Finite element-based semiconductor element performance evaluation method and system

Abstract

The invention discloses a semiconductor element performance evaluation method and system based on a finite element, and relates to the technical field of finite element analysis. According to the semiconductor element performance evaluation method based on the finite element, an optimal test scheme is determined; applying the optimal test scheme to a to-be-tested semiconductor element finite element model stored in a database, and obtaining to-be-evaluated thermal characteristic data of the to-be-tested semiconductor element finite element model; according to the method, thermal performance evaluation is performed on a to-be-tested semiconductor element corresponding to the to-be-tested semiconductor element finite element model based on to-be-evaluated thermal characteristic data, and the performance change and failure risk of the element under different thermal loads can be predicted by accurately simulating thermal distribution and physical expansion conditions of the element under actual working conditions; the problems about thermal management and reliability of elements in the semiconductor manufacturing process can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of finite element analysis, and in particular to a semiconductor component performance evaluation method and system based on finite elements. Background Art

[0002] The performance evaluation of semiconductor components is a key step to ensure their reliable operation in various applications, including but not limited to electrical performance testing, physical performance testing, thermal performance testing, and mechanical performance testing.

[0003] However, existing semiconductor component performance evaluation methods usually test them separately, which makes it difficult to evaluate thermal and mechanical properties in combination during the manufacturing process. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides a semiconductor component performance evaluation method and system based on finite elements, which solves the thermal management and reliability problems of components in the semiconductor manufacturing process.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a finite element-based semiconductor component performance evaluation method, comprising the following steps: determining an optimal test scheme; applying the optimal test scheme to a finite element model of a semiconductor component to be tested stored in a database, obtaining thermal characteristic data to be evaluated of the finite element model of the semiconductor component to be tested, the thermal characteristic data to be evaluated including thermal distribution data to be evaluated and expansion data to be evaluated, the thermal distribution data to be evaluated including temperature values ​​to be evaluated of each analysis unit, and the expansion data to be evaluated including expansion rates to be evaluated and shrinkage rates to be evaluated of each analysis unit; and performing thermal performance evaluation on the semiconductor component to be tested corresponding to the finite element model of the semiconductor component to be tested based on the thermal characteristic data to be evaluated.

[0006] Furthermore, determining the best test scheme includes the following steps: obtaining a standard semiconductor component finite element model stored in a database; obtaining several test schemes stored in the database, and applying each test scheme to the standard semiconductor component finite element model; obtaining thermal characteristic evaluation data after each test scheme is applied to the standard semiconductor component finite element model, the thermal characteristic evaluation data including thermal distribution characteristic data and expansion characteristic data; obtaining required thermal characteristic data stored in the database, the required thermal characteristic data including thermal distribution requirement data and expansion requirement data; comparing the thermal characteristic evaluation data corresponding to each test scheme with the required thermal characteristic data one by one to determine the most similar thermal characteristic evaluation data; defining the test scheme corresponding to the most similar thermal characteristic evaluation data as the best test scheme.

[0007] Furthermore, the thermal characteristic evaluation data corresponding to each test scheme is compared with the required thermal characteristic data one by one to determine the most similar thermal characteristic evaluation data, including the following steps: the thermal distribution characteristic data of each thermal characteristic evaluation data is compared with the thermal distribution requirement data one by one to determine the thermal distribution compliance coefficient, the thermal distribution characteristic data includes the temperature value of each analysis unit, and the thermal distribution requirement data includes the temperature requirement value of each analysis unit; the expansion characteristic data of each thermal characteristic evaluation data is compared with the expansion requirement data one by one to determine the expansion compliance coefficient, the expansion characteristic data includes the expansion rate and the shrinkage rate of each analysis unit, and the expansion requirement data includes the expansion requirement rate and the shrinkage requirement rate of each analysis unit; each thermal distribution compliance coefficient is superimposed with the corresponding expansion compliance coefficient to determine the similarity index; the thermal characteristic evaluation data corresponding to the smallest similarity index is determined as the most similar thermal characteristic evaluation data.

[0008] Furthermore, the method for obtaining the similarity index is:

[0009] Xs = ln(1+wx+px);

[0010] Where Xs is the similarity index, wx is the thermal distribution compliance coefficient, and px is the expansion compliance coefficient.

