Ion implantation machine pressure compensation coefficient fitting method and computer program product

Abstract

The invention relates to the technical field of semiconductors, and provides an ion implantation machine pressure compensation coefficient fitting method and a computer program product. The method comprises the steps of parameter definition, data acquisition, data analysis and fitting, and specifically comprises the following steps: acquiring a current machine rotating speed, an optimal pressure compensation coefficient of a certain energy section of a current ion implantation source and a plurality of current vacuum pressure values by defining a brand new machine vacuum characterization parameter; according to the method, the optimal pressure compensation coefficient of any energy section of the corresponding injection ion source of the machine can be calculated, the precision of the pressure compensation coefficient is greatly improved, a key film layer can be optimized, meanwhile, the injection dose difference caused by abnormal change of the state of the machine can be early warned and optimized in time, and manpower and material resources are saved.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor technology, and in particular to a pressure compensation coefficient fitting method for an ion implantation machine and a computer program product. Background Art

[0002] Ion implantation is a method for precisely introducing impurities into semiconductors, modifying the material by introducing dopant ions into the solid. The ion implantation process involves irradiating (implanting) the solid material with accelerated ions of the desired dopant atoms in a vacuum system, thereby forming a surface layer (implantation layer) with specific properties in the selected (implanted) area.

[0003] The GSD ion implanter is a batch wafer synchronous implanter. It loads 13 wafers 19 onto a disk 11 at a time. The machine rotates and the disk scans up and down (as shown by arrow 110 in the figure) to ensure that the ions in the ion beam 12 are evenly implanted onto the surface of all wafers. Figure 1 Schematic diagram of the working principle of ion implantation.

[0004] Certain stages of ion implantation require the wafer to be coated with photoresist (PR) prior to ion implantation. This is particularly true for wafers coated entirely with photoresist. During the initial processing phase of a GSD ion implanter, high-current ion beams bombard the wafer, causing moisture and chemical substances in the photoresist to precipitate, leading to vacuum anomalies in the process chamber. This phenomenon is known as outgassing. Outgassing represents a decrease in the vacuum chamber pressure, indicating the presence of particles that can neutralize the implanted ions, affecting the actual implant dose. Therefore, manufacturers define a pressure compensation factor (pcom) during the initial design phase of the tool to adjust the actual process beam current to ensure the implant dose. However, determining pcom is a complex process, requiring six test wafers and 36 photoresist filler wafers, as well as annealing and sheet resistance (RS) measurements to calculate the formula. According to the official manual, pcom is theoretically related to the implant ion source and energy. For a highly accurate pcom, testing is required for each energy range, which requires significant manpower and resources. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a pressure compensation coefficient fitting method and computer program product for an ion implantation machine, which can improve the accuracy of the pressure compensation coefficient, optimize the key film layer, and provide timely warning and optimization for the injection dose difference caused by abnormal changes in the machine state.

[0006] In order to solve the above problems, the present invention provides a method for fitting the pressure compensation coefficient of an ion implantation machine, comprising the following steps: parameter definition: defining a vacuum characterization parameter expression related to the pressure compensation coefficient and the vacuum pressure value of the process chamber during the machine process; data acquisition: obtaining the optimal pressure compensation coefficient of the current process recipe, and obtaining multiple current vacuum pressure values ​​of the process chamber during the machine process under the current process recipe, wherein the current process recipe includes: the current machine speed, the current ion implantation source, and the current energy segment; data analysis: according to the optimal pressure compensation coefficient of the current process recipe and the multiple current vacuum pressure values ​​and the vacuum characterization parameter expression, calculating the optimal vacuum characterization parameter of the current process recipe as the optimal vacuum characterization parameter for all energy segments under the current machine speed and the current ion implantation source; and fitting: fitting the optimal pressure compensation coefficient for other energy segments under the current machine speed and the current ion implantation source according to the optimal vacuum characterization parameter.

[0007] In some embodiments, in the parameter definition step, the vacuum characterization parameter expression is defined using the following formula:

[0008] Among them, τ represents the vacuum characterization parameter, pcom represents the pressure compensation coefficient, N represents the total number of samples of vacuum pressure values ​​defined by the formula, and P i Represents the vacuum pressure value of the i-th sample.

