Method for analyzing doping concentration during ion implantation, software, equipment and storage medium

Abstract

The invention discloses a method for analyzing doping concentration during ion implantation, software, equipment and a storage medium, relates to the technical field of ion implantation of semiconductor process simulation, and discloses a method for analyzing doping concentration during ion implantation, which comprises the following steps: acquiring a background grid of a device to be processed; refining the background grid to obtain a slice grid of the device to be processed; integrating the geometric relationship between the refined slices represented by the slice grid and the target grid point in the slice grid, and predicting the effective contribution value of each refined slice to the target grid point; and calculating the contribution sum of the effective contribution values at the target grid points, and obtaining the doping concentration of the target grid points in the device to be processed. Namely, the simulation error of doping at the complex structure can be reduced by refining the background grid, and through the effective contribution value of each slice to the target grid point, not only is the accuracy of the obtained doping concentration improved, but also the calculation efficiency is improved.

Description

Technical Field

[0001] This application relates to the technical field of ion implantation in semiconductor process simulation, and particularly to an analysis method, software, device, and storage medium for doping concentration during ion implantation. Background Art

[0002] Ion implantation is the core process to achieve precise doping distribution in semiconductor devices and is widely used in microelectronics manufacturing.

[0003] Ion implantation bombards the surface of a solid material with a high-energy ion beam, thereby introducing doping into the material to form a specific distribution and changing the electrical properties of the solid material. Currently, the structure of chips is becoming more and more complex, and the geometric shape of the chip is no longer a simple straight line or plane. When analyzing the ion implantation process of three-dimensional devices using an analytical ion implantation algorithm, the doping error at complex structures will increase, resulting in a decrease in the efficiency and result accuracy during the simulation of the doping reference concentration of the device.

[0004] The above content is only used to assist in understanding the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide an analysis method for doping concentration during ion implantation, aiming to solve the technical problem of the decrease in efficiency and result accuracy during the simulation of the doping reference concentration of a device.

[0006] To achieve the above purpose, this application proposes an analysis method for doping concentration during ion implantation, and the method includes:

[0007] Obtain the background grid of the device to be processed;

[0008] Refine the background grid to obtain the sliced grid of the device to be processed;

[0009] Integrate the geometric relationship between the refined slices represented by the sliced grid and the target grid points in the sliced grid to predict the effective contribution value of each refined slice to the target grid points;

[0010] Calculate the sum of the contribution values of the effective contribution values at each target grid point to obtain the doping concentration at each target grid point in the device to be processed.

[0011] In one embodiment, the step of integrating the geometric relationship between the refined slices represented by the sliced grid and the target grid points in the sliced grid to predict the effective contribution value of each refined slice to the target grid points includes:

[0012] From the refined slices represented by the sliced grid, mark the target refined slices in the sliced grid whose contribution to the target grid points is not zero;

[0013] Integrate the geometric relationship between the target refined slice and the target grid point based on the Gaussian error function to predict the slice contribution value of each target refined slice to the target grid point;

[0014] Screen out the valid contribution values that meet the preset requirements from the slice contribution values.

[0015] In one embodiment, the step of integrating the geometric relationship between the target refined slice and the target grid point based on the Gaussian error function to predict the slice contribution value of each target refined slice to the target grid point includes:

[0016] Determine the relative positions between each target refined slice and the target grid point;

[0017] Predict the slice contribution value of each target refined slice to the target grid point based on the relative position and the Gaussian error function.

[0018] In one embodiment, the step of refining the background grid to obtain the slice grid of the device to be processed includes:

[0019] Predict the initial contribution value of each initial slice to the target grid point based on the relative position relationship between the initial slice characterized by the background grid and the target grid point in the background grid;

[0020] Judge whether the initial contribution value meets the preset error requirement;

[0021] If the initial contribution value meets the preset error requirement, mark the initial slice corresponding to the initial contribution value;

[0022] Based on the geometric structure of the device to be processed, perform recursive refinement processing on the marked initial slices in the background grid until the error meets the requirement to obtain the slice grid of the device to be processed.

[0023] In one embodiment, the step of calculating the contribution sum of the valid contribution values at each target grid point to obtain the doping concentration of each target grid point in the device to be processed includes:

[0024] Parallelly calculate the contribution sum of each target refined slice to the target grid point to obtain the doping concentration of each target grid point in the device to be processed.

