A method and system for automatically optimizing parameters for OPC model verification

Abstract

The present invention provides a method and system for automatically optimizing parameters for OPC model verification, the system at least comprising: a parameter input module for inputting inline exposure conditions and inline exposure data files; a focus data analysis module for generating fitting curves and tables for focus data analysis; an energy data analysis module for generating fitting curves and tables for energy data analysis; a graphical display module for graphically displaying the fitting curves of the focus data analysis module and the energy data analysis module; and an optimal exposure parameter generation module for optimizing parameters and generating optimal focus data and dose data. The present invention greatly improves the accuracy, processing speed and efficiency of OPC model verification, while avoiding the occurrence of various errors in model verification caused by manual operation errors, and has very good application prospects.

Description

Technical Field

[0001] The invention belongs to the technical field of OPC model verification, and in particular relates to a parameter automatic optimization method and system for OPC model verification. Background Art

[0002] As semiconductor process nodes continue to shrink, especially as 40nm and below process nodes gradually become mainstream products, OPC (optical proximity correction) has become an indispensable and important part of the semiconductor process. An accurate OPC model is a prerequisite for OPC correction, and OPC model verification is an indispensable and important part of testing the accuracy of the OPC model. The quality of model verification is directly related to the success of the final product mass production. At present, OPC model verification mainly relies on the personal experience of OPC engineers, and the exposure-related parameters are obtained by manually analyzing and calculating the data. This is not only time-consuming and labor-intensive, but also often has poor accuracy and consistency in parameter calculation, and is prone to errors, resulting in large errors in subsequent data measurement after exposure, which may eventually lead to model verification failure, so it can only start from scratch, resulting in project delays and waste of resources.

[0003] Therefore, providing a method and system for automatically optimizing parameters for OPC model verification is a problem that needs to be solved by those skilled in the art. Summary of the invention

[0004] In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a method and system for automatically optimizing parameters for OPC model verification, so as to solve the problem that manual OPC model verification in the prior art is time-consuming, labor-intensive and inaccurate.

[0005] To achieve the above-mentioned and other related purposes, the present invention provides a parameter automatic optimization system for OPC model verification, the system at least comprising:

[0006] Parameter input module, used for inputting inline exposure conditions and inline exposure data files;

[0007] A focus data analysis module, connected to the parameter input module, for generating a fitting curve and table for focus data analysis;

[0008] An energy data analysis module, connected to the parameter input module, for generating a fitting curve and table for energy data analysis;

[0009] A graphical display module, connected to the focus data analysis module and the energy data analysis module, for graphically displaying the fitting curves of the focus data analysis module and the energy data analysis module;

[0010] The optimal exposure parameter generation module is connected to the focus data analysis module and the energy data analysis module, and is used for parameter optimization and generating optimal focus data and dose data.

[0011] Optionally, the inline exposure conditions include a focus step, a focus center value, a dose step and a dose center value.

[0012] Optionally, the inline exposure data file includes a data type, a data area size, and a target energy.

[0013] Optionally, the optimal exposure parameter generation module optimizes the algorithm module parameters and generates optimal focus data and dose data.

[0014] The present invention also provides a method for automatically optimizing parameters for OPC model verification, the method at least comprising:

[0015] Use the parameter input module to input inline exposure conditions and inline exposure data files;

[0016] According to the inline exposure condition and the inline exposure data file, a focus data analysis module generates a fitting curve and a table for focus data analysis;

[0017] According to the inline exposure condition and the inline exposure data file, an energy data analysis module generates a fitting curve and a table for energy data analysis;

[0018] Using a graphical display module to graphically display the fitting curves of the focus data analysis module and the energy data analysis module;

[0019] The optimal exposure parameter generation module is used to optimize parameters and generate optimal focus data and dose data.

[0020] Optionally, the inline exposure conditions include a focus step, a focus center value, a dose step and a dose center value.

[0021] Optionally, the inline exposure data file includes a data type, a data area size, and a target energy.

[0022] Optionally, the graphical display module uses different fillings to mark the fitting curves of the focus data analysis module and the energy data analysis module to facilitate intuitive inspection of data validity.

[0023] Optionally, the optimal exposure parameter generation module performs parameter optimization through an algorithm and generates optimal focus data and dose data.