[0009] In some embodiments, the data acquisition step specifically includes: collecting, verifying, and determining the optimal pressure compensation coefficient for the current process recipe through official manuals; and obtaining batch historical data of the process chamber during the machine process for a target number of historical days under the current process recipe, and performing vacuum pressure value analysis based on the batch historical data to obtain a plurality of the current vacuum pressure values.

[0010] In some embodiments, the step of determining the optimal pressure compensation coefficient of the current process recipe by collecting and verifying through the official manual specifically includes: determining the optimal pressure compensation coefficient of the current process recipe by collecting and verifying through the official manual on the first day of the target historical days; the step of obtaining the batch historical data of the process chamber in the machine process for the target historical days under the current process recipe specifically includes: extracting the data of the process chamber in the machine process for the target historical days under the current process recipe through FDC as the batch historical data, or exporting all datalogs of the process chamber in the machine process for the target historical days under the current process recipe as the batch historical data.

[0011] In some embodiments, the fitting step specifically includes: obtaining multiple target vacuum pressure values ​​of the process chamber during the machine process under the current machine speed, the current ion implantation source and the target energy segment; according to the optimal vacuum characterization parameter and the multiple target vacuum pressure values ​​and the vacuum characterization parameter expression, substituting different pressure compensation coefficients for fitting until the error between the calculated vacuum characterization parameter and the optimal vacuum characterization parameter meets the error range, and the pressure compensation coefficient at this time is the optimal pressure compensation coefficient under the current machine speed, the current ion implantation source and the target energy segment; traversing all energy segments under the current machine speed and the current ion implantation source, and fitting all corresponding optimal pressure compensation coefficients.

[0012] In some embodiments, the value of the optimal vacuum characterization parameter is accurate to 3 decimal places, and the error range is ±0.001.

[0013] In some embodiments, the fitting step specifically includes: forming a trend line of pressure compensation coefficient and vacuum characterization parameter under the current machine speed, the current ion injection source and the target energy segment; predicting the optimal pressure compensation coefficient through the trend line, obtaining the pressure compensation coefficient whose error between the vacuum characterization parameter and the optimal vacuum characterization parameter satisfies the error range, as the optimal pressure compensation coefficient under the current machine speed, the current ion injection source and the target energy segment; traversing all energy segments under the current machine speed and the current ion injection source, and fitting all corresponding optimal pressure compensation coefficients.

[0014] In some embodiments, the method further includes: when the current machine speed of the current process recipe changes, fitting an optimal pressure compensation coefficient after the speed of the current process recipe changes according to the optimal vacuum characterization parameter.

[0015] In some embodiments, the method further includes: collecting and recording the optimal vacuum characterization parameters at a preset period; if the recorded optimal vacuum characterization parameters exceed an allowable fluctuation range, determining that the operating vacuum of the machine is abnormal.

[0016] In order to solve the above problem, the present invention further provides a computer program product, comprising a computer program, wherein the computer program implements the steps of the above method of the present invention when executed by a processor.

[0017] The above technical solution defines new machine vacuum characterization parameters, obtains the current machine speed, the optimal pressure compensation coefficient of a certain energy segment of the current ion injection source, and multiple current vacuum pressure values, and can calculate the optimal pressure compensation coefficient of any energy segment of the machine's corresponding injection ion source, greatly improving the accuracy of the pressure compensation coefficient, and can optimize key film layers. At the same time, it can provide timely warning and optimization of injection dose differences caused by abnormal changes in machine status, saving manpower and material resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 Schematic diagram of the working principle of ion implantation; Figure 2 A flow chart of a method for fitting a pressure compensation coefficient of an ion implantation machine according to an embodiment of the present invention; Figure 3 A schematic diagram of obtaining optimal vacuum characterization parameters provided by an embodiment of the present invention; Figure 4 A schematic diagram of the optimal pressure compensation coefficient for fitting other energy ranges provided by one embodiment of the present invention; Figure 5 A schematic diagram of a pressure compensation coefficient and a vacuum characterization parameter trend line provided in one embodiment of the present invention; Figure 6 A schematic diagram of vacuum differences in processes at different rotation speeds provided by an embodiment of the present invention; Figure 7 A schematic diagram of fitting the optimal pressure compensation coefficient after a speed change is provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0021] Please also refer to Figures 2 to 7 ,in, Figure 2 A flow chart of a method for fitting a pressure compensation coefficient of an ion implantation machine according to an embodiment of the present invention; Figure 3 A schematic diagram of obtaining optimal vacuum characterization parameters provided by an embodiment of the present invention; Figure 4 A schematic diagram of the optimal pressure compensation coefficient for fitting other energy ranges provided by one embodiment of the present invention; Figure 5A schematic diagram of a pressure compensation coefficient and a vacuum characterization parameter trend line provided in one embodiment of the present invention; Figure 6 A schematic diagram of vacuum differences in processes at different rotation speeds provided by an embodiment of the present invention; Figure 7 A schematic diagram of fitting the optimal pressure compensation coefficient after a speed change is provided in one embodiment of the present invention.