[0025] In one embodiment, the step of refining the background grid to obtain the slice grid of the device to be processed further includes:

[0026] Obtain the user-specified refinement area;

[0027] Refine the to-be-refined grid corresponding to the refined area in the background grid to obtain the sliced grid of the to-be-processed device.

[0028] In addition, to achieve the above object, the present application also proposes an analysis software for doping concentration during ion implantation, and the analysis software for doping concentration during ion implantation includes:

[0029] An acquisition module, configured to acquire the background grid of the to-be-processed device;

[0030] A refinement module, configured to refine the background grid to obtain the sliced grid of the to-be-processed device;

[0031] A calculation module, configured to integrate the geometric relationship between the refined slice characterized by the sliced grid and the target grid points in the sliced grid, and predict the effective contribution value of each refined slice to the target grid points;

[0032] An output module, configured to calculate the contribution sum of the effective contribution values at each target grid point, and obtain the doping concentration at each target grid point in the to-be-processed device.

[0033] In addition, to achieve the above object, the present application also proposes an analysis device for doping concentration during ion implantation, and the device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the analysis method for doping concentration during ion implantation as described above.

[0034] In addition, to achieve the above object, the present application also proposes a storage medium, and the storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the analysis method for doping concentration during ion implantation as described above are implemented.

[0035] In addition, to achieve the above object, the present application also provides a computer program product, and the computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the analysis method for doping concentration during ion implantation as described above are implemented.

[0036] One or more technical solutions proposed by the present application have at least the following technical effects:

[0037] Since the background grid can reflect the geometric structure of the device to be processed, in order to accurately reflect the geometric structure of the device to be processed using grid lines, after obtaining the background grid, the background grid is refined to obtain a more refined grid (slice grid), so that the background grid can precisely represent the geometric features of the device to be processed. Since each slice region represents a slice, the effective contribution value of the refined slice in each slice region to the target grid points to be doped on the device to be processed can be determined, the sum of the contributions of the effective contribution values of each target refined slice is calculated, and the doping concentration of each target grid point is accurately determined using this sum of contributions. Since the slice grid that can accurately represent the geometric structure of the device to be processed can be obtained by refining the background grid, the simulation error of doping at complex structures can be reduced. Combining with the effective contribution values at each target grid point, the accuracy of the doping concentration obtained during the simulation of device doping can be improved. Moreover, combining with the effective contribution values can also reduce unnecessary calculations and improve calculation efficiency. Therefore, the efficiency and result accuracy in the simulation process of the reference concentration of device doping are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0039] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0040] Figure 1 It is a schematic flowchart provided for Embodiment 1 of the method for analyzing the doping concentration during ion implantation in the present application;

[0041] Figure 2 It is a schematic grid diagram provided for Embodiment 1 of the method for analyzing the doping concentration during ion implantation in the present application;

[0042] Figure 3 It is a schematic flowchart provided for Embodiment 2 of the method for analyzing the doping concentration during ion implantation in the present application;

[0043] Figure 4 It is a schematic diagram of a refined slice provided for Embodiment 2 of the method for analyzing the doping concentration during ion implantation in the present application;

[0044] Figure 5 It is a schematic flowchart provided for Embodiment 3 of the method for analyzing the doping concentration during ion implantation in the present application;

[0045] Figure 6Schematic diagram of the module structure of the analysis software for doping concentration during ion implantation of this application;

[0046] Figure 7 Schematic diagram of the device structure of the hardware operating environment involved in the analysis method for doping concentration during ion implantation of this application.

[0047] The realization, functional features and advantages of the purpose of this application will be further described with reference to the accompanying drawings in combination with embodiments. Detailed implementation manners

[0048] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of this application and are not used to limit this application.

[0049] In order to better understand the technical solutions of this application, the following will be described in detail in combination with the accompanying drawings of the specification and specific implementation manners.

[0050] The main solution of the embodiment of this application is: the ion implantation emulator obtains the background grid of the device to be processed; performs refinement processing on the background grid to obtain the slice grid of the device to be processed; integrates the geometric relationship between the refined slices characterized by the slice grid and the target grid points in the slice grid to predict the effective contribution value of each refined slice to the target grid points; calculates the sum of the contribution values of the effective contribution values at each target grid point to obtain the doping concentration of each target grid point in the device to be processed.

