A method and system for predicting optoelectronic performance based on random crack templates

Abstract

The application discloses a kind of photoelectric performance prediction method and system based on random crack template, the method is first directly modeled simulation by format conversion to micrograph, obtains electromagnetic shielding performance simulation result;Then according to aperture unit area size, long axis size and short axis size, carry out graphic data iterative fitting, and according to the parameters of the metal mesh transparent conductive film to be prepared, carry out full-wave electromagnetic simulation, obtain electromagnetic shielding performance simulation result;Finally, the average value of the two simulation results is obtained by solving to predict the electromagnetic shielding performance.The method can quickly predict the light transmission and electromagnetic shielding performance of the metal mesh transparent conductive film prepared based on the pattern and size distribution of the random crack template, greatly improve the efficiency of the metal mesh transparent conductive film with target photoelectric performance, and fully exert the high cost performance advantage of the metal mesh transparent conductive film with excellent performance prepared based on the random crack template method.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of metal mesh transparent conductive film, and in particular to a photoelectric performance prediction method and system based on a random crack template. BACKGROUND

[0002] Currently, the preparation of metal mesh transparent conductive film is mainly through the process of photolithography to prepare a photolithography mask plate, then depositing metal and removing glue to obtain the corresponding metal mesh transparent conductive film. Because the photolithography mask plate needs to be prepared, the technical threshold is high, and the corresponding preparation cost is high due to the complex process. In recent years, the metal mesh transparent conductive film prepared based on the random crack template method has a low technical threshold, and the preparation cost of the crack template is greatly reduced due to the low cost of crack collagen raw materials and the simple process, so it has a good performance-price ratio and is concerned.

[0003] However, the metal mesh transparent conductive film pattern prepared based on the random crack template is randomly distributed, and it is not possible to accurately predict its light transmittance and electromagnetic shielding performance in advance according to the known pattern distribution and size as the photolithography mask plate. Because the light transmittance and electromagnetic shielding performance of the metal mesh transparent conductive film prepared based on the random crack template cannot be effectively predicted, the corresponding photoelectric performance can only be obtained by actual measurement after the metal mesh transparent conductive film is prepared, which is time-consuming and laborious. The efficiency of preparing the metal mesh transparent conductive film with the target photoelectric performance is low. SUMMARY

[0004] The present application provides a photoelectric performance prediction method and system based on a random crack template, which is used to overcome the defect that the corresponding photoelectric performance can only be obtained after the metal mesh transparent conductive film is prepared in the prior art.

[0005] To achieve the above-mentioned purpose, the present application provides a photoelectric performance prediction method based on a random crack template, comprising the following steps:

[0006] Obtaining a microscopic image of a random crack template and the area size, long axis size and short axis size of each aperture unit in the microscopic image;

[0007] Converting the format of the microscopic image to obtain a parameter model, performing full-wave electromagnetic simulation according to the parameter model, and obtaining corresponding electromagnetic shielding performance simulation result I;

[0008] According to the area size, long axis size and short axis size of each aperture unit in the microscopic image, data statistics are performed to obtain the initial values of the aperture unit area, long axis and short axis;

[0009] selecting a polygonal figure as a fitting figure, performing iterative fitting of figure data by using the initial values of the aperture unit area, the long axis and the short axis, until the values of the aperture unit area, the long axis and the short axis obtained satisfy the set condition, and outputting the values of the aperture unit area, the long axis and the short axis;

[0010] performing full-wave electromagnetic simulation according to the output values of the aperture unit area, the long axis and the short axis, and parameters of the metal mesh transparent conductive thin film to be prepared, to obtain corresponding electromagnetic shielding performance simulation result II;

[0011] obtaining the predicted electromagnetic shielding performance by calculating the average of the electromagnetic shielding performance simulation result I and the electromagnetic shielding performance simulation result II.