[0024] As described above, the automatic parameter optimization method and system for OPC model verification of the present invention have the following beneficial effects:

[0025] The system has the characteristics of simple operation, automatic parameter generation, graphical display, intelligent calculation, process-based, rapid positioning of test errors, high processing efficiency and accuracy, etc. It can minimize human errors and greatly reduce the burden of manual calculation. At present, the method and system of the invention have been applied to the OPC model verification of multiple products. After practical verification, it can greatly improve the accuracy, processing speed and efficiency of OPC model verification, and avoid the occurrence of various errors in model verification caused by human operation errors, and has very good application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a structural schematic diagram of the automatic parameter optimization system for OPC model verification of the present invention.

[0027] Figure 2 The figure is a flow chart of the automatic parameter optimization method for OPC model verification according to the present invention.

[0028] Figure 3 It is a schematic diagram of algorithm execution of the automatic parameter optimization method for OPC model verification of the present invention.

[0029] Figures 4 to 14 These are the curves and table images from the model verification step for the M2 layer of a product in a specific case. DETAILED DESCRIPTION

[0030] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0031] Please refer to the attached drawings. It should be noted that the illustrations provided in this embodiment are only used to illustrate the basic concept of the present invention in a schematic manner, and the drawings only show the components related to the present invention rather than the number, shape and size of the components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0032] like Figure 1 As shown, the present invention provides a parameter automatic optimization system for OPC model verification, the system at least comprising: a parameter input module 1, a focus data analysis module 2, an energy data analysis module 3, a graphical display module 4 and an optimal exposure parameter generation module 5.

[0033] The parameter input module 1 is used for inputting inline exposure conditions and inline exposure data files. In the present invention, the inline means "online".

[0034] The parameter input module 1 mainly includes the OPC model verification inline exposure condition input function and the inline exposure data file and related information input function. The former mainly inputs the inline exposure center conditions, including focus and dose step and center value, and the latter mainly inputs the inline data file name (such as CDSEM FULLMAP), data type, data area size and target energy.

[0035] The focus data analysis module 2 is connected to the parameter input module 1 and is used to generate a fitting curve and table for focus data analysis.

[0036] The function of the focus data analysis module 2 is mainly to automatically generate a focus data analysis table; calculate the focus sequence according to the inline exposure CDSEM FULLMAP data and the focus center value and step length, and then calculate the quadratic curve fitting of the focus under different dose conditions, and sum its coefficients with R 2 The values ​​are automatically filled into the focus data analysis module table, and the average values ​​of different focuses are calculated; each focus curve data is automatically analyzed, and the data with the largest fitting error is found and marked with different colors in the CDSEM data table, and the data with R2<0.90 is marked with different colors in the generated focus data table; the CDSEM FULLMAP data file containing focus data with multiple different anchor points can be processed simultaneously.

[0037] The energy data analysis module 3 is connected to the parameter input module 1 and is used to generate a fitting curve and table for energy data analysis.

[0038] The energy data analysis module 3 is mainly used to automatically generate energy data analysis tables; calculate the dose sequence according to the inline exposure CDSEM FULLMAP data and the dose center value and step length, and then calculate the linear fitting of dose under different focus conditions, and compare its coefficients with R 2 The values ​​are automatically filled into the energy data analysis module table, and the average dose is calculated. Each energy linear data (energy linear data) is automatically analyzed, and the data with the largest fitting error is found and marked with different colors in the CDSEM data table. At the same time, the R values ​​are marked with different colors in the generated energy data table.2 Data <0.90.

[0039] The graphical display module 4 is connected to the focus data analysis module 2 and the energy data analysis module 3 , and is used to graphically display the fitting curves of the focus data analysis module 2 and the energy data analysis module 3 .

[0040] The function of the graphical display module 4 is to graphically display the series of focus and series of dose fitting curves generated by the focus data analysis module 2 and the energy data analysis module 3, and mark them with different colors and icon filling to facilitate intuitive inspection of data validity.

[0041] The optimal exposure parameter generation module 5 is connected to the focus data analysis module 2 and the energy data analysis module 3, and is used for parameter optimization and generating optimal focus data and dose data.

[0042] The optimal exposure parameter generation module 5 automatically performs parameter optimization and generates the final optimal focus data (best focus) and optimal dose data (best dose) through a set of intelligent algorithms based on the series of focus and dose curve parameter data obtained by the focus data analysis module 2 and the energy data analysis module 3, taking into account the validity of the CDSEM data (which may include focus CDSEM data of multiple different anchor points), the distribution characteristics of the CDSEM data and the inline exposure parameters.