[0051] In this embodiment, for the convenience of description, the ion implantation emulator is used as the execution subject for elaboration below.

[0052] Since ion implantation is to bombard the surface of a solid material with a high-energy ion beam, thereby introducing doping into the material interior to form a specific distribution and changing the electrical properties of the solid material. Currently, the structure of chips is becoming more and more complex, and the geometric shape of the chip is no longer a simple straight line or plane. When analyzing the ion implantation process of three-dimensional devices by an analytical ion implantation algorithm, the doping error at complex structures will increase, which will further lead to a decrease in the efficiency and result accuracy during the simulation of the doping reference concentration of the device.

[0053] The present application provides a solution. Since the background grid can reflect the geometric structure of the device to be processed, in order to accurately reflect the geometric structure of the device to be processed using grid lines, after obtaining the background grid, the background grid is refined to obtain a more refined grid (slice grid), so that the background grid can precisely represent the geometric features of the device to be processed. Since each slice region represents a slice, the effective contribution value of the refined slice in each slice region to the target grid points that need to be doped on the device to be processed can be determined. Calculate the contribution sum of the effective contribution values of each target refined slice, and use this contribution sum to accurately determine the doping concentration of each target grid point. Since the slice grid that can accurately represent the geometric structure of the device to be processed can be obtained by refining the background grid, the simulation error of doping at complex structures can be reduced. Combining with the effective contribution values at each target grid point, the accuracy of the doping concentration obtained when simulating device doping can be improved. And combining with the effective contribution values can also reduce unnecessary calculations and improve calculation efficiency. Therefore, the efficiency and result accuracy in the simulation process of the doping reference concentration of the device are improved.

[0054] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication, and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, an ion implantation controller, etc. that can implement the above functions. Hereinafter, taking the ion implantation controller as an example, this embodiment and the following embodiments will be described.

[0055] Based on this, the embodiment of the present application provides a method for analyzing the doping concentration during ion implantation, referring to Figure 1 , Figure 1 which is a schematic flowchart of the first embodiment of the method for analyzing the doping concentration during ion implantation of the present application.

[0056] In this embodiment, the method for analyzing the doping concentration during ion implantation includes steps S10 to S40:

[0057] Step S10, obtain the background grid of the device to be processed;

[0058] It should be noted that the device to be processed is a microelectronic device such as a semiconductor device or a chip. The background grid is a grid structure divided in the initial geometric model of the device to be processed.

[0059] It can be understood that the division of the background grid can be preliminarily designed according to the geometric shape, size, and distribution of the doping region of the device. It provides a basic framework for subsequent refinement processing, and different grid types can be selected according to the complexity of the device, for example, triangular grids, quadrilateral grids, etc., specifically selected according to the structure of the device to be processed.

[0060] It can be understood that the background grid can quickly make a preliminary division of the overall structure of the device, providing a basis for subsequent refinement processing. Moreover, the background grid can be flexibly adjusted according to the complexity of the device according to the user's needs, and is applicable to devices with different geometric structures.

[0061] It can be understood that since the background grid is a grid structure divided in the geometric model of the device to be processed, the background grid can represent devices to be processed with various complexities and generate efficient three-dimensional slices.

[0062] Step S20: Refine the background grid to obtain the slice grid of the device to be processed;

[0063] It should be noted that the refinement processing is to further divide the background grid to make it more refined. The slice grid is the grid structure obtained after refinement processing. It is more refined than the background grid and can more accurately represent the geometric structure and doping distribution of the device.

[0064] It can be understood that the division of the slice grid can be optimized according to the geometric structure of the device, the position of the doping points, and the distribution of the target grid points. For example, the grid near the doping points (target grid points) can be divided more densely, or the grid with a large error in analyzing the doping points can be divided more densely to improve the analysis accuracy.

[0065] It can be understood that through reasonable grid division, the use of computing resources can be optimized while ensuring accuracy.

[0066] It can be understood that since the refinement processing can more accurately capture the local features of the device to be processed, by refining the background grid, the local features of the device to be processed, especially the details of the doping region, can be more accurately represented.