[0022] like Figure 2 As shown, the ion implantation machine pressure compensation coefficient fitting method described in this embodiment includes the following steps: S1, parameter definition: defining a vacuum characterization parameter expression related to the pressure compensation coefficient and vacuum pressure value of the process chamber during the machine process; S2, data acquisition: obtaining the optimal pressure compensation coefficient under the current process recipe, and obtaining multiple current vacuum pressure values ​​of the process chamber during the machine process under the current process recipe, the current process recipe including: current machine speed, current ion implantation source and current energy segment; S3, data analysis: according to the optimal pressure compensation coefficient of the current process recipe and the multiple current vacuum pressure values ​​and the vacuum characterization parameter expression, the optimal vacuum characterization parameter of the current process recipe is calculated as the optimal vacuum characterization parameter for all energy segments under the current machine speed and the current ion implantation source; and S4, fitting: fitting the optimal pressure compensation coefficient for other energy segments under the current machine speed and the current ion implantation source according to the optimal vacuum characterization parameter.

[0023] Regarding step S1, parameter definition: defining a vacuum characterization parameter expression related to a pressure compensation coefficient and a vacuum pressure value of a process chamber during a process of the machine.

[0024] In some embodiments, in the parameter definition step, the vacuum characterization parameter expression is defined using the following formula 1: (Formula 1) Among them, τ represents the vacuum characterization parameter, pcom represents the pressure compensation coefficient, N represents the total number of samples of vacuum pressure values ​​defined by the formula, and P i represents the vacuum pressure value of the i-th sample. Specifically, the pressure compensation coefficient pcom and the vacuum pressure value P correspond to the same process recipe, that is, the pressure compensation coefficient pcom and the vacuum pressure value P correspond to the same tool type and tool speed, the same ion implantation source, and the same energy range. A larger number of i indicates a more accurate fit; the tool can be comprehensively considered based on accuracy requirements and cost control.

[0025] Specifically, according to the official manual's definition of the pressure compensation coefficient pcom, the actual beam size I a is the beam current I measured by mMultiply by the compensation coefficient related to the pressure compensation coefficient pcom, as shown in the following formula 2.

[0026] (Formula 2) in, is the compensation coefficient, k=10000*ln(1+pcom*P / 100), P is the corresponding vacuum pressure value. Formula 2 is derived as follows:

[0027]

[0028]

[0029] After derivation of the above formula, the expression for the vacuum characterization parameter τ of the process chamber during the tool process is defined as shown in Formula 1, which characterizes the compensation coefficient related to the pressure compensation coefficient pcom.

[0030] Regarding step S2, data acquisition: obtaining the optimal pressure compensation coefficient of the current process recipe, and obtaining multiple current vacuum pressure values ​​of the process chamber during the machine process under the current process recipe, the current process recipe including: current machine speed, current ion implantation source and current energy segment.

[0031] In some embodiments, the data acquisition step specifically includes: (21) collecting and verifying the optimal pressure compensation coefficient of the current process recipe through official manuals; and (22) obtaining batch historical data of the process chamber during the machine process for a target number of historical days under the current process recipe, and performing vacuum pressure value analysis based on the batch historical data to obtain a plurality of the current vacuum pressure values.

