proportionality constant calculation formula according to the condition for ignoring electron quenching; calculating the proportionality constant based on the proportionality constant calculation formula, the first collision coefficient, the second collision coefficient, the first branching ratio, and the second branching ratio. Obtaining the ground-state electron excitation collision coefficients of the carrier gas and the reactive gas from the open-source database ensures the accuracy of the basic data. The differences in the collision coefficients of different gases can reflect their excitation and reaction characteristics in the plasma environment, providing a solid foundation for subsequent calculations; by accurately obtaining the branching ratios, which are key parameters for atomic or molecular excited-state transitions, it is of great significance for understanding the excited-state behavior and spectral characteristics of gases in the plasma and is an important basis for calculating the proportionality constant; the condition for ignoring electron quenching simplifies the complex energy transfer and reaction processes, resulting in a relatively simple and practical proportionality constant calculation formula, reducing the calculation difficulty and resource consumption. At the same time, based on reasonable physical assumptions and theoretical derivations, the scientific nature of the formula is ensured; the accurately calculated proportionality constant can more precisely describe the relationship between the reactive gas and the carrier gas in the plasma, helping to more accurately evaluate the working state and performance of the remote plasma source, providing strong support for process control, optimization, and in-depth research on plasma processes, and enhancing the practicality and accuracy of the system.

[0009] Further, the mass spectrometry dissociation rate calculated according to the first mass spectrometry diagram and the second mass spectrometry diagram includes: Performing feature analysis on the first mass spectrometry diagram to obtain the peak value of the first characteristic peak and the peak value of the second characteristic peak; performing feature analysis on the second mass spectrometry diagram to obtain the peak value of the third characteristic peak and the peak value of the fourth characteristic peak; performing percentage calculation based on the peak value of the first characteristic peak, the peak value of the second characteristic peak, the peak value of the third characteristic peak, and the peak value of the fourth characteristic peak to obtain the mass spectrometry dissociation rate. The peak value of the first characteristic peak and the peak value of the second characteristic peak obtained by performing feature analysis on the first mass spectrometry diagram reflect the mass spectrometry characteristics of the carrier gas and the reaction gas when not affected by the plasma source, providing reliable basic data for subsequent calculations; secondly, the peak value of the third characteristic peak and the peak value of the fourth characteristic peak obtained by analyzing the second mass spectrometry diagram, compared with the first mass spectrometry diagram, can visually show the changes in the dissociation and reaction conditions of the gas in the plasma environment; calculating the mass spectrometry dissociation rate according to the four characteristic peak values through a specific formula can quantitatively describe the dissociation degree of the reaction gas under the action of the plasma source, thereby providing accurate data support for evaluating the working effect and reaction efficiency of the remote plasma source; in addition, this method is relatively simple to operate, only requiring feature analysis of the mass spectrometry diagram and simple percentage calculation, without complex equipment and processes, and can quickly detect and evaluate, improving work efficiency; at the same time, the comparative analysis of multiple states helps to deeply understand the action mechanism of the plasma source on the gas, providing a theoretical basis for scientific research and process optimization, and enhancing the understanding and control of the reactions related to the remote plasma source.

[0010] Further, the initial prior Gaussian distribution model constructed according to the preset first database includes: obtaining the maximum mass spectrometry measurement error, the maximum spectroscopy measurement error, the fusion error, and the process requirement dissociation rate from the first database; constructing the initial prior Gaussian distribution model based on the maximum mass spectrometry measurement error, the maximum spectroscopy measurement error, the fusion error, and the process requirement dissociation rate. By modeling the error factors in mass spectrometry and spectroscopy measurements as Gaussian distributions, this method effectively reduces error interference, making the calculated dissociation rate closer to the true value, improving the accuracy of dissociation rate calculation, and providing more reliable data support for the process control of the remote plasma source; incorporating the process requirement dissociation rate into the construction of the initial prior Gaussian distribution model enables the model to not only consider measurement errors but also closely combine the requirements of the actual process. The model constructed in this way can provide more targeted guidance for process optimization; this way of combining theory with practice makes the model have strong scientificity and practicality, and can play an important role in actual applications such as the detection of the dissociation rate of the remote plasma source and process control, providing an effective method and tool for research and practice in related fields.

[0011] Further, the corrected dissociation rate is obtained through corrected calculation based on the initial prior Gaussian distribution model, the mass spectrometry dissociation rate, and the spectral dissociation rate, including: obtaining the dissociation rate mean parameter from the initial prior Gaussian distribution model; constructing a mass spectrometry Gaussian distribution model according to the dissociation rate mean parameter, the mass spectrometry dissociation rate, and the maximum mass spectrometry measurement error; constructing a spectral Gaussian distribution model according to the dissociation rate mean parameter, the spectral dissociation rate, and the maximum spectral measurement error; constructing a joint posterior distribution model according to the initial prior Gaussian distribution model, the mass spectrometry Gaussian distribution model, the spectral Gaussian distribution model, the spectral dissociation rate, the mass spectrometry dissociation rate, and the dissociation rate mean parameter; obtaining the posterior mean and posterior standard deviation from the joint posterior distribution model; and performing corrected calculation according to the posterior mean and posterior standard deviation to obtain the corrected dissociation rate. Considering multiple factors comprehensively to determine the dissociation rate mean parameter provides a reliable benchmark for subsequent analysis and enhances the scientific nature of the overall analysis. Constructing the mass spectrometry Gaussian distribution model and the spectral Gaussian distribution model respectively fully considers the measurement error characteristics and accurately describes the probability distribution under different dissociation rates, providing strong support for in-depth analysis of these two types of dissociation rate data. Using the Bayesian fusion mechanism to construct the joint posterior distribution model integrates the mass spectrometry, spectral, and initial prior model information, realizes real-time cross-verification of multi-source data, effectively utilizes the advantages of multi-source data, and significantly improves the accuracy of dissociation rate estimation. By obtaining the posterior mean and standard deviation of the joint posterior distribution model for corrected calculation, the dissociation rate estimation result is optimized, making the corrected dissociation rate more accurate and reliable. This series of steps not only provides accurate data support for the process control of the remote plasma source, helps improve the process stability and product yield, but also provides effective methods and ideas for dealing with similar multi-source data fusion and parameter estimation problems, with high theoretical value and practical application significance.

[0012] Further, when the corrected dissociation rate meets the process - required dissociation rate, calculating the actual reaction rate according to the spectrogram and the preset emission peak height threshold includes: when the corrected dissociation rate meets the process - required dissociation rate, obtaining the emission peak height of the reaction product from the spectrogram; performing normalization calculation based on the emission peak height of the reaction product and the emission peak height threshold to obtain the actual reaction rate. On the basis of an appropriate dissociation rate, the subsequent analysis of the emission peak height of the reaction product is more meaningful. Secondly, calculating the actual reaction rate by performing normalization calculation based on the emission peak height of the reaction product and the emission peak height threshold utilizes the relationship between the emission peak height of the reaction product in the spectrogram and the actual reaction rate, providing a scientific and reasonable way to characterize the actual reaction rate in the chamber. This method fully considers factors such as the maximum reaction gas flow rate allowed by the process and the allowed dissociation rate, making the calculated actual reaction rate more accurately reflect the true reaction situation in the chamber; by monitoring and calculating the emission peak height of the reaction product, the reaction rate in the chamber can be understood in real - time, facilitating timely adjustment of process parameters to meet the process requirements, improving product quality and production efficiency, reducing production costs, and providing strong support for the optimization and control of remote plasma source - related processes.