[0067] It can be understood that when performing ion implantation analysis on a complex device structure, due to the complex structure, the doping points at the complex structure cannot be accurately identified. Therefore, on the basis of the background grid that can represent the geometric structure of the device to be processed, the grid structure of the device to be processed is refined again, so that the refined slice grid can clearly represent the complex structure of the device to be processed, so as to improve the identification of the doping points, and local refinement is performed according to different regions and requirements of the device to avoid the computational burden brought by global refinement.

[0068] In a specific implementation, refer to Figure 2, the refinement of the background grid can be achieved through a recursive refinement algorithm, that is, further divide the slices whose errors exceed the tolerance threshold. Estimate the influence of the slices on the target grid points through the Gaussian error function, and judge whether they need to be refined. Further divide the parts that need to be refined, which can make rational use of computing resources, reduce the waste of computing resources, and improve the analysis efficiency of ion implantation for the device to be processed.

[0069] Step S30, integrate the geometric relationship between the refined slices represented by the slice grid and the target grid points in the slice grid, and predict the effective contribution values of each refined slice to the target grid points;

[0070] It should be noted that the target grid points are specific points used to calculate the doping concentration in the slice grid. These points are usually distributed at the key positions of the grid and are used to characterize the influence of doping points on the surrounding areas. The selection of target grid points can be optimized according to preset rules or error requirements. The effective contribution value is the part of each refined slice in the slice grid that meets the preset requirements for the target grid points, reflecting the contribution and actual influence of ions from each slice on the concentration of the target grid points.

[0071] It can be understood that the screening of effective contribution values can reduce unnecessary calculations, improve the calculation efficiency, and under the circumstances of different devices or doping distributions, the screening conditions of effective contribution values can be flexibly adjusted to accurately determine the slices with greater influence on the target grid points, exclude noise and unnecessary interferences, improve the accuracy of doping concentration analysis, and reduce the calculations for slices with less influence. While ensuring the accurate analysis of the doping concentration at the target grid points, it can also improve the calculation efficiency.

[0072] In specific implementations, the calculation of effective contribution values can be optimized according to preset error requirements and relative positions. For example, according to the distance between the doping points and the target grid points, predict the contribution values of each refined slice to the target grid points, and screen out the effective contribution values that meet the preset requirements.

[0073] Step S40, calculate the sum of the contributions of the effective contribution values at each target grid point, and obtain the doping concentration of each target grid point in the device to be processed.

[0074] It should be noted that the doping concentration is the distribution density of doping elements in the device to be processed. It is one of the important parameters for measuring the performance of the device.

[0075] It can be understood that by accurately calculating the doping concentration, the performance of the device can be better characterized, providing an important basis for the design and optimization of the device, and the accurate doping concentration distribution can help optimize the structure and performance of the device, improving the efficiency and reliability of the device.

[0076] Further, to more efficiently analyze the doping concentration of the device to be processed, step S40 may further include:

[0077] Parallelly calculate the sum of the contributions of each of the target refined slices to the target grid points to obtain the doping concentration of each target grid point in the device to be processed.

[0078] It can be understood that for a complex device structure, parallel computing technology can be adopted to simultaneously process the accumulation of the contribution values of multiple target grid points to improve the efficiency of analyzing the doping concentration.

[0079] This embodiment provides a method for analyzing the doping concentration during ion implantation. Since the background grid can reflect the geometric structure of the device to be processed, in order to accurately reflect the geometric structure of the device to be processed using grid lines, after obtaining the background grid, the background grid is refined to obtain a finer grid (slice grid) so that the background grid can accurately represent the geometric characteristics of the device to be processed. Since each slice region represents a slice, the effective contribution value of the refined slice in each slice region to the target grid point that needs to be doped on the device to be processed can be determined, the sum of the contributions of the effective contribution values of each target refined slice is calculated, and the doping concentration of each target grid point is accurately determined using this sum of contributions. Since the slice grid that can accurately represent the geometric structure of the device to be processed can be obtained by refining the background grid, the simulation error of doping at complex structures can be reduced. Combined with the effective contribution values at each target grid point, the accuracy of the doping concentration obtained during the simulation of device doping is improved, and unnecessary calculations can also be reduced by combining the effective contribution values, improving the calculation efficiency. Therefore, the efficiency and result accuracy in the simulation process of the reference concentration of device doping are improved.