[0011] Furthermore, a thermal performance evaluation is performed on the semiconductor element to be tested corresponding to the finite element model of the semiconductor element to be tested based on the thermal characteristic data to be evaluated, comprising the following steps: obtaining defined thermal characteristic data stored in a database, wherein the defined thermal characteristic data include thermal distribution defined data and expansion defined data; comparing the thermal characteristic data to be evaluated with the defined thermal characteristic data to obtain a comparison coefficient; and performing a thermal performance evaluation on the semiconductor element to be tested based on the comparison coefficient, wherein the evaluation results are that the thermal performance evaluation of the semiconductor element to be tested is unqualified and the thermal performance evaluation of the semiconductor element to be tested is qualified.

[0012] Furthermore, obtaining defined thermal characteristic data stored in a database includes the following steps: applying the best test scheme to multiple standard semiconductor component finite element models to obtain parameterized thermal characteristic data corresponding to each standard semiconductor component finite element model; performing mean processing on the parameterized thermal characteristic data to obtain the temperature average value of each analysis unit, the expansion rate average value and the shrinkage rate average value of each analysis unit; defining the temperature average value of each analysis unit as thermal distribution definition data, and defining the expansion rate average value and the shrinkage rate average value of each analysis unit as expansion definition data.

[0013] Furthermore, the parameterized thermal characteristic data include parameterized thermal distribution data and parameterized expansion data, the parameterized thermal distribution data include temperature parameter values ​​of each analysis unit, and the parameterized expansion data include parameterized expansion rates and parameterized retraction rates of each analysis unit.

[0014] Furthermore, the method for obtaining the comparison coefficient is as follows:

[0015]

[0016] Where i is the number of the analysis unit, i = 1, 2, 3, ..., n, n is the total number of analysis units, Wd i is the temperature value to be evaluated of the i-th analysis unit, Pd i is the expansion rate to be evaluated of the ith analysis unit, Hd is the retraction rate to be evaluated, Wp i is the average temperature of the ith analysis unit, Pp i is the average expansion rate of the ith analysis unit, Hp i is the average value of the i-th retraction rate, and Bx is the comparison coefficient.

[0017] Furthermore, a thermal performance evaluation of the semiconductor component to be tested is performed based on the comparison coefficient, comprising the following steps: determining whether the comparison coefficient is greater than a comparison threshold stored in a database: if the comparison coefficient is greater than the comparison threshold stored in the database, the thermal performance evaluation of the semiconductor component to be tested corresponding to the comparison coefficient is unqualified; if the comparison coefficient is not greater than the comparison threshold stored in the database, the thermal performance evaluation of the semiconductor component to be tested corresponding to the comparison coefficient is qualified.

[0018] A semiconductor component performance evaluation system based on finite elements comprises a scheme determination module, a data acquisition module and an evaluation module, wherein: the scheme determination module is used to determine an optimal test scheme; the data acquisition module is used to apply the optimal test scheme to a finite element model of a semiconductor component to be tested stored in a database, and obtain thermal characteristic data to be evaluated of the finite element model of the semiconductor component to be tested, wherein the thermal characteristic data to be evaluated comprises thermal distribution data to be evaluated and expansion data to be evaluated, wherein the thermal distribution data to be evaluated comprises temperature values ​​to be evaluated of each analysis unit, and wherein the expansion data to be evaluated comprises expansion rates to be evaluated and shrinkage rates to be evaluated of each analysis unit; and the evaluation module is used to perform thermal performance evaluation on the semiconductor component to be tested corresponding to the finite element model of the semiconductor component to be tested based on the thermal characteristic data to be evaluated.

[0019] The present invention has the following beneficial effects:

[0020] This finite element-based semiconductor component performance evaluation method can predict the performance changes and failure risks of components under different thermal loads by accurately simulating the thermal distribution and physical expansion of components under actual working conditions. It can solve the thermal management and reliability issues of components in the semiconductor manufacturing process.

[0021] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of the semiconductor component performance evaluation method based on finite element method of the present invention.

[0023] Figure 2 This is a flowchart of the semiconductor component performance evaluation system based on finite elements of the present invention. DETAILED DESCRIPTION

[0024] The embodiment of the present application adopts a semiconductor component performance evaluation method and system based on finite elements, and accurately simulates the thermal distribution and physical expansion of the component under actual working conditions. The method can predict the performance changes and failure risks of the component under different thermal loads, and can solve the thermal management and reliability issues of the component in the semiconductor manufacturing process.