[0032] The optimal pressure compensation coefficient for the current process recipe can be determined by collecting and verifying data from the official manual. The existing method for determining the pressure compensation coefficient pcom can be used. Specifically, determining the pressure compensation coefficient pcom requires six test wafers and 36 photoresist (PR) filler wafers, as well as annealing and RS measurements, and formula calculations. According to the official manual, the pressure compensation coefficient pcom is theoretically related to the ion implantation source and the energy range used. A typical monitor recipe can be selected for the current process recipe to calculate the corresponding pressure compensation coefficient pcom; alternatively, any other recipe can be selected to verify and determine the pressure compensation coefficient pcom.

[0033] In some embodiments, the step of determining the optimal pressure compensation coefficient of the current process formula through collection and verification in the official manual specifically includes: determining the optimal pressure compensation coefficient of the current process formula through collection and verification in the official manual on the first day of the target historical days.

[0034] In some embodiments, the step of obtaining batch historical data of the process chamber during the machine process for the target historical number of days under the current process recipe specifically includes: extracting data of the process chamber during the machine process for the target historical number of days under the current process recipe through FDC as the batch historical data, or exporting all datalogs of the process chamber during the machine process for the target historical number of days under the current process recipe as the batch historical data.

[0035] Regarding step S3, data analysis: based on the optimal pressure compensation coefficient of the current process recipe, multiple current vacuum pressure values ​​and the vacuum characterization parameter expression, the optimal vacuum characterization parameters of the current process recipe are calculated as the optimal vacuum characterization parameters for all energy segments under the current machine speed and the current ion implantation source.

[0036] Specifically, the pressure compensation coefficient pcom obtained in the data acquisition step and multiple current vacuum pressure values ​​P are substituted into the aforementioned vacuum characterization parameter expression (Formula 1) to calculate a vacuum characterization parameter. The calculated vacuum characterization parameter is used as the optimal vacuum characterization parameter of the current process recipe. At the same time, the optimal vacuum characterization parameter of the current process recipe is used as the optimal vacuum characterization parameter (goldenτ) in all energy segments under the current machine speed and the current ion implantation source.

[0037] Regarding step S4, fitting: fitting the optimal pressure compensation coefficients for other energy ranges under the current machine speed and the current ion implantation source according to the optimal vacuum characterization parameters.

[0038] In some embodiments, the fitting step specifically includes: (411) obtaining multiple target vacuum pressure values ​​of the process chamber during the machine process under the current machine speed, the current ion implantation source, and the target energy segment; (412) according to the optimal vacuum characterization parameter and the multiple target vacuum pressure values ​​and the vacuum characterization parameter expression, substituting different pressure compensation coefficients for fitting until the error between the calculated vacuum characterization parameter and the optimal vacuum characterization parameter meets the error range, and the pressure compensation coefficient at this time is the optimal pressure compensation coefficient under the current machine speed, the current ion implantation source, and the target energy segment; and (413) traversing all energy segments under the current machine speed and the current ion implantation source, and fitting all corresponding optimal pressure compensation coefficients.

[0039] Compared to existing technologies, if a very accurate pressure compensation coefficient pcom is required for each energy segment, each energy segment must be tested and verified using official manuals to determine the optimal pressure compensation coefficient, which requires significant manpower and material resources. However, this embodiment defines new machine vacuum characterization parameters, obtains the current machine speed, the optimal pressure compensation coefficient for a specific energy segment of the current ion implantation source, and multiple current vacuum pressure values, and can calculate the optimal pressure compensation coefficient for any energy segment of the corresponding ion implantation source on the machine, allowing optimization of key film layers. Furthermore, compared to the existing method of selecting a typical test process recipe (monitor recipe) to calculate the corresponding pressure compensation coefficient pcom to represent the pressure compensation coefficient pcom for all energy segments of the same ion implantation source on a single machine, this embodiment significantly improves the accuracy of the pressure compensation coefficient. It can also calculate the optimal pressure compensation coefficient for any energy segment of all ion implantation sources on the machine, further improving the accuracy of the pressure compensation coefficient and optimizing key film layers while saving manpower and material resources.

[0040] In some embodiments, the value of the optimal vacuum characterization parameter is accurate to 3 decimal places, and the error range is ±0.001.

[0041] The following is an example of optimizing the pressure compensation coefficient pcom for all energy ranges of an As source on a particular machine.