[0080] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar content as in the above-mentioned first embodiment can be referred to the above introduction and will not be repeated hereinafter. On this basis, please refer to Figure 3 , step S30 further includes steps S31 to S33:

[0081] Step S31, mark the target refined slices in the slice grid whose contribution to the target grid point is not zero from the refined slices represented by the slice grid;

[0082] Step S32, based on the Gaussian error function, integrate the geometric relationship between the target refined slice and the target grid point to predict the slice contribution value of each target refined slice to the target grid point;

[0083] Step S33, screen out the effective contribution values that meet the preset requirements from the slice contribution values.

[0084] It should be noted that the refined slices are smaller grid units formed after refinement in the slice grid. These slices can more accurately reflect the geometric details of the device and the distribution of doping points. The target refined slices are the refined slices in the slice grid that are marked as having an actual impact on the target grid points. These slices are the areas that need to be focused on when calculating the doping concentration. The slice contribution value refers to the quantified value of the contribution of each refined slice to the doping concentration of the target grid point, and the slice contribution value can be calculated through the Gaussian error function and the relative position.

[0085] It can be understood that by marking the target refined slices and screening the effective contribution values, the impact of doping points on the target grid points can be evaluated more precisely, thereby improving the accuracy of doping concentration measurement. In addition, through local refinement and contribution value screening, unnecessary calculations are reduced, and the calculation efficiency is significantly improved, thus achieving an optimized balance between accuracy and efficiency, which is applicable to the precise doping control of complex microelectronic devices.

[0086] It can be understood that the slice grid can be flexibly adjusted according to the geometric structure and doping distribution of the device, which is applicable to devices with various complex shapes and doping patterns, improving the universality of ion implantation analysis, and enabling the analysis method of doping concentration during ion implantation to be applicable to any device with a complex geometric structure.

[0087] It can be understood that the specific steps of screening target refined slices, predicting slice contribution values, and screening effective contribution values from the slice grid. The core of these steps lies in accurately calculating the contribution values of each target refined slice to the target grid point through a preset Gaussian error function and screening mechanism, thereby improving the accuracy and efficiency of doping concentration analysis.

[0088] In the specific implementation, refer to Figure 4 , in the slice grid, by analyzing the relative position between the refined slice and the target grid point, mark the target refined slices that have an actual impact on the target grid point. Based on the Gaussian error function, calculate the slice contribution value of each target refined slice to the target grid point. From the calculated slice contribution values, screen out the effective contribution values that meet the preset requirements to improve the calculation accuracy and efficiency by excluding noise and irrelevant contributions.

[0089] Furthermore, step S32 further includes:

[0090] Determine the relative position between each of the target refined slices and the target grid point;

[0091] Based on the relative position and the Gaussian error function, predict the slice contribution value of each of the target refined slices to the target grid point.

[0092] It should be noted that the relative position is the spatial distance and relative direction from the target grid point to the target refined slice; the relative position is used to quantify the influence degree of the doping point on the target grid point and is an important parameter for calculating the slice contribution value. The Gaussian error function is a special function widely used in advanced mathematics and statistical analysis. By calculating the contribution of a single slice to the target grid point through the integration of the Gaussian error function, the calculation efficiency of the effective contribution value can be improved.

[0093] It can be understood that by using the relative position and the preset Gaussian error function to predict the slice contribution value of each target refined slice to the target grid point, the contribution of each target refined slice to the target grid point can be evaluated more accurately, thereby improving the accuracy of doping concentration measurement. Moreover, through the rapid calculation of the relative position and the efficient application of the preset Gaussian error function, the prediction time can be significantly shortened, which is applicable to the analysis of large-scale devices or complex structures and improves the universality of this method.

[0094] In a specific implementation, the relative position between the target refined slice and the target grid point is calculated. Through this distance, the potential influence range of the doping point on the target grid point can be reflected. Then, using a preset Gaussian error function that can be optimized according to factors such as doping concentration distribution and grid density, combined with the relative position, the slice contribution value of each target refined slice to the target grid point is calculated to improve the prediction accuracy.