[0013] Further, a method for judging the working point of a remote plasma source further includes: judging whether the actual reaction rate is greater than the reaction rate threshold; when the actual reaction rate is greater than the reaction rate threshold, generating a first process - requirement adjustment instruction. By judging the magnitude relationship between the actual reaction rate and the reaction rate threshold, the process operation state can be detected in a timely manner. When the actual reaction rate is greater than the threshold, generating a first process - requirement adjustment instruction to control the flowmeter to reduce the reaction gas input and perform mass spectrometry and spectroscopy tests again. This measure can effectively avoid process deviations caused by too fast a reaction rate, ensuring that the reaction proceeds at a reasonable rate. At the same time, based on the repeated tests of mass spectrometry and spectroscopy, the situation in the process chamber can be further accurately grasped, providing data support for subsequent adjustments and enhancing the overall stability and reliability of the process.

[0014] Further, a method for judging the working point of a remote plasma source further includes: judging whether the actual reaction rate is less than the reaction rate threshold; when the actual reaction rate is less than the reaction rate threshold, generating a second process - requirement adjustment instruction. By judging whether the actual reaction rate is less than the reaction rate threshold, it is possible to know the insufficiency of the reaction rate during the process operation; when the actual reaction rate is lower than the threshold, generating a second process - requirement adjustment instruction to control the flowmeter to increase the reaction gas input, thereby increasing the reaction rate; at the same time, by using mass spectrometry and spectroscopy to test the process chamber again, the changes in the process chamber can be comprehensively and accurately monitored. This can not only effectively ensure that the process is in the best operating state, improve production efficiency, but also provide strong support for the stable and efficient operation of the process.

[0015] Further, a working point judgment device for a remote plasma source includes: an image acquisition module for acquiring mass spectra to obtain a first mass spectrum and a second mass spectrum; a first dissociation rate calculation module for calculating a mass spectrum dissociation rate based on the first mass spectrum and the second mass spectrum; a second dissociation rate calculation module for acquiring a spectrogram and calculating a spectral dissociation rate based on the spectrogram; a model construction module for constructing an initial prior Gaussian distribution model according to a preset first database; a dissociation rate calculation module for performing correction calculations on the mass spectrum dissociation rate and the spectral dissociation rate based on the initial prior Gaussian distribution model to obtain a corrected dissociation rate; a first judgment module for judging whether the corrected dissociation rate meets a preset process requirement dissociation rate; a reaction rate calculation module for, when the corrected dissociation rate meets the process requirement dissociation rate, calculating an actual reaction rate according to the spectrogram and a preset emission peak height threshold; a second judgment module for judging whether the actual reaction rate is equal to a preset reaction rate threshold; and a feedback signal generation module for, when the actual reaction rate is equal to the reaction rate threshold, generating a feedback signal indicating that the process working point has been reached. By acquiring the mass spectrum and spectrogram of the remote plasma source, calculating the mass spectrum dissociation rate and the spectral dissociation rate respectively, and performing correction calculations based on the initial prior Gaussian distribution model, real-time cross-verification of mass spectrum and spectral data is achieved; this multi-data-source fusion method overcomes the inherent contradiction between the accuracy and process compatibility of single-modal detection methods, effectively reduces errors caused by problems such as mass spectrum signal attenuation, interference in ion collection accuracy, overlapping of characteristic peaks, and difficulty in separating adjacent spectral emission curves, and greatly improves the reliability of dissociation rate detection; in terms of working point judgment, only when both the corrected dissociation rate and the actual reaction rate meet the requirements, it is determined that the process working point has been reached and a feedback signal is generated, which helps to ensure that the remote plasma source is always in the best working state under complex process conditions, significantly enhances the stability control ability, thereby improving the process accuracy and stability, and increasing the yield of related processes during the long-term operation of the remote plasma source.

[0016] Further, a working point judgment device for a remote plasma source includes: a memory and at least one processor, wherein instructions are stored in the memory; at least one of the processors calls the instructions in the memory so that the working point judgment method for a remote plasma source executes each step of the working point judgment method for a remote plasma source as described in any one of the above.

[0017] Further, a computer-readable storage medium has instructions stored thereon, and when the instructions are executed by a processor, each step of the working point judgment method for a remote plasma source as described in any one of the above is implemented.

[0018] The beneficial effects of the working point judgment method for a remote plasma source of the present invention are as follows: By obtaining the mass spectrometry and spectrogram of a remote plasma source, calculating the mass spectrometry dissociation rate and spectrogram dissociation rate respectively, and performing corrected calculations based on the initial prior Gaussian distribution model, real-time cross-verification of mass spectrometry and spectral data is achieved; this method of fusing multiple data sources overcomes the inherent contradiction between the accuracy and process compatibility of single-modal detection methods, effectively reducing errors caused by problems such as mass spectrometry signal attenuation, interference in ion collection accuracy, overlapping of characteristic peaks, and difficulty in separating adjacent spectral emission curves, greatly improving the reliability of dissociation rate detection; in terms of working point judgment, only when both the corrected dissociation rate and the actual reaction rate meet the requirements is it determined that the process working point is reached and a feedback signal is generated, which helps to ensure that the remote plasma source is always in the best working state under complex process conditions, significantly enhancing the stability control ability, thereby improving the process accuracy and stability, and increasing the yield of related processes during the long-term operation of the remote plasma source. Description of the Drawings

[0019] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the following description of the embodiments in conjunction with the accompanying drawings, where: Figure 1 The first flow chart of a method for judging the working point of a remote plasma source provided by an embodiment of the present invention; Figure 2 The second flow chart of a method for judging the working point of a remote plasma source provided by an embodiment of the present invention; Figure 3 The third flow chart of a method for judging the working point of a remote plasma source provided by an embodiment of the present invention; Figure 4 The fourth flow chart of a method for judging the working point of a remote plasma source provided by an embodiment of the present invention; Figure 5 The fifth flow chart of a method for judging the working point of a remote plasma source provided by an embodiment of the present invention; Figure 6 The sixth flow chart of a method for judging the working point of a remote plasma source provided by an embodiment of the present invention; Figure 7 The seventh flow chart of a method for judging the working point of a remote plasma source provided by an embodiment of the present invention; Figure 8 The eighth flow chart of a method for judging the working point of a remote plasma source provided by an embodiment of the present invention; Figure 9 The ninth flow chart of a method for judging the working point of a remote plasma source provided by an embodiment of the present invention; Figure 10The tenth flowchart of a method for determining the operating point of a remote plasma source provided by an embodiment of the present invention; Figure 11 A schematic structural diagram of a device for determining the operating point of a remote plasma source provided by an embodiment of the present invention; Figure 12 A schematic structural diagram of a device for determining the operating point of a remote plasma source provided by an embodiment of the present invention. Detailed implementation manners