[0012] To achieve the above object, the present application further provides a photoelectric performance prediction system based on a random crack template, comprising:

[0013] a data acquisition module configured to acquire a microscopic image of the random crack template, and the size of each aperture unit area, the size of the long axis and the size of the short axis in the microscopic image;

[0014] a performance prediction module configured to perform format conversion on the microscopic image to obtain a parameter model, perform full-wave electromagnetic simulation according to the parameter model to obtain corresponding electromagnetic shielding performance simulation result I, perform data statistics according to the size of each aperture unit area, the size of the long axis and the size of the short axis in the microscopic image to obtain initial values of the aperture unit area, the long axis and the short axis, select a polygonal figure as a fitting figure, perform iterative fitting of figure data by using the initial values of the aperture unit area, the long axis and the short axis, until the values of the aperture unit area, the long axis and the short axis obtained satisfy the set condition, and output the values of the aperture unit area, the long axis and the short axis, perform full-wave electromagnetic simulation according to the output values of the aperture unit area, the long axis and the short axis, and parameters of the metal mesh transparent conductive thin film to be prepared, to obtain corresponding electromagnetic shielding performance simulation result II, and obtain the predicted electromagnetic shielding performance by calculating the average of the electromagnetic shielding performance simulation result I and the electromagnetic shielding performance simulation result II.

[0015] To achieve the above object, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0016] To achieve the above object, the present application further provides a computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the steps of the above method.

[0017] Compared with the prior art, the present application has the following beneficial effects:

[0018] The method for predicting photoelectric performance based on a random crack template provided by the application firstly directly models and simulates by format conversion of a microscopic image to obtain corresponding electromagnetic shielding performance simulation result I; then performs graphic iterative fitting according to the extracted aperture unit area size, long axis size and short axis size to obtain a graphic duty cycle for representing light transmittance, and performs full-wave electromagnetic simulation according to the parameters of the metal mesh transparent conductive thin film to be prepared to obtain corresponding electromagnetic shielding performance simulation result II; finally, the average value of the two simulation results is obtained to obtain the final predicted electromagnetic shielding performance. The prediction method provided by the application can quickly and accurately predict the light transmittance and electromagnetic shielding performance of the metal mesh transparent conductive thin film prepared based on the crack template, can greatly improve the efficiency of the metal mesh transparent conductive thin film with target photoelectric performance, and fully plays the high cost performance advantage of the metal mesh transparent conductive thin film with excellent performance prepared based on the random crack template method. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other drawings can also be obtained according to the structures shown in the drawings without creative labor.

[0020] Figure 1 is the iteration flow chart of the hexagonal pattern size data in the application;

[0021] Figure 2 is a sample pattern schematic diagram observed under a microscope in the crack template in embodiment 1 of the application;

[0022] Figure 3 is a schematic diagram of converting the sample pattern into a full-wave electromagnetic simulation model in embodiment 1 of the application;

[0023] Figure 4 is a pore area size data statistical curve distribution schematic diagram in embodiment 1 of the application;

[0024] Figure 5 is a long axis size data statistical curve distribution schematic diagram in embodiment 1 of the application;

[0025] Figure 6 is a short axis size data statistical curve distribution schematic diagram in embodiment 1 of the application;

[0026] Figure 7 is a fitted hexagonal structure model schematic diagram in embodiment 1 of the application;

[0027] Figure 8is a simulation result comparison diagram of a pattern extraction model and a fitted hexagonal model of sample pattern conversion in embodiment 1 of the present application;

[0028] Figure 9 is a sample pattern schematic diagram observed under a microscope of a crack template in embodiment 2 of the present application;

[0029] Figure 10 is a schematic diagram of sample pattern conversion into a full-wave electromagnetic simulation model in embodiment 2 of the present application;

[0030] Figure 11 is an aperture area size data statistical curve distribution schematic diagram in embodiment 2 of the present application;

[0031] Figure 12 is a long axis size data statistical curve distribution schematic diagram in embodiment 2 of the present application;

[0032] Figure 13 is a short axis size data statistical curve distribution schematic diagram in embodiment 2 of the present application;

[0033] Figure 14 is a fitted hexagonal structure model schematic diagram in embodiment 2 of the present application;

[0034] Figure 15 is a simulation result comparison diagram of a pattern extraction model and a fitted hexagonal model of sample pattern conversion in embodiment 2 of the present application.