[0095] Based on the first and second embodiments of the present application, in the third embodiment of the present application, the same or similar content as that in the above-mentioned first embodiment can be referred to the above introduction and will not be repeated hereinafter. On this basis, please refer to Figure 5 , step S20 further includes steps S21 to S24:

[0096] Step S21, based on the relative position relationship between the initial slice characterized by the background grid and the target grid point in the background grid, predict the initial contribution value of each initial slice to the target grid point;

[0097] Step S22, determine whether the initial contribution value meets the preset error requirement;

[0098] Step S23, if the initial contribution value meets the preset error requirement, mark the initial slice corresponding to the initial contribution value;

[0099] Step S24, based on the geometric structure of the device to be processed, perform recursive refinement processing on the marked initial slices in the background grid until the error meets the requirement to obtain the slice grid of the device to be processed.

[0100] It should be noted that the preset error requirement refers to an error threshold set when calculating the initial contribution value. The preset error requirement is used to determine whether the initial contribution value meets the accuracy requirement, so as to decide whether it is necessary to perform recursive refinement processing on this slice.

[0101] It can be understood that by predicting the initial contribution value and screening in combination with the preset error requirement, the area that needs to be further refined is identified, the accuracy of the doping concentration measurement is improved, and then by performing recursive refinement processing only on the initial slices that meet the preset error requirement, the global refinement of the entire background grid is avoided, significantly reducing the computational amount and improving the computational efficiency, and finally achieving an optimized balance between the accuracy of the doping concentration and the measurement efficiency.

[0102] In specific implementation, according to the initial slice characterized by the background grid and the target grid points where the doping points are mapped in the background grid, predict the initial contribution value of each initial slice to the target grid points; then judge whether the initial contribution value meets the preset error contribution value; if the error of the initial contribution value is within the acceptable range, it is considered that the contribution of this slice is accurate enough and no further refinement is required; if the initial contribution value meets the preset error requirement, it is considered that the contribution of this slice is accurately meeting the requirements, so it is necessary to mark this initial slice, and based on the geometric structure of the device to be processed, perform recursive refinement processing on the marked initial slices in the background grid to obtain a finer slice grid, thereby improving the evaluation accuracy of the contribution of the doping points, especially in the area where the doping concentration changes greatly.

[0103] Optionally, step S20 may further include:

[0104] Obtain the refinement area specified by the user;

[0105] Refine the grid to be refined corresponding to the refinement area in the background grid to obtain the slice network of the device to be processed.

[0106] It should be noted that the refinement area specified by the user refers to the area that needs to be grid-refined specified by the user through the interaction interface according to the specific requirements of the device to be processed.

[0107] It can be understood that the user can make flexible adjustments according to the geometric structure and doping distribution of the device to be processed, which is applicable to devices with various complex shapes and doping patterns, and according to the specific requirements and concerns of the device to be processed, flexibly specify the refinement area, enhancing the user's control ability over the analysis process and improving the applicability and flexibility of the technical solution.

[0108] In specific implementation, provide a user interface to allow the user to specify a higher grid density for the key area to meet the higher accuracy requirements in special scenarios.

[0109] It should be noted that the above examples are only for understanding the present application and do not constitute a limitation on the method for analyzing the doping concentration during ion implantation in the present application. Based on this technical concept, more forms of simple transformations are within the protection scope of the present application.

[0110] The present application also provides an analysis software for the doping concentration during ion implantation. Please refer to Figure 6 , and the analysis software for the doping concentration during ion implantation includes:

[0111] An acquisition module 10, configured to acquire the background grid of the device to be processed;

[0112] A refinement module 20, configured to perform a refinement process on the background grid to obtain the sliced grid of the device to be processed;

[0113] A prediction module 30, configured to integrate the geometric relationship between the refined slices characterized by the sliced grid and the target grid points in the sliced grid, and predict the effective contribution values of the refined slices to the target grid points;

[0114] An output module 40, configured to calculate the sum of the contributions of the effective contribution values at each target grid point, and obtain the doping concentration at each target grid point in the device to be processed.

[0115] Optionally, the prediction module 30 is further configured to mark, from the refined slices characterized by the sliced grid, the target refined slices in the sliced grid that contribute non-zero to the target grid points; based on the Gaussian error function, integrate the geometric relationship between the target refined slices and the target grid points, and predict the sliced contribution values of the target refined slices to the target grid points; and screen out the effective contribution values that meet the preset requirements from the sliced contribution values.

[0116] Optionally, the prediction module 30 is further configured to determine the relative positions between the target refined slices and the target grid points; and predict the sliced contribution values of the target refined slices to the target grid points based on the relative positions and the Gaussian error function.