[0020] Next, the technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0021] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order different from that shown or described herein. In addition, the terms "comprising" or "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0022] For ease of understanding, the specific process of the embodiment of the present invention will be described below. Please refer to Figure 1 , an embodiment of a method for determining the operating point of a remote plasma source in an embodiment of the present invention, includes: 101. Obtain a mass spectrum to obtain a first mass spectrum and a second mass spectrum; In this embodiment, the first mass spectrum is the mass spectrum generated when the power of the remote plasma source is turned off; the second mass spectrum is the mass spectrum generated when the power of the remote plasma source is turned on; 102. Calculate the mass spectrum dissociation rate according to the first mass spectrum and the second mass spectrum; 103. Obtain a spectrogram and calculate the spectral dissociation rate according to the spectrogram; In this embodiment, the spectrogram is the spectrogram generated when the remote plasma source power is turned on. This spectrogram records the spectral information in the plasma state and is used for subsequent calculation of the spectral dissociation rate. When the remote plasma source is normally powered on and running, the carrier gas (usually Ar, which does not participate in the reaction) and the reaction gas (the gas participating in the actual process reaction) are dissociated into plasma and transported to the process chamber. At this time, the controller is in a state of waiting for the host computer signal. The multi-channel spectroscope and mass spectrometer detect the plasma in the process chamber and generate a spectrogram and a mass spectrogram and output them to the host computer. 104. An initial prior Gaussian distribution model is constructed according to a preset first database. In this embodiment, the database contains relevant data such as the dissociation rate of the plasma source under different conditions. The model constructed through these data can play a prior guiding role in the subsequent calculation of the dissociation rate and provide a basic framework for the correction calculation. 105. Based on the initial prior Gaussian distribution model, the mass spectrometry dissociation rate and the spectral dissociation rate are corrected and calculated to obtain the corrected dissociation rate. In this embodiment, this fusion calculation method of multiple data sources can comprehensively utilize the advantages of mass spectrometry and spectral detection, complement and verify data with each other, reduce the error of a single detection method, so that the detection accuracy can reach >98%, and improve the reliability of the dissociation rate detection accuracy. 106. Determine whether the corrected dissociation rate meets the preset process requirement dissociation rate. In this embodiment, the calculated corrected dissociation rate is compared with the preset dissociation rate standard that meets the process requirements to determine whether the dissociation situation of the current plasma source meets the process expectations. 107. When the corrected dissociation rate meets the process requirement dissociation rate, the actual reaction rate is calculated according to the spectrogram and the preset emission peak height threshold. 108. Determine whether the actual reaction rate is equal to the preset reaction rate threshold. 109. When the actual reaction rate is equal to the reaction rate threshold, a feedback signal indicating that the process working point is reached is generated. In this embodiment, if the actual reaction rate is equal to the reaction rate threshold, it means that the working state of the plasma source also meets the requirements in terms of the reaction rate. At this time, a feedback signal indicating that the process working point is reached is generated, indicating the working point state of the remote plasma source at this time. The entire process runs well, realizing the judgment of the working point of the remote plasma source and improving the stability and yield of related processes during the long-term operation of the remote plasma source. In this embodiment, by obtaining the mass spectrometry and spectrogram of the remote plasma source, calculating the mass spectrometry dissociation rate and spectrogram dissociation rate respectively, and performing correction calculations based on the initial prior Gaussian distribution model, real-time cross-verification of mass spectrometry and spectral data is achieved; this multi-data-source fusion method overcomes the inherent contradiction between the accuracy and process compatibility of single-modal detection methods, effectively reducing errors caused by problems such as mass spectrometry signal attenuation, interference in ion collection accuracy, overlapping of characteristic peaks, and difficulty in separating adjacent spectral emission curves, greatly improving the reliability of dissociation rate detection; in terms of working point judgment, only when both the corrected dissociation rate and the actual reaction rate meet the requirements, it is determined that the process working point is reached and a feedback signal is generated, which helps to ensure that the remote plasma source is always in the best working state under complex process conditions, significantly enhancing the stability control ability, thereby improving the process accuracy and stability, and increasing the yield of related processes during the long-term operation of the remote plasma source.

[0023] Please refer to Figure 2 , the second embodiment of a method for judging the working point of a remote plasma source in the embodiment of the present invention, includes: 201. Calculate the sensitivity according to the preset second database and the preset sensitivity correction curve to obtain the first relative sensitivity and the second relative sensitivity; In this embodiment, the first relative sensitivity and the second relative sensitivity are the inherent characteristics of the spectral hardware, reflecting the relative response ability of the spectral hardware to the detection of signals of different substances, and are key parameters for accurately calculating the density ratio subsequently; 202. Calculate the proportionality constant according to the preset third database and the preset condition for ignoring electron quenching; In this embodiment, this proportionality constant plays a key role in adjusting the calculation of the density ratio. It takes into account various complex physical and chemical conditions, making the process of calculating the density ratio based on spectral data more accurate and scientific; 203. Obtain the spectrogram; 204. Perform feature analysis on the spectrogram to obtain spectral emission peak data; obtain the first measured emission intensity and the second measured emission intensity from the spectral emission peak data; In this embodiment, the first measured emission intensity and the second measured emission intensity are the spectral measured emission intensities of the reaction gas and the carrier gas respectively. This step ensures that the data used in the subsequent calculation can accurately reflect the spectral characteristics of the reaction gas and the carrier gas in the plasma state; 205. Calculate the density ratio according to the first measured emission intensity, the second measured emission intensity, the first relative sensitivity, the second relative sensitivity, and the proportionality constant; In this embodiment, the density ratio is the ratio of the reaction gas number density to the carrier gas number density, and the calculation formula of the density ratio is as follows: , is the number density of the reaction gas, is the number density of the carrier gas, The first measured emission intensity, The second measured emission intensity, is the first relative sensitivity, is the second relative sensitivity, is the proportionality constant. By combining the spectral measurement intensity with the spectral hardware characteristics and the proportionality constant, the conversion from spectral data to the proportional relationship of the number density of substances is achieved, providing the core data for subsequent calculation of the spectral dissociation rate; 206. Obtain the relative data of carrier gas particles, the relative data of reaction gas particles, the carrier gas flow rate, and the reaction gas flow rate; 207. Perform percentage calculation based on the relative data of carrier gas particles, the relative data of reaction gas particles, the carrier gas flow rate, the reaction gas flow rate, and the density ratio to obtain the spectral dissociation rate; In this embodiment, the calculation formula of the spectral dissociation rate is as follows: , where in the formula, is the spectral dissociation rate, is the relative data of carrier gas particles, is the relative data of reaction gas particles, is the carrier gas flow rate, is the reaction gas flow rate. The carrier gas flow rate and the reaction gas flow rate are the flow rates of the carrier gas and the reaction gas detected by the flowmeter. The relative data of carrier gas particles and the relative data of reaction gas particles are solely determined by the number of particles participating in the reaction (for example, when the carrier gas is Ar and the reaction gas is NF3, = 1, = 3 because there are 3 F atoms participating in the reaction in NF3, while there is only one Ar atom in Ar relatively); Using these data and the density ratio calculated previously, calculate the spectral dissociation rate according to a specific formula. This formula comprehensively considers various factors such as the number of particles and the gas flow rate in the reaction system, and can comprehensively and accurately reflect the dissociation degree of the reaction gas under the current process conditions; In this embodiment, key parameters such as relative sensitivity and proportionality constant are calculated through a preset database and specific conditions, fully considering the influence of spectral hardware characteristics and complex physicochemical conditions on the measurement of spectral dissociation rate; in the process of calculating the spectral dissociation rate, information from multiple aspects such as spectral emission intensity, relative particle data, and flow data is comprehensively utilized, effectively reducing the error caused by a single measurement factor, significantly improving the accuracy of spectral dissociation rate detection, and being able to provide more reliable data support for the judgment of the dissociation rate of the remote plasma source; by involving relative carrier gas particle data, relative reactant gas particle data, and flow data in the calculation of the spectral dissociation rate, the influence of different reaction conditions on the dissociation rate can be intuitively reflected, providing a strong basis for optimizing process parameters and helping to improve the stability of the process.