[0043] As an example, the optimal exposure parameter generating module 5 optimizes the algorithm module parameters and generates the optimal focus data and dose data.

[0044] like Figure 2 As shown, the present invention also provides a parameter automatic optimization method for OPC model verification, which is implemented by the above system and includes at least the following steps:

[0045] First, step S1 is performed to input inline exposure conditions and inline exposure data files using parameter input module 1;

[0046] Then, step S2 is performed, wherein the focus data analysis module 2 generates a fitting curve and a table for focus data analysis according to the inline exposure condition and the inline exposure data file;

[0047] Then, step S3 is executed, and according to the inline exposure condition and the inline exposure data file, the energy data analysis module 3 generates a fitting curve and a table for energy data analysis;

[0048] Then, step S4 is performed to graphically display the fitting curves of the focus data analysis module 2 and the energy data analysis module 3 using the graphical display module 4;

[0049] Finally, step S5 is executed to use the optimal exposure parameter generation module 5 to perform parameter optimization and generate optimal focus data and dose data.

[0050] like Figure 3 It is a schematic diagram showing the algorithm execution of the automatic parameter optimization method for OPC model verification according to the present invention.

[0051] Furthermore, the optimal exposure parameter generation module 5 performs parameter optimization through an algorithm and generates optimal focus data and dose data.

[0052] The algorithm steps of the optimal exposure parameter generation module are as follows:

[0053] 1. Optimal focus optimization algorithm:

[0054] a) Calculate the quadratic function fitting curve for each column in the full map data table and obtain its symmetry axis series F i and R i 2 , i=1...n, n is the number of columns; the "full map" in the present invention refers to the entire wafer area.

[0055] b) According to different R i 2 Calculate the weight T according to the table below i ;

[0056]

[0057] c) Calculate the weight U according to the table below according to different columns i ;

[0058]

[0059] d) Calculate the weight WF according to the following formula i And the optimal exposure focal length F.

[0060] WFi=Ti*Ui

[0061] F=(F1*WF1+F2*WF2+…+Fn*WFn) / (WF1+WF2+…+WFn), n=1…9

[0062] 2. Optimal dose optimization algorithm:

[0063] a) Calculate the linear fitting curve for each row in the full map data table and obtain its symmetry axis series D i and R i2 , i = 1…n, n is the number of columns;

[0064] b) According to different R i 2 Calculate the weight D according to the following table i ;

[0065]

[0066] c) Calculate the weight V according to the table below according to different rows i ;

[0067]

[0068] d) Calculate the weight WD according to the following formula: i and the optimal exposure dose D.

[0069] WDi=Di*Vi

[0070] D=(D1*WD1+D2*WD2+…+Dn*WDn) / (WD1+WD2+…+WDn), n=1…9

[0071] The significant advantage of this algorithm is that it takes into account both the distribution of full map data and the validity of the data, obtains the comprehensive weighting coefficient of the optimal exposure parameters, and then performs weighted averaging to obtain the Best Focus and Best Dose parameters. This not only takes into account the validity of the full map data itself and automatically weakens the weight of data with large measurement errors, but also automatically adjusts the weight of intermediate data to be higher than non-intermediate data according to the actual distribution of the full map data. The optimal Best Focus and Best Dose parameters are finally obtained, so the credibility is very high. Practical verification has also confirmed the effectiveness of this method.

[0072] The following takes the model verification of the M2 layer of a certain product as an example to illustrate the specific implementation method of the present invention.

[0073] 1) Parameter input.

[0074] like Figure 4 As shown in the figure, the CDSEM FULLMAP data file after Inline exposure contains 3 focus type anchor point data and 1 energy type data table.

[0075] After the parameter input is completed, open the CDSEM data file "M2-FEM_ANCHOR-1.xlsm", and automatically calculate and analyze the optimal focus or optimal dose for the four sheets according to the type of each sheet data, such as focus and energy. After the analysis is completed, a dialog box pops up to prompt that the analysis process is completed, and the analysis result chart is output.

[0076] 2) Analysis results of the 3 focus data.

[0077] A)1D-80-280-PRE

[0078] like Figure 5 and Figure 6 Shown are the corresponding focus data analysis module table and fitting curve. Figure 7 The table shown can mark the data with the largest fitting error.