[0042] The specific process is as follows: (1) Determine the pcom of the As 40KV voltage by collecting data from official manuals. (2) After a period of machine operation, obtain the vacuum pressure value of the As 40KV voltage. (3) According to the expression, calculate the vacuum characterization parameter as golden τ. (4) To optimize the pcom of the As 50KV voltage, obtain the vacuum pressure value of the As 50KV voltage and use the expression to substitute different pcom fittings until the calculated τ and golden τ are close. At this point, the As 50KV pcom is the optimal pcom. Detailed instructions are given below.

[0043] Data Acquisition and Analysis: This machine uses the As 40KV recipe. On Day 1, data collected and verified (machine testing) from the official manual yielded a pcom of 18 (i.e., the optimal pressure compensation factor for the current process recipe is 18). Using FDC software, we extracted the process chamber pressures for all As 40KV recipe runs over the past 500 days to obtain multiple current vacuum pressure values. Using the expression, we calculated the optimal vacuum characterization parameter for the current process recipe, τ = 1.032, as follows: Figure 3 shown. Figure 3In the table, Source.Name represents the ion implantation source, Energy represents the energy range corresponding to the ion implantation source, RUN_START_TIME represents the job start time, Beam_current_AVG represents the average beam current, Beam_current_STD represents the stable beam current, pcom represents the optimal pressure compensation coefficient obtained during the first test run, and τ represents the vacuum parameter calculated using the expression. goldenτ is the average value of all τ values ​​in the table and serves as the optimal vacuum parameter for all energy ranges under As source implantation. This means that after the pressure compensation coefficient pcom for all energy ranges under As source implantation is set, the optimal vacuum parameter should be 1.032.

[0044] Fitting: As Figure 4 As shown in the figure, when pcom is set to 18, only the vacuum characterization parameters for As 100kV and As 110kV match the golden τ (with an error of ±0.001). By varying pcom, for example, increasing pcom from 18 to 19 for As 120kV, we achieve τ = 1.032, matching the golden τ. At this point, pcom = 19 is the optimal pcom for this tool during As 120kV implantation. Similarly, the optimal pcom for all other energy ranges can be fitted (the pcom with τ matching 1.032 is the optimal pcom). Furthermore, this fitting process eliminates the need for additional verification using a control sheet, improving the accuracy of the pressure compensation coefficient while saving both manpower and material resources.

[0045] In some embodiments, the fitting step specifically includes: (421) forming a trend line of pressure compensation coefficient and vacuum characterization parameter under the current machine speed, the current ion injection source and the target energy segment; (422) predicting the optimal pressure compensation coefficient through the trend line, obtaining a pressure compensation coefficient whose error between the vacuum characterization parameter and the optimal vacuum characterization parameter satisfies the error range as the optimal pressure compensation coefficient under the current machine speed, the current ion injection source and the target energy segment; and (423) traversing all energy segments under the current machine speed and the current ion injection source, and fitting all corresponding optimal pressure compensation coefficients.

[0046] It has been verified that the pressure compensation coefficient pcom is proportional to the vacuum characterization parameter τ, so pcom can be predicted by the trend line. Figure 5 The figure shows the pcom and τ trend lines for As 30 kV. When the vacuum characterization parameter τ matches 1.032, it can be determined that the optimal pcom needs to be set to 21. Similarly, the optimal pcom for all other energy ranges can be fitted based on the corresponding trend lines.

[0047] In some embodiments, the method further includes: when the current machine speed of the current process recipe changes, fitting an optimal pressure compensation coefficient after the speed of the current process recipe changes according to the optimal vacuum characterization parameter.

[0048] like Figure 6 As shown, the process vacuum after the GSD switches to slow spin (indicated by the red line in the figure) is significantly different from the process vacuum at high spin speed (indicated by the blue line in the figure). Due to the difference in process vacuum at different spin speeds, PCM verification according to the official manual is required before formal mass production.

[0049] like Figure 7 As shown, using the official manual to verify the pcom of the process recipe for slowspin, the optimal pcom should be set to 56.8, while the optimal pcom verified on day 1 was 62. Using FDC to extract historical data, the vacuum pressure value P was obtained. Substituting pcom = 62 and the corresponding vacuum pressure value P into the aforementioned vacuum characterization parameter expression (Formula 1), the calculated value of golden τ = 1.115 was obtained. Fitting revealed that when pcom was set to 56.8, τ = 1.114, matching the golden τ. Therefore, the pcom setting of 56.8 was reasonable. In other words, the fitted pcom (56.8) obtained by matching the golden τ was identical to the optimal pcom (56.8) obtained by verifying the pcom of the process recipe for slowspin using the official manual. This demonstrates that the aforementioned vacuum characterization parameter expression (Formula 1) is applicable and of reference value. Ultimately, pcom = 56.8 was used as the optimal pressure compensation coefficient after the GSD switched to slowspin. That is, when the current machine speed of the current process recipe changes, the optimal pressure compensation coefficient after the speed change of the current process recipe is re-fitted according to the optimal vacuum characterization parameter.