[0024] Please refer to Figure 3 , the third embodiment of a method for determining the operating point of a remote plasma source in an embodiment of the present invention, includes: 301. Obtain the emission wavelengths of the reactant gas and the carrier gas from the second database to obtain the first emission wavelength and the second emission wavelength; In this embodiment, the second database is an open-source light source database, and the emission wavelength is an inherent property of the reactant gas and the carrier gas, which can be queried through an open-source spectral database. The first emission wavelength and the second emission wavelength are the emission wavelengths of the reactant gas and the carrier gas respectively; different gases have specific emission wavelengths, which are characteristic identifiers of the gases at the spectral level and provide key parameters for accurately calculating the sensitivity subsequently; 302. Calculate the sensitivity for the first emission wavelength and the second emission wavelength to obtain the first sensitivity and the second sensitivity; In this embodiment, the first sensitivity and the second sensitivity are the sensitivities at the first emission wavelength and the second emission wavelength respectively; since the first sensitivity and the second sensitivity contain the inherent errors of the spectral hardware, they need to be corrected according to the sensitivity correction curve to obtain the first relative sensitivity and the second relative sensitivity. The sensitivity correction curve is obtained through a large number of experiments or theoretical derivations, which describes the relationship between the actual response and the ideal response of the spectral hardware at different wavelengths. By substituting the initial sensitivity into the correction curve for calculation, the influence of hardware errors can be eliminated, and the obtained relative sensitivity can more accurately reflect the actual situation of the reactant gas and the carrier gas in spectral detection, which helps to more precisely judge the operating state of the remote plasma source, provides reliable data support for subsequent process control, and thus improves the accuracy and quality of the entire process; 303. Correct the first sensitivity and the second sensitivity according to the sensitivity correction curve to obtain the first relative sensitivity and the second relative sensitivity; In this embodiment, the first sensitivity and the second sensitivity are the inherent errors of the spectral hardware, and the first sensitivity and the second sensitivity can be corrected by the sensitivity correction curve; In this embodiment, by using the open-source spectral database to obtain the emission wavelength and combining with the sensitivity correction curve for correction, the influence of hardware errors can be reduced, and the obtained relative sensitivity can more accurately reflect the actual situation of the reaction gas and the carrier gas in spectral detection. This helps to more precisely judge the working state of the remote plasma source, enables the system to adapt to a variety of different reaction gas and carrier gas combinations, provides reliable data support for subsequent process control, and thus improves the accuracy and quality of the entire process; in actual industrial production or scientific research applications, the remote plasma source may use a variety of different gases for process operations. Through the sensitivity curve correction method, the spectral sensitivities of different gases can be accurately measured and corrected conveniently, without the need for complex system adjustments for different gas combinations, improving the versatility of the system and its adaptability to different process conditions.

[0025] Please refer to Figure 4 , the fourth embodiment of a method for judging the working point of a remote plasma source in the embodiments of the present invention, includes: 401. Obtain the collision coefficients of the reaction gas and the carrier gas from the third database to obtain the first collision coefficient and the second collision coefficient; In this embodiment, the third database is an open-source database (such as NIST or LXCat), and the first collision coefficient and the second collision coefficient are respectively the ground-state electron excitation collision coefficients of the carrier gas and the reaction gas, both of which can be obtained by querying the open-source database; the ground-state electron excitation collision coefficient describes the ability of ground-state electrons to collide with gas molecules and excite the gas molecules from the ground state to other energy states; different gases have different ground-state electron excitation collision coefficients, which directly affect the excitation and reaction processes of the gas in the plasma environment; 402. Obtain the branching ratios at the first emission wavelength and the second emission wavelength to obtain the first branching ratio and the second branching ratio; In this embodiment, the branching ratio refers to the proportion of each transition path during the transition of an atom or molecule in the excited state to different lower energy levels. Different emission wavelengths correspond to different transition processes. The magnitude of the branching ratio determines the intensity and relative proportion of spectral emission at a specific emission wavelength. Accurately obtaining the branching ratio is crucial for understanding the excited-state behavior and spectral characteristics of the gas in the plasma, and it is one of the important parameters for subsequent calculation of the proportionality constant; 403. Obtain the proportionality constant calculation formula according to the condition of neglecting electron quenching; In this embodiment, electronic quenching refers to the process in which excited atoms or molecules interact with electrons and transfer energy to the electrons to return to a lower energy state. In this embodiment, by ignoring the conditions of electronic quenching, the complex energy transfer and reaction processes in the plasma are simplified, thereby obtaining a relatively simple calculation formula for the proportionality constant applicable to the current calculation. This formula is derived based on certain physical assumptions and theoretical derivations, which relates parameters such as the collision coefficient and the branching ratio, providing a theoretical basis for calculating the proportionality constant; 404. Calculate the proportionality constant based on the calculation formula for the proportionality constant, the first collision coefficient, the second collision coefficient, the first branching ratio, and the second branching ratio; In this embodiment, the expression of the calculation formula for the proportionality constant is as follows: , where, is the proportionality constant, the first collision coefficient, the second collision coefficient, the first branching ratio, the second branching ratio; By accurately calculating the proportionality constant, the relationship between the reaction gas and the carrier gas in the plasma can be described more precisely, and then the working state and performance of the remote plasma source can be evaluated more accurately; In this embodiment, the ground-state electron excitation collision coefficients of the carrier gas and the reaction gas are obtained from an open-source database, ensuring the accuracy of the basic data. The differences in the collision coefficients of different gases can reflect their excitation and reaction characteristics in the plasma environment, providing a solid foundation for subsequent calculations; By accurately obtaining the branching ratio, which is a key parameter for the transition of the excited state of atoms or molecules, it is of great significance for understanding the excited-state behavior and spectral characteristics of gases in the plasma and is an important basis for calculating the proportionality constant; Ignoring the conditions of electronic quenching simplifies the complex energy transfer and reaction processes, obtaining a relatively simple and practical calculation formula for the proportionality constant, reducing the calculation difficulty and resource consumption. At the same time, based on reasonable physical assumptions and theoretical derivations, the scientific nature of the formula is ensured; The accurately calculated proportionality constant can more precisely describe the relationship between the reaction gas and the carrier gas in the plasma, helping to more accurately evaluate the working state and performance of the remote plasma source, providing strong support for process control, optimization, and in-depth research on the plasma process, and enhancing the practicality and accuracy of the system.