[0025] See also Figure 1 , an embodiment of the present invention provides a technical solution: a semiconductor component performance evaluation method based on finite elements, comprising the following steps: determining the best test scheme; this step involves selecting appropriate simulation parameters and test conditions to ensure that the evaluation can accurately reflect the various situations that the semiconductor components may encounter in actual use, wherein the test scheme is a combination of different allowable currents and different allowable ambient temperatures.

[0026] The best test scheme is applied to the finite element model of the semiconductor component to be tested stored in the database, and the thermal characteristic data to be evaluated of the finite element model of the semiconductor component to be tested is obtained, wherein the thermal characteristic data to be evaluated includes thermal distribution data to be evaluated and expansion data to be evaluated, the thermal distribution data to be evaluated includes the temperature value to be evaluated of each analysis unit, and the expansion data to be evaluated includes the expansion rate to be evaluated and the shrinkage rate to be evaluated of each analysis unit; based on the thermal characteristic data to be evaluated, the thermal performance of the semiconductor component to be tested corresponding to the finite element model of the semiconductor component to be tested is evaluated.

[0027] By applying these test scenarios on pre-established finite element models, data on the behavior of components under specific conditions, such as thermal distribution and physical expansion, can be obtained. Collect component thermal characteristic data, including thermal distribution data and expansion data, which are obtained by simulating the component response to test conditions. Finally, the thermal performance of semiconductor components is evaluated based on this data to determine their performance and reliability under actual operating conditions.

[0028] Finite element analysis can be used to very accurately simulate the response of semiconductor components under various environmental conditions, helping to predict the performance of the components in actual applications. Through this evaluation, designers can identify potential weaknesses in the design and make improvements to optimize its performance and reliability in the initial design stage of the product.

[0029] Specifically, determining the best test scheme includes the following steps: obtaining a standard semiconductor component finite element model stored in a database; obtaining several test schemes stored in the database, and applying each test scheme to the standard semiconductor component finite element model; obtaining thermal characteristic evaluation data after each test scheme is applied to the standard semiconductor component finite element model, the thermal characteristic evaluation data including thermal distribution characteristic data and expansion characteristic data; obtaining required thermal characteristic data stored in the database, the required thermal characteristic data including thermal distribution requirement data and expansion requirement data; comparing the thermal characteristic evaluation data corresponding to each test scheme with the required thermal characteristic data one by one, and determining the most similar thermal characteristic evaluation data; defining the test scheme corresponding to the most similar thermal characteristic evaluation data as the best test scheme.

[0030] In this embodiment, first, a finite element model of a stored standard semiconductor component is extracted from a database. This step ensures that all tests are performed based on a unified and standardized model to maintain consistency and comparability of the evaluation. Multiple test schemes stored in the database are applied to this standard model. Each test scheme may involve different environmental conditions, operating conditions, or thermal loads to simulate different actual application scenarios. The thermal characteristics of each model to which the test scheme is applied are evaluated, including thermal distribution and physical expansion. These data reflect the behavior of the model under specific test conditions. The thermal characteristics requirements in the design and safety specifications are extracted from the database, which include thermal distribution and expansion standards that must be met.

[0031] The obtained thermal characteristic evaluation data is compared with the required thermal characteristic data to find the test result closest to the required data. Based on the comparison results, the test scheme that is most similar to the required thermal characteristic data is selected as the best scheme, which is used as a reference for future design and manufacturing.

[0032] Ensure that the selected test solution can most accurately simulate the conditions that the product may encounter in actual use, thereby improving the practicality and reliability of the product design. Choosing the best test solution can reduce unnecessary testing and rework, save time and resources, and reduce development costs.

[0033] Specifically, the thermal characteristic evaluation data corresponding to each test scheme is compared with the required thermal characteristic data one by one to determine the most similar thermal characteristic evaluation data, including the following steps: the thermal distribution characteristic data of each thermal characteristic evaluation data is compared with the thermal distribution requirement data one by one to determine the thermal distribution compliance coefficient, the thermal distribution characteristic data includes the temperature value of each analysis unit (by solving the heat conduction equation (usually Fourier's heat conduction law), calculating the temperature distribution inside and on the surface of the component under the test scheme), and the thermal distribution requirement data includes the temperature requirement value of each analysis unit.