[0050] In some embodiments, the method further includes: collecting and recording the optimal vacuum characterization parameters at a preset period; if the recorded optimal vacuum characterization parameters exceed an allowable fluctuation range, determining that the operating vacuum of the machine is abnormal.

[0051] Without changing the pressure compensation coefficient pcom, the vacuum parameter τ should theoretically fluctuate within a small range. If the vacuum parameter τ fluctuates significantly within a certain period of time, this indicates an abnormal vacuum condition in the machine and the pressure compensation coefficient pcom may be ineffective, unable to compensate for the implant dose loss caused by this abnormal vacuum condition. By collecting and recording the vacuum parameter τ at a preset interval, abnormal fluctuations in the vacuum parameter τ can be detected promptly, helping to prevent and detect process anomalies.

[0052] The specific steps are as follows: First, identify previously processed products with a key layer and good yield, use an expression to calculate the optimal vacuum parameter, golden τ, and provide an allowable fluctuation range. Collect data and record the optimal vacuum parameter, golden τ, on a monthly basis. The relationship between the optimal vacuum parameter and time can be used to determine whether the machine's pressure compensation coefficient, pcom, is unable to compensate for vacuum fluctuations, leading to dose shifts. If the machine's operating vacuum is abnormal, the pressure compensation coefficient, pcom, is promptly corrected. A special optimal vacuum parameter, golden τ, can be defined for the key layer. This relationship between the optimal vacuum parameter and time can be used to determine whether the machine's pressure compensation coefficient, pcom, is unable to compensate for vacuum fluctuations, leading to dose shifts.

[0053] The above embodiment defines new machine vacuum characterization parameters, obtains the current machine speed, the optimal pressure compensation coefficient of a certain energy segment of the current ion injection source, and multiple current vacuum pressure values, and can calculate the optimal pressure compensation coefficient of any energy segment of the machine's corresponding injection ion source, greatly improving the accuracy of the pressure compensation coefficient, and can optimize key film layers. At the same time, it can provide timely warnings and optimizations for injection dose differences caused by abnormal changes in the machine state, saving manpower and material resources.

[0054] Based on the same inventive concept, the present invention further provides a computer program product, including a computer program, which implements the steps of the aforementioned method of the present invention when executed by a processor.

[0055] Based on the same inventive concept, the present invention also provides a computer device, comprising: a memory for storing a computer program; a processor connected to the memory and for executing the computer program to implement the steps of the aforementioned method of the present invention.

[0056] Based on the same inventive concept, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the aforementioned method of the present invention when executed by a processor.

[0057] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media used in the various embodiments provided herein may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAM bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAM bus dynamic RAM (RDRAM).

[0058] It should be noted that, in the above-mentioned embodiments, each embodiment focuses on the differences from other embodiments, and the same / similar parts between the embodiments can be referred to in detail.

[0059] The terms "including" and "having" and their variations referred to in the present invention document are intended to cover non-exclusive inclusions. The terms "first", "second", etc. are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence, unless the context clearly indicates otherwise, and it should be understood that the data used in this way can be interchanged where appropriate. The term "one or more" depends at least in part on the context and can be used to describe features, structures or characteristics in a singular sense, or can be used to describe features, structures or combinations of features in a plural sense. The term "based on" can be understood as not necessarily intended to express a set of exclusive factors, but can alternatively, also at least in part on the context, allow for the presence of other factors that are not necessarily explicitly described. In addition, the embodiments of the present invention and the features in the embodiments can be combined with each other unless there is a conflict. In addition, in the above description, the description of well-known components and technologies has been omitted to avoid unnecessary confusion of the concepts of the present invention.