[0026] Please refer to Figure 5 , the fifth embodiment of a method for judging the working point of a remote plasma source in the embodiments of the present invention, including: 501. Perform feature analysis on the first mass spectrum to obtain the peak value of the first characteristic peak and the peak value of the second characteristic peak; In this embodiment, the peak value of the first characteristic peak is the peak value of the carrier gas m / z characteristic peak detected by the mass spectrometry when the remote plasma source power is turned off, and the peak value of the second characteristic peak is the peak value of the reactive gas m / z characteristic peak detected by the mass spectrometry when the remote plasma source power is turned off. Both the peak value of the first characteristic peak and the peak value of the second characteristic peak can be obtained by analyzing the first mass spectrometry diagram; the peak values of the first characteristic peak and the second characteristic peak reflect the mass spectrometry characteristics of the carrier gas and the reactive gas when not affected by the plasma source, and are the basic data for subsequent calculations; 502. Perform characteristic analysis on the second mass spectrometry diagram to obtain the peak value of the third characteristic peak and the peak value of the fourth characteristic peak; In this embodiment, the peak value of the third characteristic peak is the peak value of the reactive gas m / z characteristic peak detected by the mass spectrometry when the remote plasma source power is turned on, and the peak value of the second characteristic peak is the peak value of the carrier gas m / z characteristic peak detected by the mass spectrometry when the remote plasma source power is turned off. Both the peak value of the first characteristic peak and the peak value of the second characteristic peak can be obtained by analyzing the first mass spectrometry diagram; compared with the first mass spectrometry diagram, the peak values of the characteristic peaks in the second mass spectrometry diagram may change due to the action of the plasma, and the obtained peak values of the third characteristic peak and the fourth characteristic peak reflect the dissociation and reaction conditions of the gas in the plasma environment; 503. Perform percentage calculation based on the peak value of the first characteristic peak, the peak value of the second characteristic peak, the peak value of the third characteristic peak, and the peak value of the fourth characteristic peak to obtain the mass spectrometry dissociation rate; In this embodiment, the mass spectrometry dissociation rate is obtained from the following formula: , where is the mass spectrometry dissociation rate, is the peak value of the first characteristic peak, is the peak value of the second characteristic peak, is the peak value of the third characteristic peak, is the peak value of the fourth characteristic peak; by calculating the mass spectrometry dissociation rate, the dissociation degree of the reactive gas under the action of the plasma source can be quantitatively described, that is, how many reactive gas molecules are dissociated in the plasma environment, which is of great significance for evaluating the working effect and reaction efficiency of the remote plasma source; In this embodiment, the peak values of the first characteristic peak and the second characteristic peak obtained by analyzing the characteristics of the first mass spectrum reflect the mass spectrometry characteristics of the carrier gas and the reaction gas when they are not affected by the plasma source, providing reliable basic data for subsequent calculations. Secondly, by analyzing the peak values of the third characteristic peak and the fourth characteristic peak obtained from the second mass spectrum and comparing them with the first mass spectrum, the dissociation and reaction changes of the gas in the plasma environment can be visually displayed. By calculating the mass spectrometry dissociation rate through a specific formula based on the peak values of the four characteristic peaks, the dissociation degree of the reaction gas under the action of the plasma source can be quantitatively described, thus providing accurate data support for evaluating the working effect and reaction efficiency of the remote plasma source. In addition, this method is relatively simple to operate, only requiring characteristic analysis of the mass spectrum and simple percentage calculations, without complex equipment and processes, enabling rapid detection and evaluation and improving work efficiency. At the same time, the comparative analysis of multiple states helps to deeply understand the mechanism of the plasma source's action on the gas, providing a theoretical basis for scientific research and process optimization, and enhancing the understanding and control of the reactions related to the remote plasma source.

[0027] Please refer to Figure 6 , the sixth embodiment of a method for determining the working point of a remote plasma source in an embodiment of the present invention, includes: 601. Obtain the maximum mass spectrometry measurement error, the maximum spectroscopy measurement error, the fusion error, and the process requirement dissociation rate from the first database; 602. Construct an initial prior Gaussian distribution model based on the maximum mass spectrometry measurement error, the maximum spectroscopy measurement error, the fusion error, and the process requirement dissociation rate; In this embodiment, by modeling the noise generated by secondary electrons and the influence of detection accuracy on the mass spectrum and ignoring the error caused by electron quenching on the spectrum as obeying a Gaussian distribution, and then using the Bayesian fusion mechanism to correct the error interference in the dissociation rate calculation; the expression of the initial prior Gaussian distribution model is as follows: , where , is the preset mean parameter of the true dissociation rate, is the maximum error that appears in the mass spectrum in the most recent n measurements, that is, the maximum mass spectrometry measurement error, is the maximum error that appears in the spectrum in the most recent n measurements, that is, the maximum spectroscopy measurement error, is the dissociation rate required by the relevant process, that is, the process requirement dissociation rate, The fusion error is the error that may occur during the fusion of mass spectrometry and spectral data; these parameters provide an important reference standard for subsequent model construction and analysis; the Gaussian distribution has extensive applications and good characteristics in describing random errors, and many noises and errors in practice approximately follow the Gaussian distribution. By fusing the error information of mass spectrometry and spectral measurements and prior information such as the process requirement dissociation rate, a more accurate initial prior Gaussian distribution model is obtained. The expression of this model comprehensively considers multiple factors such as the true dissociation rate mean parameter, the maximum mass spectrometry measurement error, the maximum spectral measurement error, the process requirement dissociation rate, and the fusion error, and can accurately describe the possible distribution of the dissociation rate. In this embodiment, by modeling the error factors in mass spectrometry and spectral measurements as a Gaussian distribution, this method effectively reduces error interference, makes the calculated dissociation rate closer to the true value, improves the accuracy of dissociation rate calculation, and provides more reliable data support for the process control of the remote plasma source; incorporating the process requirement dissociation rate into the construction of the initial prior Gaussian distribution model enables the model to not only consider measurement errors but also closely combine the requirements of the actual process. The model constructed in this way can provide more targeted guidance for process optimization; this way of combining theory with practice makes the model have strong scientificity and practicality, can play an important role in practical applications such as remote plasma source dissociation rate detection and process control, and provides an effective method and tool for research and practice in related fields.