[0117] Optionally, the refinement module 20 is further configured to predict the initial contribution values of the initial slices to the target grid points based on the relative position relationship between the initial slices characterized by the background grid and the target grid points in the background grid; determine whether the initial contribution values meet the preset error requirements; if the initial contribution values meet the preset error requirements, mark the initial slices corresponding to the initial contribution values; and perform a recursive refinement process on the marked initial slices in the background grid based on the geometric structure of the device to be processed until the error meets the requirements, to obtain the sliced grid of the device to be processed.

[0118] Optionally, the output module 40 is further configured to calculate the sum of the contributions of the target refined slices to the target grid points in parallel, and obtain the doping concentration of each target grid point in the device to be processed.

[0119] Optionally, the refinement module 20 is further configured to obtain a user-specified refinement area; refine the to-be-refined grids corresponding to the refinement area in the background grid to obtain a slice network of the device to be processed.

[0120] The analysis software for doping concentration during ion implantation provided by this application adopts the analysis method for doping concentration during ion implantation in the above embodiments, and can solve the technical problem of the decline in the accuracy of the simulation results of the doping reference concentration of the device. Compared with the prior art, the beneficial effects of the analysis software for doping concentration during ion implantation provided by this application are the same as those of the analysis method for doping concentration during ion implantation provided by the above embodiments, and other technical features in the analysis software for doping concentration during ion implantation are the same as those disclosed in the above embodiment method, and will not be elaborated here.

[0121] This application provides an analysis device for doping concentration during ion implantation. The analysis device for doping concentration during ion implantation includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the analysis method for doping concentration during ion implantation in the first embodiment above.

[0122] Reference is made below to Figure 7 , which shows a schematic structural diagram of an analysis device for doping concentration during ion implantation suitable for implementing the embodiments of this application. The analysis device for doping concentration during ion implantation in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7 The analysis device for doping concentration during ion implantation shown is only an example, and should not impose any limitations on the functions and usage scope of the embodiments of this application.

[0123] As Figure 7As shown, the analysis device for doping concentration during ion implantation may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the analysis device for doping concentration during ion implantation are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the analysis device for doping concentration during ion implantation to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows an analysis device for doping concentration during ion implantation with various systems, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems can be alternatively implemented or had.

[0124] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments disclosed in the present application are executed.

[0125] The analysis device for doping concentration during ion implantation provided by the present application adopts the analysis method for doping concentration during ion implantation in the above embodiments, and can solve the technical problem of the decrease in the accuracy of the simulation results of the reference doping concentration of the device. Compared with the prior art, the beneficial effects of the analysis device for doping concentration during ion implantation provided by the present application are the same as those of the analysis method for doping concentration during ion implantation provided by the above embodiments, and other technical features in the analysis device for doping concentration during ion implantation are the same as those disclosed in the method of the previous embodiment, and will not be elaborated here.

[0126] It should be understood that each part disclosed in this application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0127] As described above, the above are only specific embodiments of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0128] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the method for analyzing doping concentration during ion implantation in the above embodiments.

[0129] The computer-readable storage medium provided by this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0130] The above computer-readable storage medium can be included in the analysis device for doping concentration during ion implantation; it can also exist separately and not be assembled into the analysis device for doping concentration during ion implantation.

[0131] The above computer-readable storage medium carries one or more programs, which, when executed by an analysis device for doping concentration during ion implantation, cause the analysis device for doping concentration during ion implantation to: obtain a background grid of a device to be processed; refine the background grid to obtain a sliced grid of the device to be processed; integrate the geometric relationship between the refined slices characterized by the sliced grid and target grid points in the sliced grid to predict the effective contribution values of the refined slices to the target grid points; calculate the sum of the contribution values of the effective contribution values at each of the target grid points to obtain the doping concentration at each target grid point in the device to be processed.

[0132] Computer program code for performing the operations of the present application may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may execute entirely on the user's computer, partially on the user's computer, execute as a stand-alone software package, execute partially on the user's computer and partially on a remote computer, or execute entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (for example, by connecting through an Internet service provider using the Internet).

[0133] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0134] The modules involved in the embodiments of the present application can be implemented in software or in hardware. In some cases, the name of the module does not constitute a limitation on the unit itself.