[0035] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work are within the protection scope of the present application.

[0037] In addition, the technical solutions in each embodiment of the present application can be combined with each other, but it must be based on that a person of ordinary skill in the art can realize, when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, and is not within the protection scope required by the present application.

[0038] The present application proposes a photoelectric performance prediction method based on a random crack template, comprising the following steps:

[0039] 101: Obtain a microscopic image of a random crack template, and the size of each aperture unit area, the long axis size and the short axis size in the microscopic image.

[0040] 102: Format conversion is performed on the microscopic image to obtain a parameter model, and full-wave electromagnetic simulation is performed according to the parameter model to obtain corresponding electromagnetic shielding performance simulation result I.

[0041] 103: According to the size of each aperture unit area, the long axis size and the short axis size in the microscopic image, data statistics are performed to obtain initial values of the aperture unit area, the long axis and the short axis.

[0042] 104: A polygonal graph is selected as a fitting graph, and graph data iterative fitting is performed using the initial values of the aperture unit area, the long axis and the short axis until the values of the aperture unit area, the long axis and the short axis meet the set conditions, and the values of the aperture unit area, the long axis and the short axis are output.

[0043] 105: According to the output values of the aperture unit area, the long axis and the short axis, and the parameters of the metal mesh transparent conductive film to be prepared, full-wave electromagnetic simulation is performed to obtain corresponding electromagnetic shielding performance simulation result II.

[0044] 106: The average value of the electromagnetic shielding performance simulation result I and the electromagnetic shielding performance simulation result II is obtained to obtain the predicted electromagnetic shielding performance.

[0045] Optoelectronic performance refers to transmittance and electromagnetic shielding performance.

[0046] In order to improve the implementation efficiency of optimizing and preparing a random crack template and a corresponding metal mesh transparent conductive film meeting target optoelectronic performance, the present application proposes an optoelectronic performance prediction method based on a random crack template, which only needs to obtain sample pattern information of the crack template through microscope observation, and can effectively predict the corresponding optoelectronic performance without preparing a metal mesh transparent conductive film, which greatly improves the efficiency of optimizing and preparing a metal mesh transparent conductive film with corresponding target optoelectronic performance.

[0047] In one embodiment, for step 101, a crack template with a random distribution pattern is placed under an optical microscope for observation, and a microscopic image of the crack template is collected; the microscopic system can simultaneously extract the size of each aperture unit area, the long axis size and the short axis size in the microscopic image.

[0048] In another embodiment, for step 102, the microscopic image is format-converted to obtain a parameter model, which includes:

[0049] The microscopic image is converted into a two-dimensional CAD format file, and then the two-dimensional CAD file format is converted into a parameter model file of full-wave electromagnetic simulation software.

[0050] In the next embodiment, for step 103, according to the size of each aperture unit area, the major axis size and the minor axis size in the microscopic image, data statistics are performed to obtain the initial values of the aperture unit area, the major axis and the minor axis, including:

[0051] According to the size of each aperture unit area, the major axis size and the minor axis size in the microscopic image, data statistics are performed and the corresponding curve distribution diagram is made to obtain the data centralized distribution region of the aperture unit area, the major axis and the minor axis;

[0052] The average value of the data centralized distribution region is calculated to obtain the initial values of the aperture unit area, the major axis and the minor axis.