[0028] Please refer to Figure 7 , the seventh embodiment of a method for judging the working point of a remote plasma source in the embodiments of the present invention, includes: 701. Obtain the dissociation rate mean parameter from the initial prior Gaussian distribution model; In this embodiment, the dissociation rate mean parameter comprehensively considers factors such as the maximum mass spectrometry measurement error, the maximum spectral measurement error, the fusion error, and the process requirement dissociation rate, and provides a reference value for overall analysis; 702. Construct a mass spectrometry Gaussian distribution model according to the dissociation rate mean parameter, the mass spectrometry dissociation rate, and the maximum mass spectrometry measurement error; In this embodiment, the expression of the mass spectrometry Gaussian distribution model is as follows: , where, is the true dissociation rate mean parameter, is the maximum mass spectrometry measurement error, is the mass spectrometry dissociation rate, is the preset mass spectrometry measurement standard deviation, is numerically equal to Equal; the mass spectrometry Gaussian distribution model models the distribution of the mass spectrometry dissociation rate by considering the errors in the mass spectrometry measurement process and the relationship with the mean parameter, which helps to more accurately describe the probability distribution of mass spectrometry data at different dissociation rates; 703. A spectral Gaussian distribution model is constructed based on the mean dissociation rate parameter, the spectral dissociation rate, and the maximum spectral measurement error; In this embodiment, the expression of the spectral Gaussian distribution model is as follows: , where, is the true mean dissociation rate parameter, is the maximum spectral measurement error, is the spectral dissociation rate, is the preset standard deviation of spectral measurement, is numerically equal to ; the spectral Gaussian distribution model performs the same processing on spectral data, considering the error characteristics of spectral measurement, and provides a probability distribution model for the analysis of spectral dissociation rate; 704. A joint posterior distribution model is constructed based on the initial prior Gaussian distribution model, the mass spectrometry Gaussian distribution model, the spectral Gaussian distribution model, the spectral dissociation rate, the mass spectrometry dissociation rate, and the mean dissociation rate parameter; In this embodiment, the expression of the joint posterior distribution model is as follows: , the joint posterior distribution model is a Bayesian fusion mechanism: the core of Bayesian theory is Bayes' formula, which describes the probability of an event occurring under certain known conditions. Before data fusion, it is necessary to determine the prior probabilities of each information source. Each information source calculates the likelihood function under different hypotheses (such as different types of targets) based on its own observed data. Using Bayes' formula, the prior probability and the likelihood function are combined to calculate the posterior probability of each hypothesis. In this way, the observed data of each information source are fused to obtain a more accurate target estimate; in this embodiment, based on the three models constructed above and the spectral dissociation rate, the mass spectrometry dissociation rate, and the mean dissociation rate parameter, a joint posterior distribution model is constructed, applying the Bayesian fusion mechanism and combining Bayes' formula to fuse the information contained in each model. First, determine the prior probabilities of each information source (mass spectrometry dissociation rate and spectral dissociation rate), then calculate the likelihood function according to their respective observed data, and finally obtain the joint posterior distribution through Bayes' formula. This fusion method integrates the information contained in mass spectrometry, spectroscopy, and the initial prior model, makes full use of the advantages of multi-source data, and successfully realizes the real-time cross-verification between mass spectrometry and spectral data, aiming to obtain a more accurate dissociation rate estimate; 705. Obtain the posterior mean and posterior standard deviation from the joint posterior distribution model; 706. Perform correction calculations based on the posterior mean and posterior standard deviation to obtain the corrected dissociation rate; In this embodiment, the posterior mean and posterior standard deviation reflect the central tendency and dispersion degree of the joint posterior distribution. By performing correction calculations using these parameters, the estimation of the dissociation rate obtained previously can be optimized, making the final corrected dissociation rate more accurate and reliable; In this embodiment, the mean parameter of the dissociation rate is determined by comprehensively considering various factors, providing a reliable benchmark for subsequent analysis and enhancing the scientific nature of the overall analysis. The mass spectrometry Gaussian distribution model and the spectral Gaussian distribution model are respectively constructed, fully considering the measurement error characteristics, accurately describing the probability distribution under different dissociation rates, and providing strong support for in-depth analysis of these two types of dissociation rate data. The Bayesian fusion mechanism is used to construct a joint posterior distribution model, integrating the mass spectrometry, spectroscopy, and initial prior model information, realizing real-time cross-verification of multi-source data, effectively utilizing the advantages of multi-source data, and significantly improving the accuracy of dissociation rate estimation. By obtaining the posterior mean and standard deviation of the joint posterior distribution model for correction calculations, the estimation result of the dissociation rate is optimized, making the corrected dissociation rate more accurate and reliable. This series of steps not only provides precise data support for the process control of the remote plasma source, helps improve the process stability and product yield, but also provides effective methods and ideas for dealing with similar multi-source data fusion and parameter estimation problems, having high theoretical value and practical application significance.

[0029] Please refer to Figure 8 , the eighth embodiment of a method for judging the working point of a remote plasma source in the embodiments of the present invention, includes: 801. When the corrected dissociation rate meets the process required dissociation rate, obtain the reaction product emission peak height from the spectrogram; In another embodiment, when the corrected dissociation rate does not meet the process required dissociation rate, increase the power supply output power, control the flowmeter to reduce the input of the raw material gas, and test the process chamber again through mass spectrometry and spectroscopy; 802. Perform normalization calculation based on the reaction product emission peak height and the emission peak height threshold to obtain the actual reaction rate; In this embodiment, compared with when the raw material to be processed is not placed in the process chamber, after the raw material to be processed is placed in the process chamber, the spectrogram will show the emission peak of the reaction product generated after the reaction of the reaction gas and the raw material. Therefore, the normalized occurrence peak height can be used to characterize the actual reaction rate in the chamber. The expression of the normalization calculation is as follows: , where, is the actual reaction rate, is the detected reaction product emission peak height, is the reaction product emission peak height detected at the maximum reaction gas flow rate allowed by the process under the allowed dissociation rate, that is, the emission peak height threshold; In this embodiment, on the basis of an appropriate dissociation rate, the subsequent analysis of the emission peak height of the reaction product is more meaningful. Secondly, the actual reaction rate is obtained through normalization calculation based on the emission peak height of the reaction product and the emission peak height threshold. By utilizing the relationship between the emission peak height of the reaction product in the spectrogram and the actual reaction rate, a scientific and reasonable method is provided for characterizing the actual reaction rate in the cavity. This method fully considers factors such as the maximum reaction gas flow rate allowed by the process and the allowed dissociation rate, making the calculated actual reaction rate more accurately reflect the true reaction situation in the cavity; By monitoring and calculating the emission peak height of the reaction product, the reaction rate in the cavity can be understood in real time, facilitating timely adjustment of process parameters to meet process requirements, improve product quality and production efficiency, reduce production costs, and provide strong support for the optimization and control of remote plasma source-related processes.