[0034]

[0035] Where i is the number of the thermal characteristics evaluation data, j is the number of the analysis unit, j = 1, 2, 3, ..., m, m is the total number of analysis units, Wsd ij is the temperature value of the jth analysis unit of the ith thermal distribution characteristic data, Wsy j is the temperature requirement value of the jth analysis unit of the thermal distribution requirement data, wx i is the i-th thermal distribution compliance coefficient. It evaluates the degree of deviation between the actual thermal distribution in the test plan and the thermal distribution required by the design. Since thermal management is a key factor in the performance and reliability of semiconductor devices, this parameter is crucial. Thermal distribution directly affects the performance and life of semiconductors, so it must be accurately controlled and monitored.

[0036] The expansion characteristic data of each thermal characteristic evaluation data are compared with the expansion requirement data one by one to determine the expansion compliance coefficient. The expansion characteristic data include the expansion rate and shrinkage rate of each analysis unit. The expansion requirement data include the expansion requirement rate (obtained by calculating the increase in component size during the simulation time and dividing it by the time) and the shrinkage requirement rate (the rate of size reduction is also calculated during the cooling process) of each analysis unit.

[0037]

[0038] In the formula, Psd ij is the expansion rate of the jth analysis unit of the i-th expansion characteristic data, Hsd ij is the retraction rate of the jth analysis unit of the i-th expansion characteristic data, Psy j is the required expansion rate of the jth analysis unit, Hsy j The required rate of retraction of the jth analysis unit. Evaluate how well the structural deformation caused by thermal expansion and other physical changes complies with the design requirements. The physical stability of semiconductor devices during operation is equally important to their performance and durability. Expansion and retraction are directly related to the mechanical stress and long-term stability of the components.

[0039] Each thermal distribution compliance coefficient is superimposed with the corresponding expansion compliance coefficient to determine a similarity index; the thermal characteristic evaluation data corresponding to the smallest similarity index is determined as the most similar thermal characteristic evaluation data.

[0040] The method to obtain the similarity index is:

[0041] Xs i =ln(1+wx i +px i );

[0042] Where Xs is the i-th similarity index. It provides a metric that takes into account both thermal and physical properties to evaluate and compare the overall compliance of different test schemes. It helps designers make more comprehensive decisions by comprehensively considering all key performance parameters.

[0043] In this embodiment, for the thermal characteristic evaluation data generated by each test scheme, its thermal distribution characteristic data (the actual temperature value of each analysis unit) is compared with the preset thermal distribution requirement data (the target temperature value of each analysis unit). The thermal distribution compliance coefficient is obtained by calculating the square root of the sum of the squares of the temperature deviations of all analysis units in each scheme. Similarly, the expansion characteristic data of each scheme (including the expansion rate and the retraction rate) are compared with the preset expansion requirement data. The expansion compliance coefficient is obtained by calculating the square root of the sum of the squares of the deviations of the expansion rate and the retraction rate. The thermal distribution compliance coefficient and the expansion compliance coefficient are added, and then the natural logarithm function is applied to increase the nonlinear weight to obtain a comprehensive similarity index, which is used to evaluate the overall compliance of each test scheme with the requirements. The similarity indexes of all test schemes are compared, and the scheme with the smallest similarity index is selected, which is the test scheme closest to the preset requirements.

[0044] By accurately calculating and comparing thermal and expansion characteristics, it is possible to ensure that the selected test solution is closest to the design requirements, thereby improving the accuracy and reliability of product design. By simultaneously considering the two key factors of thermal distribution and physical expansion, this method provides a comprehensive means of evaluating the performance of semiconductor components under various operating conditions.

[0045] Specifically, a thermal performance evaluation is performed on a semiconductor element to be tested corresponding to a finite element model of the semiconductor element to be tested based on the thermal characteristic data to be evaluated, comprising the following steps: obtaining defined thermal characteristic data stored in a database, the defined thermal characteristic data comprising thermal distribution defined data and expansion defined data; comparing the thermal characteristic data to be evaluated with the defined thermal characteristic data to obtain a comparison coefficient; performing a thermal performance evaluation on the semiconductor element to be tested based on the comparison coefficient, the evaluation results being that the thermal performance evaluation of the semiconductor element to be tested is unqualified and the thermal performance evaluation of the semiconductor element to be tested is qualified.