[0053] In the next embodiment, for step 104, a polygonal graph is selected as the fitting graph, and the initial values of the aperture unit area, the major axis and the minor axis are used for iterative fitting of the graph data until the values of the aperture unit area, the major axis and the minor axis obtained satisfy the set condition, such as Figure 1 as shown, including:

[0054] The polygonal graph is selected as the fitting graph, and the area is S_area, the major axis is l_long and the minor axis is l_short; wherein the area is the size of the area contained by the aperture unit, the major axis refers to the distance between the two longest vertices passing through the center of the graph in the aperture unit, and the minor axis refers to the distance between the two shortest vertices passing through the center of the graph in the aperture unit;

[0055] The initial values of the aperture unit area, the major axis and the minor axis are used for iterative fitting of the graph data until the values of the aperture unit area, the major axis and the minor axis obtained satisfy the set condition.

[0056] In an embodiment, the initial values of the aperture unit area, the major axis and the minor axis are used for iterative fitting of the graph data until the values of the aperture unit area, the major axis and the minor axis obtained satisfy the set condition, including:

[0057] The offset coefficient is set, and the initial values of the aperture unit area, the major axis and the minor axis are used to calculate the random offset data of iteration;

[0058] The iterative calculation is performed until the values of the aperture unit area, the major axis and the minor axis obtained satisfy the set condition.

[0059] In the next embodiment, the set condition is:

[0060] The ratio of the minor axis size to the major axis size is greater than 0.86 and less than 0.87;

[0061] Aperture unit area = 3* major axis size * minor axis size / 4;

[0062] The ratio of the final aperture unit area to the initial value of the aperture unit area is greater than 0.9 and less than 1.1.

[0063] In another embodiment, for step 105, the parameters of the metal mesh transparent conductive film include: metal material, thickness and average line width.

[0064] The application further provides an optoelectronic performance prediction system based on a random crack template, comprising:

[0065] A data acquisition module is configured to acquire a microscopic image of the random crack template and sizes of each aperture unit area, a long axis and a short axis in the microscopic image.

[0066] A performance prediction module is configured to perform format conversion on the microscopic image to obtain a parameter model, perform full-wave electromagnetic simulation according to the parameter model to obtain corresponding electromagnetic shielding performance simulation result I, perform data statistics according to the sizes of each aperture unit area, the long axis and the short axis in the microscopic image to obtain initial values of the aperture unit area, the long axis and the short axis, select a polygon as a fitting graph, perform graph data iterative fitting using the initial values of the aperture unit area, the long axis and the short axis until the values of the aperture unit area, the long axis and the short axis meet a set condition, and output the values of the aperture unit area, the long axis and the short axis, perform full-wave electromagnetic simulation according to the output values of the aperture unit area, the long axis and the short axis and parameters of the metal mesh transparent conductive film to be prepared to obtain corresponding electromagnetic shielding performance simulation result II, and obtain a predicted electromagnetic shielding performance by calculating an average value of the electromagnetic shielding performance simulation result I and the electromagnetic shielding performance simulation result II.

[0067] The application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0068] The application further provides a computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the steps of the above method.

[0069] Embodiment 1

[0070] The embodiment provides an optoelectronic performance prediction method based on a random crack template, comprising the following steps:

[0071] The microscopic image of the random crack template and the sizes of each aperture unit area, a long axis and a short axis in the microscopic image are acquired.

[0072] A silicon glass piece with a diameter of 50mm and a thickness of 1mm is used as a crack template for the substrate, and is placed under an optical microscope for observation to obtain a corresponding crack template sample pattern, which is in jpg picture format, as shown in Figure 2 .

[0073] The sample pattern is first converted into a DXF format file, and then converted into a three-dimensional model file of electromagnetic simulation software CST according to the existing parameters of the metal material copper and the thickness t = 0.8um, as shown in Figure 3 , and then model simulation calculation is performed to obtain the shielding performance results as shown in Figure 8 .

[0074] The area size, long axis and short axis dimensions of each aperture in the pattern sample are statistically analyzed, and the corresponding aperture area size data statistical curve distribution diagram is shown in Figure 4 , the long axis size data statistical curve distribution diagram is shown in Figure 5 , and the short axis size data statistical curve distribution diagram is shown in Figure 6 . It can be seen that the statistical data are concentratedly distributed, and the corresponding preliminary average aperture area, long axis and short axis are obtained by statistically analyzing the average value of the concentratedly distributed data, respectively S_area0 = 358.36um 2 , l_short0 = 19.46um, l_long0 = 27.88um.