[0030] Please refer to Figure 9 , the ninth embodiment of a method for judging the operating point of a remote plasma source in an embodiment of the present invention, includes: 901. Judge whether the actual reaction rate is greater than the reaction rate threshold; 902. When the actual reaction rate is greater than the reaction rate threshold, generate a first process requirement adjustment instruction; In this embodiment, the first process requirement adjustment instruction is to control the flowmeter to reduce the input of the reaction gas, and then test the process cavity again through mass spectrometry and spectroscopy; In this embodiment, by judging the magnitude relationship between the actual reaction rate and the reaction rate threshold, the process operation state can be detected in a timely manner. When the actual reaction rate is greater than the threshold, a first process requirement adjustment instruction is generated to control the flowmeter to reduce the input of the reaction gas and perform mass spectrometry and spectroscopy tests again. This measure can effectively avoid process deviations caused by too fast reaction rate and ensure that the reaction proceeds at a reasonable rate. At the same time, based on the repeated tests of mass spectrometry and spectroscopy, the situation in the process cavity can be further accurately grasped, providing data support for subsequent adjustments and improving the stability and reliability of the overall process.

[0031] Please refer to Figure 10 , the tenth embodiment of a method for judging the operating point of a remote plasma source in an embodiment of the present invention, includes: 1001. Judge whether the actual reaction rate is less than the reaction rate threshold; 1002. When the actual reaction rate is less than the reaction rate threshold, generate a second process requirement adjustment instruction; In this embodiment, the second process requirement adjustment instruction is to control the flowmeter to increase the input of the reaction gas, and then test the process cavity again through mass spectrometry and spectroscopy; In this embodiment, by determining whether the actual reaction rate is less than the reaction rate threshold, it is possible to know the deficiency of the reaction rate during the process operation; when the actual reaction rate is lower than the threshold, a second process requirement adjustment instruction is generated to control the flowmeter to increase the input of the reaction gas, thereby increasing the reaction rate; at the same time, by using mass spectrometry and spectroscopy to test the process chamber again, the changes in the process chamber can be monitored comprehensively and accurately. This can not only effectively ensure that the process is in the best operating state, improve production efficiency, but also provide strong support for the stable and efficient operation of the process.

[0032] The above describes a method for determining the working point of a remote plasma source in an embodiment of the present invention. Next, a device for determining the working point of a remote plasma source in an embodiment of the present invention will be described. Please refer to Figure 11 An embodiment of a device for determining the working point of a remote plasma source in an embodiment of the present invention includes: An image acquisition module 1 for acquiring a mass spectrometry graph to obtain a first mass spectrometry graph and a second mass spectrometry graph; A first dissociation rate calculation module 2 for calculating the mass spectrometry dissociation rate according to the first mass spectrometry graph and the second mass spectrometry graph; A second dissociation rate calculation module 3 for acquiring a spectrogram and calculating the spectral dissociation rate according to the spectrogram; A model construction module 4 for constructing an initial prior Gaussian distribution model according to a preset first database; A dissociation rate calculation module 5 for performing correction calculation on the mass spectrometry dissociation rate and the spectral dissociation rate based on the initial prior Gaussian distribution model to obtain a corrected dissociation rate; A first judgment module 6 for judging whether the corrected dissociation rate meets the preset process requirement dissociation rate; A reaction rate calculation module 7 for calculating the actual reaction rate according to the spectrogram and a preset emission peak height threshold when the corrected dissociation rate meets the process requirement dissociation rate; A second judgment module 8 for judging whether the actual reaction rate is equal to a preset reaction rate threshold; A feedback signal generation module 9 for generating a feedback signal indicating that the process working point has been reached when the actual reaction rate is equal to the reaction rate threshold; In this embodiment, by obtaining the mass spectrometry and spectrogram of the remote plasma source, calculating the mass spectrometry dissociation rate and spectrogram dissociation rate respectively, and performing correction calculations based on the initial prior Gaussian distribution model, real-time cross-verification of mass spectrometry and spectral data is achieved; this multi-data-source fusion method overcomes the inherent contradiction between the accuracy and process compatibility of single-modal detection methods, effectively reducing errors caused by problems such as mass spectrometry signal attenuation, interference in ion collection accuracy, overlapping of characteristic peaks, and difficulty in separating adjacent spectral emission curves, greatly improving the reliability of dissociation rate detection; in terms of working point judgment, only when both the corrected dissociation rate and the actual reaction rate meet the requirements, it is determined that the process working point is reached and a feedback signal is generated, which helps to ensure that the remote plasma source is always in the best working state under complex process conditions, significantly enhancing the stability control ability, thereby improving the process accuracy and stability, and increasing the yield of related processes during the long-term operation of the remote plasma source.

[0033] Figure 12 FIG. 4 is a schematic structural diagram of a device for judging the working point of a remote plasma source provided by an embodiment of the present invention. The device 900 for judging the working point of a remote plasma source may vary greatly due to configuration or performance, and may include one or more processors (central processing units, CPU) 913 (for example, one or more processors) and a memory 920, and one or more storage media 930 (for example, one or more mass storage devices) for storing application programs 933 or data 932. Among them, the memory 920 and the storage media 930 may be transient storage or persistent storage. The program stored in the storage media 930 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations for a device 900 for judging the working point of a remote plasma source. Further, the processor 913 may be configured to communicate with the storage media 930 and execute a series of instruction operations in the storage media 930 on a device 900 for judging the working point of a remote plasma source to implement the steps of a method for judging the working point of a remote plasma source provided in each of the above method embodiments.

[0034] A device 900 for judging the working point of a remote plasma source may further include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input / output interfaces 960, and / or, one or more operating systems 931, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art can understand, Figure 12The structure of a remote plasma source operating point determination device shown does not limit a remote plasma source operating point determination device 900, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0035] A computer-readable storage medium having instructions stored thereon, which when executed by a processor implement the steps of a remote plasma source operating point determination method as described in any one of the above.

[0036] The present invention and its embodiments have been described above. Such description is not restrictive, and only one of the embodiments of the present invention is shown in the drawings. The actual content is not limited thereto. In general, if those of ordinary skill in the art are inspired by it and, without departing from the gist of the present invention, creatively design a structural manner and an embodiment similar to the technical solution, they shall fall within the protection scope of the present invention.

Claims

1. A method for determining the operating point of a remote plasma source, characterized in that, Including: Obtain mass spectra to get a first mass spectrum and a second mass spectrum; Calculate the mass spectrometry dissociation rate based on the first mass spectrum and the second mass spectrum; Obtain a spectrogram and calculate the spectral dissociation rate based on the spectrogram; Construct an initial prior Gaussian distribution model according to a preset first database; Perform correction calculations on the mass spectrometry dissociation rate and the spectral dissociation rate based on the initial prior Gaussian distribution model to obtain a corrected dissociation rate; Determine whether the corrected dissociation rate meets the preset process requirement dissociation rate; When the corrected dissociation rate meets the process requirement dissociation rate, calculate the actual reaction rate based on the spectrogram and a preset emission peak height threshold; Determine whether the actual reaction rate is equal to a preset reaction rate threshold; When the actual reaction rate is equal to the reaction rate threshold, generate a feedback signal indicating reaching the process operating point.