[0046] Performing thermal performance evaluation on a semiconductor component to be tested based on a comparison coefficient includes the following steps: determining whether the comparison coefficient is greater than a comparison threshold stored in a database: if the comparison coefficient is greater than the comparison threshold stored in the database, the thermal performance evaluation of the semiconductor component to be tested corresponding to the comparison coefficient is unqualified; if the comparison coefficient is not greater than the comparison threshold stored in the database, the thermal performance evaluation of the semiconductor component to be tested corresponding to the comparison coefficient is qualified.

[0047] In this embodiment, first, thermal characteristic definition data are extracted from the database, which define the thermal distribution and expansion standards that the semiconductor element should achieve under normal operating conditions. These data are used as evaluation criteria, including thermal distribution definition data and expansion definition data.

[0048] The thermal characteristic data to be evaluated (including measured thermal distribution and expansion data) obtained from the finite element model are compared with the defined thermal characteristic data. This comparison is achieved by calculating the comparison coefficient, which reflects the deviation between the actual data and the standard. Based on the comparison coefficient, the thermal performance of the semiconductor component is evaluated. If the comparison coefficient shows that the deviation between the actual data and the defined standard is within an acceptable range, the evaluation result is qualified; if it exceeds the acceptable range, it is unqualified.

[0049] The data obtained through finite element analysis is highly accurate and can very accurately simulate the thermal behavior under actual operating conditions, thereby improving the reliability of the evaluation. Although physical testing is unavoidable in some cases, finite element analysis can reduce its number, thereby reducing testing costs and accelerating the development process.

[0050] Specifically, obtaining defined thermal characteristic data stored in a database includes the following steps: applying the best test scheme to multiple standard semiconductor component finite element models to obtain parameterized thermal characteristic data corresponding to each standard semiconductor component finite element model; performing mean processing on the parameterized thermal characteristic data to obtain the temperature average value of each analysis unit, the expansion rate average value and the shrinkage rate average value of each analysis unit; defining the temperature average value of each analysis unit as thermal distribution defining data, and defining the expansion rate average value and the shrinkage rate average value of each analysis unit as expansion defining data.

[0051] The parameterized thermal characteristic data include parameterized thermal distribution data and parameterized expansion data. The parameterized thermal distribution data include the temperature parameter values ​​of each analysis unit. The parameterized expansion data include the parameterized expansion rate and the parameterized retraction rate of each analysis unit.

[0052] The test scheme determined to be optimal is applied to finite element models of multiple standard semiconductor components. This ensures that the data obtained is highly reliable and representative, reflecting the performance of the component under optimal conditions. Each model is simulated and its thermal distribution and physical expansion data are collected. These data include temperature values, expansion rates and retraction rates for each analysis unit, which are directly extracted from the simulation results. The collected parameterized thermal characteristic data are statistically processed to calculate the average value of the temperature, expansion rate and retraction rate of each analysis unit. This step is to smooth out abnormal fluctuations in individual data points and obtain a more stable and reliable performance standard. The calculated average values ​​are formally defined as thermal distribution definition data and expansion definition data. These data will serve as standards and references for the thermal performance of semiconductor components in future production.

[0053] Obtaining and defining data through a unified method ensures consistency and standardization of the evaluation process, which helps maintain consistency in product quality. Setting standards based on the parameter data obtained through the best test program can ensure that all products can operate under the best thermal management and physical performance conditions, thereby improving the overall product reliability and performance.

[0054] The method to obtain the comparison coefficient is as follows:

[0055]

[0056] Where i is the number of the analysis unit, i = 1, 2, 3, ..., n, n is the total number of analysis units, Wd i is the temperature value to be evaluated of the i-th analysis unit, Pd i is the expansion rate to be evaluated of the ith analysis unit, Hd is the retraction rate to be evaluated, Wp i is the average temperature of the ith analysis unit, Pp i is the average expansion rate of the ith analysis unit, Hp i is the average value of the i-th retraction rate, and Bx is the comparison coefficient.