[0075] A regular hexagonal structure is used for data fitting pattern analysis, and the area is S_area, the long axis is l_long, and the short axis is l_short,

[0076] wherein the area is the size of the area contained by the hexagonal aperture unit, the long axis size refers to the distance between the two longest vertices passing through the center of the hexagonal aperture unit, and the short axis size refers to the distance between the two shortest vertices passing through the center of the hexagonal aperture unit.

[0077] The selected hexagonal pattern to be fitted is further iteratively processed, and the hexagonal size data iteration flowchart is shown in Figure 1 , the offset coefficient m = 0.15, and the final iteration aperture area size, long axis size and short axis size output are respectively:

[0078] S_area = 372.43um 2 , l_short = 20.76um, l_long = 23.91um

[0079] According to the final aperture area, long axis and short axis size of the corresponding fitting pattern obtained in the foregoing, and according to the existing parameters: the metal material is copper, the thickness is t = 0.8 um, and the average line width 2a = 2 um, a three-dimensional model is established in the electromagnetic simulation software CST, as shown in Figure 7 .

[0080] According to the modeling pattern size data, the pattern duty cycle size that can be used to characterize the light transmittance performance is obtained, and the light transmittance duty cycle is calculated as

[0081] T0 = (1-6*l_long*a / (l_long*(1+1 / 2))*l_long*cos(pi / 6)))*100% = 80.68%

[0082] Full-wave electromagnetic simulation is performed on the fitted hexagonal structure model to obtain the corresponding electromagnetic shielding performance, as shown in Figure 8 , and the shielding performance of the simulation model extracted from the pattern sample is compared. In the wide frequency band of 1-40 GHz, except for the slight difference in amplitude at the low frequency point, the amplitude deviation in other frequency bands is within 1 dB, and the correctness of the shielding performance estimation result is verified.

[0083] The average value of the two electromagnetic shielding performance simulation results is obtained to obtain the predicted electromagnetic shielding performance.

[0084] Embodiment 2

[0085] The embodiment provides a photoelectric performance prediction method based on a random crack template, comprising the following steps:

[0086] Obtain the microscopic image of the random crack template and the area size, long axis size and short axis size of each aperture unit in the microscopic image.

[0087] A silicon glass sheet with a diameter of 100 mm and a thickness of 2 mm is used as a crack template of the substrate and is placed under an optical microscope for observation to obtain a corresponding crack template sample pattern. The format of the sample pattern is PNG picture format, as shown in Figure 9 .

[0088] The sample pattern is first converted into a DXF format file, and then according to the existing parameters: the metal material is copper, the thickness is t = 0.8 um, the DXF format file is converted into a three-dimensional model file of the electromagnetic simulation software CST, as shown in Figure 10 , and then the model simulation calculation is performed to obtain the shielding performance result, as shown in Figure 15 .

[0089] Data statistics are performed on the aperture area size, long axis and short axis size of each pattern sample, and a corresponding aperture area size data statistical curve distribution diagram is drawn, as shown in Figure 11The long axis size data statistical curve distribution diagram is shown in FIG. 2. Figure 12 The short axis size data statistical curve distribution diagram is shown in FIG. 3. Figure 13 It can be seen that the statistical data are concentrated. According to the characteristics of the concentrated distribution of the statistical data, the average values of the corresponding preliminary average pore area, long axis and short axis are obtained by statistical average in the data region of the concentrated distribution, which are S_area0=2234.43um2, l_short0=48.37um and l_long0=75.17um respectively.

[0090] The data fitting graph analysis is performed on the regular hexagon structure, and the area is S_area, the long axis is l_long, and the short axis is l_short.

[0091] The area is the size of the area contained by the hexagonal aperture unit, the long axis size refers to the distance between the two longest vertices passing through the center of the graph in the hexagonal aperture unit, and the short axis size refers to the distance between the two shortest vertices passing through the center of the graph in the hexagonal aperture unit.