2. The working point determination method of a remote plasma source according to claim 1, wherein The obtaining a spectrogram and calculating the spectral dissociation rate based on the spectrogram includes: Perform sensitivity calculations according to a preset second database and a preset sensitivity correction curve to obtain a first relative sensitivity and a second relative sensitivity; Calculate a proportionality constant according to a preset third database and a preset condition for neglecting electron quenching; Obtain a spectrogram; Perform feature analysis on the spectrogram to obtain spectral emission peak data; obtain a first measured emission intensity and a second measured emission intensity from the spectral emission peak data; Calculate a density ratio based on the first measured emission intensity, the second measured emission intensity, the first relative sensitivity, the second relative sensitivity, and the proportionality constant; Obtain relative carrier gas particle data, relative reactant gas particle data, carrier gas flow rate, and reactant gas flow rate; Perform percentage calculations based on the relative carrier gas particle data, the relative reactant gas particle data, the carrier gas flow rate, the reactant gas flow rate, and the density ratio to obtain the spectral dissociation rate.

3. The method for judging the working point of a remote plasma source according to claim 2, characterized in that, The performing sensitivity calculations according to a preset second database and a preset sensitivity correction curve to obtain a first relative sensitivity and a second relative sensitivity includes: Obtain the emission wavelengths of the reactant gas and the carrier gas from the second database to obtain a first emission wavelength and a second emission wavelength; Perform sensitivity calculations on the first emission wavelength and the second emission wavelength to obtain a first sensitivity and a second sensitivity; Correct the first sensitivity and the second sensitivity according to the sensitivity correction curve to obtain a first relative sensitivity and a second relative sensitivity.

4. The method for judging the working point of a remote plasma source according to claim 3, characterized in that, The calculating a proportionality constant according to a preset third database and a preset condition for neglecting electron quenching includes: Obtain the collision coefficients of the reactant gas and the carrier gas from the third database to obtain a first collision coefficient and a second collision coefficient; Obtain the branching ratios at the first emission wavelength and the second emission wavelength to obtain a first branching ratio and a second branching ratio; Obtain a proportionality constant calculation formula according to the condition for neglecting electron quenching; Calculate the proportionality constant based on the proportionality constant calculation formula, the first collision coefficient, the second collision coefficient, the first branching ratio, and the second branching ratio.

5. The method for judging the working point of a remote plasma source according to claim 1, characterized in that The calculating the mass spectrometry dissociation rate based on the first mass spectrum and the second mass spectrum includes: Perform feature analysis on the first mass spectrum to obtain a first characteristic peak peak value and a second characteristic peak peak value; Perform feature analysis on the second mass spectrum to obtain a third characteristic peak peak value and a fourth characteristic peak peak value; Percentage calculations are performed based on the peak values of the first characteristic peak, the second characteristic peak, the third characteristic peak, and the fourth characteristic peak to obtain the mass spectrometry dissociation rate.

6. The working point determination method of a remote plasma source according to claim 1, characterized in that, The initial prior Gaussian distribution model constructed according to a preset first database includes: Obtaining the maximum mass spectrometry measurement error, the maximum spectral measurement error, the fusion error, and the process requirement dissociation rate from the first database; Constructing an initial prior Gaussian distribution model based on the maximum mass spectrometry measurement error, the maximum spectral measurement error, the fusion error, and the process requirement dissociation rate.

7. The method for judging the working point of a remote plasma source according to claim 6, wherein The correction calculation based on the initial prior Gaussian distribution model, the mass spectrometry dissociation rate, and the spectral dissociation rate to obtain the corrected dissociation rate includes: Obtaining the dissociation rate mean parameter from the initial prior Gaussian distribution model; Constructing a mass spectrometry Gaussian distribution model based on the dissociation rate mean parameter, the mass spectrometry dissociation rate, and the maximum mass spectrometry measurement error; Constructing a spectral Gaussian distribution model based on the dissociation rate mean parameter, the spectral dissociation rate, and the maximum spectral measurement error; Constructing a joint posterior distribution model based on the initial prior Gaussian distribution model, the mass spectrometry Gaussian distribution model, the spectral Gaussian distribution model, the spectral dissociation rate, the mass spectrometry dissociation rate, and the dissociation rate mean parameter; Obtaining the posterior mean and the posterior standard deviation from the joint posterior distribution model; Performing a correction calculation based on the posterior mean and the posterior standard deviation to obtain the corrected dissociation rate.

8. The working point judgment method of a remote plasma source according to claim 1, characterized in that, When the corrected dissociation rate meets the process requirement dissociation rate, calculating the actual reaction rate based on the spectrogram and a preset emission peak height threshold, including: When the corrected dissociation rate meets the process requirement dissociation rate, obtaining the emission peak height of the reaction product from the spectrogram; Performing a normalization calculation based on the emission peak height of the reaction product and the emission peak height threshold to obtain the actual reaction rate.

9. The method for judging the working point of a remote plasma source according to claim 1, wherein It also includes: Judging whether the actual reaction rate is greater than the reaction rate threshold; When the actual reaction rate is greater than the reaction rate threshold, generating a first process requirement adjustment instruction.

10. The method for judging the working point of a remote plasma source according to claim 1, wherein It also includes: Judging whether the actual reaction rate is less than the reaction rate threshold; When the actual reaction rate is less than the reaction rate threshold, generating a second process requirement adjustment instruction.

11. A device for judging the working point of a remote plasma source, characterized in that, It includes: An image acquisition module for acquiring mass spectrometry diagrams to obtain a first mass spectrometry diagram and a second mass spectrometry diagram; A first dissociation rate calculation module for calculating the mass spectrometry dissociation rate based on the first mass spectrometry diagram and the second mass spectrometry diagram; A second dissociation rate calculation module for acquiring a spectrogram and calculating the spectral dissociation rate based on the spectrogram; A model construction module for constructing an initial prior Gaussian distribution model according to a preset first database; A dissociation rate calculation module for performing a correction calculation on the mass spectrometry dissociation rate and the spectral dissociation rate based on the initial prior Gaussian distribution model to obtain the corrected dissociation rate; A first judgment module for judging whether the corrected dissociation rate meets the preset process requirement dissociation rate; A reaction rate calculation module for calculating the actual reaction rate based on the spectrogram and a preset emission peak height threshold when the corrected dissociation rate meets the process requirement dissociation rate; A second judgment module for judging whether the actual reaction rate is equal to the preset reaction rate threshold; A feedback signal generation module for generating a feedback signal indicating reaching the process working point when the actual reaction rate is equal to the reaction rate threshold.

12. A remote plasma source operating point determination device, characterized in that, It includes: A memory and at least one processor, wherein instructions are stored in the memory; At least one of the processors invokes the instructions in the memory so that the method for judging the working point of a remote plasma source executes each step of the method for judging the working point of a remote plasma source according to any one of claims 1-10.

13. A computer-readable storage medium having instructions stored thereon, characterized in that, When the instructions are executed by the processor, each step of the method for judging the working point of a remote plasma source according to any one of claims 1-10 is implemented.

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