[0057] In this embodiment, by calculating the square difference between the temperature value to be evaluated and the average temperature value of each analysis unit, this calculation emphasizes the importance of temperature deviation, because temperature is crucial to the performance and stability of semiconductors. The absolute value of the difference between the expansion rate to be evaluated and the average expansion rate of each analysis unit is calculated to evaluate the degree of deviation of the expansion behavior. Similarly, the absolute value of the deviation of the retraction rate of each analysis unit is calculated to measure the deviation of the physical size recovery ability. Finally, all these differences are summed up and divided by the total number of analysis units to obtain a comprehensive comparison coefficient, which quantifies the overall difference between the data to be evaluated and the average defined data.

[0058] Semiconductor component performance evaluation system based on finite element, such as Figure 2 As shown, it includes a scheme determination module, a data acquisition module and an evaluation module, wherein: the scheme determination module is used to determine the best test scheme; the data acquisition module is used to apply the best test scheme to the finite element model of the semiconductor component to be tested stored in the database, and obtain the thermal characteristic data to be evaluated of the finite element model of the semiconductor component to be tested, the thermal characteristic data to be evaluated includes thermal distribution data to be evaluated and expansion data to be evaluated, the thermal distribution data to be evaluated includes the temperature to be evaluated value of each analysis unit, and the expansion data to be evaluated includes the expansion rate to be evaluated and the shrinkage rate to be evaluated of each analysis unit; the evaluation module is used to perform thermal performance evaluation on the semiconductor component to be tested corresponding to the finite element model of the semiconductor component to be tested based on the thermal characteristic data to be evaluated.

[0059] An electronic device includes: a processor and a memory, wherein computer program instructions are stored in the memory, and when the computer program instructions are executed by the processor, the processor executes the semiconductor element performance evaluation method based on finite elements as described above.

[0060] A computer-readable storage medium is used to store a program, and when the program is executed by a processor, the semiconductor device performance evaluation method based on finite elements as described above is implemented.

[0061] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0062] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0063] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0064] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1A step that specifies a function in one or more boxes.

[0065] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0066] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A semiconductor component performance evaluation method based on finite element, characterized in that: The following steps are involved: Determine the best testing plan; Applying the best test scheme to the finite element model of the semiconductor component to be tested stored in the database, obtaining thermal characteristic data to be evaluated of the finite element model of the semiconductor component to be tested, wherein the thermal characteristic data to be evaluated includes thermal distribution data to be evaluated and expansion data to be evaluated, wherein the thermal distribution data to be evaluated includes the temperature value to be evaluated of each analysis unit, and the expansion data to be evaluated includes the expansion rate to be evaluated and the retraction rate to be evaluated of each analysis unit; A thermal performance evaluation is performed on the semiconductor component to be tested corresponding to the finite element model of the semiconductor component to be tested based on the thermal characteristic data to be evaluated.

2. The semiconductor device performance evaluation method based on finite element analysis according to claim 1, characterized in that: Determine the best testing plan, including the following steps: Obtaining a standard semiconductor component finite element model stored in a database; Obtaining a plurality of test schemes stored in a database and applying each test scheme to a standard semiconductor component finite element model; Acquire thermal characteristic evaluation data after each test scheme is applied to a standard semiconductor component finite element model, wherein the thermal characteristic evaluation data includes thermal distribution characteristic data and expansion characteristic data; Acquire required thermal characteristic data stored in a database, wherein the required thermal characteristic data includes required thermal distribution data and required expansion data; Compare the thermal characteristic evaluation data corresponding to each test scheme with the required thermal characteristic data one by one to determine the most similar thermal characteristic evaluation data; The test scheme corresponding to the most similar thermal characteristic evaluation data is defined as the best test scheme.

3. The semiconductor device performance evaluation method based on finite element analysis according to claim 2, characterized in that: The thermal characteristic evaluation data corresponding to each test scheme is compared with the required thermal characteristic data one by one to determine the most similar thermal characteristic evaluation data, including the following steps: Comparing the thermal distribution characteristic data of each thermal characteristic evaluation data with the thermal distribution requirement data one by one to determine the thermal distribution compliance coefficient, wherein the thermal distribution characteristic data includes the temperature value of each analysis unit, and the thermal distribution requirement data includes the temperature requirement value of each analysis unit; Comparing the expansion characteristic data of each thermal characteristic evaluation data with the expansion requirement data one by one to determine the expansion compliance coefficient, wherein the expansion characteristic data includes the expansion rate and the retraction rate of each analysis unit, and the expansion requirement data includes the expansion requirement rate and the retraction requirement rate of each analysis unit; Superimpose each thermal distribution compliance coefficient with the corresponding expansion compliance coefficient to determine a similarity index; The thermal characteristic evaluation data corresponding to the smallest similarity index is determined as the most similar thermal characteristic evaluation data.