[0092] The data of the selected hexagonal graph to be fitted are further iterated, and the hexagonal size data iteration flowchart is shown in FIG. 4. Figure 1 The offset coefficient m=0.2, and the final iteration aperture area size, long axis size and short axis size output are respectively:

[0093] S_area=2344.4um 2 , l_short=51.92um, l_long=60.2um;

[0094] According to the final aperture area, long axis and short axis size of the corresponding fitting graph obtained in the foregoing, and according to the existing parameters: the metal material is copper, the thickness t=0.8um, and the average line width 2a=2um, three-dimensional modeling is performed in the electromagnetic simulation software CST, as shown in FIG. 5. Figure 14

[0095] According to the modeling graph size data, the graph duty cycle size that can be used to characterize the light transmittance performance can be obtained, and the light transmittance duty cycle is calculated.

[0096] T0=(1-6*l_long*a / (l_long*(1+1 / 2))*l_long*cos(pi / 6)))*100%=92.32%

[0097] The full-wave electromagnetic simulation of the fitted hexagonal structure model obtains the corresponding electromagnetic shielding performance, as shown in FIG. 6. Figure 15 ​The simulation results of the electromagnetic shielding performance are shown in the figure, and the shielding performance of the simulation model of the direct figure sample extraction is compared. In the wide frequency band range of 1-40GHz, except that the amplitude difference is slightly large at the low frequency point, the amplitudes of other frequency bands, especially the high frequency band, are basically coincident, and the correctness of the shielding performance estimation results is verified mutually.

[0098] The average value of the electromagnetic shielding performance simulation results is obtained to obtain the predicted electromagnetic shielding performance.

[0099] The above two embodiments are described based on several photoelectric performance prediction examples of the pattern extraction model and the data statistical fitting hexagon model, and the effectiveness of the photoelectric performance prediction method in the application is explained. It is explained that the application is a photoelectric performance prediction method based on a random crack template, which can effectively predict the photoelectric performance of the metal mesh conductive film prepared therefrom. This is very useful in the process optimization of the preparation of the high-performance metal mesh conductive film based on the crack template method. The photoelectric performance of the metal mesh conductive film can be predicted without preparing the actual metal mesh conductive film, which greatly improves the efficiency of the optimization and preparation of the high-performance metal mesh transparent conductive film, and has obvious cost performance advantage.

[0100] The above description is only the preferred embodiments of the application, and does not limit the patent scope of the application. Any equivalent structural transformation, direct / indirect application in other related technical fields based on the inventive concept of the application, and the contents of the specification and drawings are included in the patent protection scope of the application.

Claims

1. A method for predicting photoelectric properties based on random crack templates, characterized in that, Includes the following steps: Obtain microscopic images of random crack templates, as well as the area size, major axis dimension, and minor axis dimension of each pore unit in the microscopic images; The microscopic image is converted to a format to obtain a parametric model. Full-wave electromagnetic simulation is performed based on the parametric model to obtain the corresponding electromagnetic shielding performance simulation result I. Based on the area, major axis, and minor axis dimensions of each aperture unit in the microscopic image, data statistics are performed to obtain the initial values ​​of the aperture unit area, major axis, and minor axis. Select a polygonal shape as the fitting shape, and use the initial values ​​of the aperture unit area, major axis and minor axis to perform iterative fitting of the shape data until the values ​​of the aperture unit area, major axis and minor axis meet the set conditions, and output the values ​​of the aperture unit area, major axis and minor axis. Based on the output aperture unit area, major axis and minor axis values, and the parameters of the metal mesh transparent conductive film to be prepared, a full-wave electromagnetic simulation is performed to obtain the corresponding electromagnetic shielding performance simulation results II. The predicted electromagnetic shielding performance is obtained by averaging the electromagnetic shielding performance simulation results I and II.