[0079] In addition to calculating the focus value in each dose column, the system also marks the R value in each dose column. 2 <0.9 and R 2 The maximum error of CDSEM FULLMAP data is less than 0.8, which makes it easier for users to check their exposure images and decide whether to process (modify or delete) the data. After the data processing is completed, the calculation can be repeated to obtain new calculation results.

[0080] B) IL-68

[0081] like Figure 8 and Fig. 9 Shown are the corresponding focus data analysis module table and fitting curve.

[0082] C) IS-68

[0083] like Fig.10 and Fig.11 Shown are the corresponding focus data analysis module table and fitting curve.

[0084] 3) Energy data analysis results:

[0085] like Fig.12 and Fig.13 Shown are the corresponding energy data analysis module table and fitting curve.

[0086] 4) The final best focus and best dose analysis results are as follows: Fig.14 As shown in the table.

[0087] according to Fig.14The FEM / EM measurement data obtained by the focus and dose and step size parameter combinations in the table are measured after exposure. The wafer data is accurate and effective, and the OPC model verification work is successfully completed in one go. The entire calculation process can be completed within 10 seconds on an ordinary desktop computer (Intel 3.2GHz main frequency, 2GB memory desktop computer) (experienced engineers need more than 1 hour to process, and are prone to errors), which greatly improves the efficiency of model verification.

[0088] In summary, the present invention provides a method and system for automatically optimizing parameters for OPC model verification, which automatically generates relevant exposure parameters through a set of intelligent algorithms and can graphically display the analysis results. The system has the function of quickly locating and finding potential test errors, and can greatly improve the efficiency and accuracy of OPC model verification data processing, thereby minimizing human errors and greatly reducing the burden of manual calculations.

[0089] Therefore, the present invention effectively overcomes various shortcomings in the prior art and has high industrial utilization value.

[0090] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A parameter automatic optimization system for OPC model verification, characterized in that: The system comprises at least: Parameter input module, used for inputting inline exposure conditions and inline exposure data files; A focus data analysis module, connected to the parameter input module, for generating a fitting curve and table for focus data analysis; An energy data analysis module, connected to the parameter input module, for generating a fitting curve and table for energy data analysis; A graphical display module, connected to the focus data analysis module and the energy data analysis module, for graphically displaying the fitting curves of the focus data analysis module and the energy data analysis module; The optimal exposure parameter generation module is connected to the focus data analysis module and the energy data analysis module, and is used for parameter optimization and generating optimal focus data and dose data.

2. The automatic parameter optimization system for OPC model verification according to claim 1, characterized in that: The inline exposure conditions include a focus step length, a focus center value, a dose step length, and a dose center value.

3. The automatic parameter optimization system for OPC model verification according to claim 1, characterized in that: The inline exposure data file includes data type, data area size and target energy.

4. The automatic parameter optimization system for OPC model verification according to claim 1, characterized in that: The optimal exposure parameter generation module optimizes the algorithm module parameters and generates optimal focus data and dose data.

5. A method for automatic parameter optimization for OPC model verification, characterized in that: The method at least comprises: Use the parameter input module to input inline exposure conditions and inline exposure data files; According to the inline exposure condition and the inline exposure data file, a focus data analysis module generates a fitting curve and a table for focus data analysis; According to the inline exposure condition and the inline exposure data file, an energy data analysis module generates a fitting curve and a table for energy data analysis; Using a graphical display module to graphically display the fitting curves of the focus data analysis module and the energy data analysis module; The optimal exposure parameter generation module is used to optimize parameters and generate optimal focus data and dose data.

6. The automatic parameter optimization method for OPC model verification according to claim 5, characterized in that: The inline exposure conditions include a focus step length, a focus center value, a dose step length, and a dose center value.

7. The automatic parameter optimization method for OPC model verification according to claim 5, characterized in that: The inline exposure data file includes data type, data area size and target energy.

8. The automatic parameter optimization method for OPC model verification according to claim 5, characterized in that: The graphical display module uses different fillings to mark the fitting curves of the focus data analysis module and the energy data analysis module, so as to facilitate intuitive inspection of data validity.

9. The automatic parameter optimization method for OPC model verification according to claim 5, characterized in that: The optimal exposure parameter generation module performs parameter optimization through an algorithm and generates optimal focus data and dose data.

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