[0135] The readable storage medium provided by the present application is a computer-readable storage medium. The computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned analysis method of doping concentration during ion implantation, and can solve the technical problem of the decrease in the accuracy of the simulation results of the doping reference concentration of the device. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as those of the analysis method of doping concentration during ion implantation provided by the above embodiments, and will not be elaborated here.

[0136] The present application also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned analysis method of doping concentration during ion implantation are implemented.

[0137] The computer program product provided by the present application can solve the technical problem of the decrease in the accuracy of the simulation results of the doping reference concentration of the device. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the analysis method of doping concentration during ion implantation provided by the above embodiments, and will not be elaborated here.

[0138] The above are only some embodiments of the present application, and do not limit the patent scope of the present application. All equivalent structural transformations made under the technical concept of the present application by using the content of the specification and drawings of the present application, or directly / indirectly applied to other related technical fields, are included in the patent protection scope of the present application.

Claims

1. A method for analyzing doping concentration during ion implantation, characterized in that: The method includes: Get the background grid of the device to be processed; Refining the background grid to obtain a slice grid of the device to be processed; Integrate the geometric relationship between the refined slices represented by the slice grid and the target grid points in the slice grid, and predict the effective contribution value of each of the refined slices to the target grid points; The contribution sum of the effective contribution values ​​at each of the target grid points is calculated to obtain the doping concentration of each target grid point in the device to be processed.

2. The method according to claim 1, characterized in that The step of integrating the geometric relationship between the refined slices represented by the slice grid and the target grid points in the slice grid to predict the effective contribution value of each refined slice to the target grid point comprises: From the refined slices represented by the slice grid, marking the target refined slices in the slice grid whose contribution to the target grid point is not zero; Based on a Gaussian error function, integrating the geometric relationship between the target refined slice and the target grid point, and predicting a slice contribution value of each target refined slice to the target grid point; Filter valid contribution values ​​that meet preset requirements from the slice contribution values.

3. The method according to claim 2, characterized in that The step of integrating the geometric relationship between the target refined slice and the target grid point based on the Gaussian error function and predicting the slice contribution value of each target refined slice to the target grid point comprises: Determining the relative position between each of the target refined slices and the target grid point; Based on the relative position and the Gaussian error function, a slice contribution value of each of the target refined slices to the target grid point is predicted.

4. The method according to claim 1, characterized in that The step of refining the background grid to obtain the slice grid of the device to be processed comprises: Based on the relative position relationship between the initial slices represented by the background grid and the target grid points in the background grid, predicting the initial contribution value of each of the initial slices to the target grid points; Determining whether the initial contribution value meets a preset error requirement; If the initial contribution value meets the preset error requirement, marking the initial slice corresponding to the initial contribution value; Based on the geometric structure of the device to be processed, the initial slices marked in the background grid are recursively refined until the error meets the requirement, thereby obtaining the slice grid of the device to be processed.

5. The method according to claim 1, characterized in that The step of calculating the contribution sum of the effective contribution values ​​at each of the target grid points to obtain the doping concentration of each target grid point in the device to be processed comprises: The sum of contributions of each of the target refined slices to the target grid point is calculated in parallel to obtain the doping concentration of each target grid point in the device to be processed.

6. The method according to claim 1, characterized in that The step of refining the background grid to obtain the slice grid of the device to be processed also includes: Get the user-specified refinement area; The grid to be refined in the background grid corresponding to the refined area is refined to obtain a slice network of the device to be processed.

7. An analysis software for doping concentration during ion implantation, characterized in that: The software includes: An acquisition module, used for acquiring a background grid of a device to be processed; A refinement module, used for refining the background grid to obtain a slice grid of the device to be processed; A calculation module, used for integrating the geometric relationship between the refined slices represented by the slice grid and the target grid points in the slice grid, and predicting the effective contribution value of each of the refined slices to the target grid points; The output module is used to calculate the contribution sum of the effective contribution values ​​at each of the target grid points to obtain the doping concentration of each target grid point in the device to be processed.

8. An analysis device for doping concentration during ion implantation, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the method for analyzing doping concentration during ion implantation according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the method for analyzing doping concentration during ion implantation according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the method for analyzing doping concentration during ion implantation according to any one of claims 1 to 6 are implemented.

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