2. The photoelectric performance prediction method as described in claim 1, characterized in that, The parameter model is obtained by converting the format of the microscopic image, including: The microscopic images are converted into two-dimensional CAD format files, and then the two-dimensional CAD file format is converted into a parametric model file for full-wave electromagnetic simulation software.

3. The photoelectric performance prediction method as described in claim 1, characterized in that, Based on the area, major axis, and minor axis dimensions of each aperture unit in the microscopic image, data statistics are performed to obtain initial values ​​for the aperture unit area, major axis, and minor axis, including: Based on the area size, major axis dimension, and minor axis dimension of each aperture unit in the microscopic image, data statistics are performed, and corresponding curve distribution diagrams are plotted to obtain the concentrated distribution area of ​​the aperture unit area, major axis, and minor axis data. Calculate the average value of the centrally distributed region of the dataset to obtain the initial values ​​of the aperture unit area, major axis, and minor axis.

4. The photoelectric performance prediction method as described in claim 1, characterized in that, A polygonal shape is selected as the fitting shape. The initial values ​​of the aperture unit area, major axis, and minor axis are used to iteratively fit the shape data until the obtained values ​​of the aperture unit area, major axis, and minor axis meet the set conditions, including: Select a polygonal shape as the fitting shape, and let the area be S_area, the major axis be l_long, and the minor axis be l_short; where the area is the size of the area contained in the aperture unit, the major axis refers to the distance between the two longest vertices passing through the center of the shape in the aperture unit, and the minor axis refers to the distance between the two shortest vertices passing through the center of the shape in the aperture unit. The initial values ​​of the aperture unit area, major axis, and minor axis are used to perform iterative fitting of the graphic data until the values ​​of the aperture unit area, major axis, and minor axis meet the set conditions.

5. The photoelectric performance prediction method as described in claim 4, characterized in that, The initial values ​​of the aperture unit area, major axis, and minor axis are used to iteratively fit the graphic data until the obtained values ​​of the aperture unit area, major axis, and minor axis meet the set conditions, including: Set the offset coefficient, and use the initial values ​​of the aperture unit area, major axis and minor axis to calculate the iterative random offset data; The calculation is iterated until the values ​​of the aperture element area, major axis, and minor axis meet the set conditions.

6. The photoelectric performance prediction method as described in claim 1, 4, or 5, characterized in that, The specified conditions are: The ratio of the minor axis dimension to the major axis dimension is greater than 0.86 and less than 0.87; Aperture unit area = 3 * major axis dimension * minor axis dimension / 4; The ratio of the final aperture element area to the initial aperture element area is greater than 0.9 and less than 1.

1.

7. The photoelectric performance prediction method as described in claim 1, characterized in that, The parameters of the metal mesh transparent conductive film include: metal material, thickness, and average linewidth.

8. A photoelectric performance prediction system based on a random crack template, characterized in that, include: The data acquisition module is used to acquire microscopic images of random crack templates, as well as the area size, major axis dimension, and minor axis dimension of each pore unit in the microscopic image; The performance prediction module is used to convert the format of the microscopic image to obtain a parametric model, perform full-wave electromagnetic simulation based on the parametric model, and obtain the corresponding electromagnetic shielding performance simulation result I. Based on the area, major axis, and minor axis dimensions of each aperture unit in the microscopic image, data statistics are performed to obtain the initial values ​​of the aperture unit area, major axis, and minor axis. A polygonal shape is selected as the fitting shape, and the initial values ​​of the aperture unit area, major axis, and minor axis are used for iterative fitting of the shape data until the obtained values ​​of the aperture unit area, major axis, and minor axis meet the set conditions, and the values ​​of the aperture unit area, major axis, and minor axis are output. Based on the output values ​​of the aperture unit area, major axis, and minor axis, and the parameters of the metal mesh transparent conductive film to be prepared, full-wave electromagnetic simulation is performed to obtain the corresponding electromagnetic shielding performance simulation result II. The predicted electromagnetic shielding performance is obtained by averaging the electromagnetic shielding performance simulation results I and II.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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