4. The semiconductor device performance evaluation method based on finite element method according to claim 3, characterized in that: The method for obtaining the similarity index is: Xs = ln(1+wx+px); Where Xs is the similarity index, wx is the thermal distribution compliance coefficient, and px is the expansion compliance coefficient.

5. The semiconductor device performance evaluation method based on finite element method according to claim 1, characterized in that: Based on the thermal characteristic data to be evaluated, thermal performance evaluation of the semiconductor component to be tested corresponding to the finite element model of the semiconductor component to be tested is performed, including the following steps: Obtaining defined thermal characteristic data stored in a database, wherein the defined thermal characteristic data includes thermal distribution defined data and expansion defined data; Comparing the thermal characteristic data to be evaluated with the defined thermal characteristic data to obtain a comparison coefficient; The thermal performance of the semiconductor element to be tested is evaluated based on the comparison coefficient, and the evaluation results are that the thermal performance evaluation of the semiconductor element to be tested fails and the thermal performance evaluation of the semiconductor element to be tested passes.

6. The semiconductor device performance evaluation method based on finite element method according to claim 5, characterized in that: Obtaining defined thermal characteristic data stored in a database comprises the following steps: Apply the best test scheme to multiple standard semiconductor component finite element models to obtain parameterized thermal characteristic data corresponding to each standard semiconductor component finite element model; Performing mean processing on the parameterized thermal characteristic data to obtain the average temperature of each analysis unit, the average expansion rate and the average contraction rate of each analysis unit; The average temperature of each analysis unit is defined as heat distribution definition data, and the average expansion rate and the average shrinkage rate of each analysis unit are defined as expansion definition data.

7. The semiconductor device performance evaluation method based on finite element method according to claim 6, characterized in that: The parameterized thermal characteristic data include parameterized thermal distribution data and parameterized expansion data. The parameterized thermal distribution data include the temperature parameter values ​​of each analysis unit. The parameterized expansion data include the parameterized expansion rate and the parameterized retraction rate of each analysis unit.

8. The semiconductor device performance evaluation method based on finite element method according to claim 7, characterized in that: The method to obtain the comparison coefficient is as follows: Where i is the number of the analysis unit, i = 1, 2, 3, ..., n, n is the total number of analysis units, Wd i is the temperature value to be evaluated of the i-th analysis unit, Pd i is the expansion rate to be evaluated of the ith analysis unit, Hd is the retraction rate to be evaluated, Wp i is the average temperature of the ith analysis unit, Pp i is the average expansion rate of the ith analysis unit, Hp i is the average value of the i-th retraction rate, and Bx is the comparison coefficient.

9. The semiconductor device performance evaluation method based on finite element method according to claim 5, characterized in that: The thermal performance evaluation of the semiconductor component to be tested is performed based on the comparison coefficient, including the following steps: Determine whether the comparison coefficient is greater than the comparison threshold stored in the database: If the comparison coefficient is greater than the comparison threshold stored in the database, the thermal performance evaluation of the semiconductor component to be tested corresponding to the comparison coefficient fails; If the comparison coefficient is not greater than the comparison threshold stored in the database, the thermal performance evaluation of the semiconductor component to be tested corresponding to the comparison coefficient is qualified.

10. A semiconductor component performance evaluation system based on finite element, characterized in that: It includes a program determination module, a data acquisition module and an evaluation module, among which: The scheme determination module is used to determine the best test scheme; The data acquisition module is used to apply the best test solution to the finite element model of the semiconductor component to be tested stored in the database, and obtain the thermal characteristic data to be evaluated of the finite element model of the semiconductor component to be tested, wherein the thermal characteristic data to be evaluated includes thermal distribution data to be evaluated and expansion data to be evaluated, wherein the thermal distribution data to be evaluated includes the temperature value to be evaluated of each analysis unit, and the expansion data to be evaluated includes the expansion rate to be evaluated and the retraction rate to be evaluated of each analysis unit; The evaluation module is used to perform thermal performance evaluation on the semiconductor element to be tested corresponding to the finite element model of the semiconductor element to be tested based on the thermal characteristic data to be evaluated.

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