[0060] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It should be noted that those skilled in the art may make various improvements and modifications without departing from the principles of the present invention, and such improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for fitting the pressure compensation coefficient of an ion implantation machine, characterized in that: The method includes the following steps: parameter definition: defining a vacuum characterization parameter expression related to a pressure compensation coefficient and a vacuum pressure value of a process chamber during a machine process; data acquisition: obtaining an optimal pressure compensation coefficient of a current process recipe, and obtaining a plurality of current vacuum pressure values ​​of the process chamber during a machine process under the current process recipe, wherein the current process recipe includes a current machine speed, a current ion injection source, and a current energy segment; data analysis: calculating an optimal vacuum characterization parameter of the current process recipe as an optimal vacuum characterization parameter for all energy segments under the current machine speed and the current ion injection source based on the optimal pressure compensation coefficient of the current process recipe and the plurality of current vacuum pressure values ​​and the vacuum characterization parameter expression; and fitting: fitting an optimal pressure compensation coefficient for other energy segments under the current machine speed and the current ion injection source based on the optimal vacuum characterization parameter.

2. The method according to claim 1, characterized in that In the parameter definition step, the vacuum characterization parameter expression is defined using the following formula: Among them, τ represents the vacuum characterization parameter, pcom represents the pressure compensation coefficient, N represents the total number of samples of vacuum pressure values ​​defined by the formula, and P i Represents the vacuum pressure value of the i-th sample.

3. The method according to claim 1, characterized in that The data acquisition step specifically includes: collecting, verifying and determining the optimal pressure compensation coefficient of the current process recipe through official manuals; and obtaining batch historical data of the process chamber during the machine process for a target number of historical days under the current process recipe, and performing vacuum pressure value analysis based on the batch historical data to obtain multiple current vacuum pressure values.

4. The method according to claim 3, characterized in that The step of determining the optimal pressure compensation coefficient of the current process recipe by collecting and verifying through the official manual specifically includes: determining the optimal pressure compensation coefficient of the current process recipe by collecting and verifying through the official manual on the first day of the target historical days; the step of obtaining batch historical data of the process cavity during the machine process for the target historical days under the current process recipe specifically includes: extracting the data of the process cavity during the machine process for the target historical days under the current process recipe through FDC as the batch historical data, or exporting all datalogs of the process cavity during the machine process for the target historical days under the current process recipe as the batch historical data.

5. The method according to claim 1, wherein The fitting step specifically includes: obtaining multiple target vacuum pressure values ​​of the process chamber during the machine process under the current machine speed, the current ion implantation source and the target energy segment; according to the optimal vacuum characterization parameter and the multiple target vacuum pressure values ​​and the vacuum characterization parameter expression, substituting different pressure compensation coefficients for fitting until the error between the calculated vacuum characterization parameter and the optimal vacuum characterization parameter meets the error range, and the pressure compensation coefficient at this time is the optimal pressure compensation coefficient under the current machine speed, the current ion implantation source and the target energy segment; traversing all energy segments under the current machine speed and the current ion implantation source, and fitting all corresponding optimal pressure compensation coefficients.

6. The method according to claim 5, characterized in that The value accuracy of the optimal vacuum characterization parameter is accurate to 3 decimal places, and the error range is ±0.

001.

7. The method according to claim 1, characterized in that The fitting step specifically includes: forming a trend line of the pressure compensation coefficient and the vacuum characterization parameter under the current machine speed, the current ion injection source and the target energy segment; predicting the optimal pressure compensation coefficient through the trend line, obtaining the pressure compensation coefficient whose error between the vacuum characterization parameter and the optimal vacuum characterization parameter satisfies the error range, and serving as the optimal pressure compensation coefficient under the current machine speed, the current ion injection source and the target energy segment; traversing all energy segments under the current machine speed and the current ion injection source, and fitting all corresponding optimal pressure compensation coefficients.

8. The method according to claim 1, characterized in that The method further includes: when the current machine speed of the current process recipe changes, fitting an optimal pressure compensation coefficient after the speed of the current process recipe changes according to the optimal vacuum characterization parameter.

9. The method according to claim 1, characterized in that The method further includes: collecting and recording the optimal vacuum characterization parameters at a preset period; and determining that the operating vacuum of the machine is abnormal if the recorded optimal vacuum characterization parameters exceed an allowable fluctuation range.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

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