Mold coating generation method, device, equipment, storage medium and program product

Abstract

The present application relates to the technical field of mold surface treatment, and in particular to a mold coating generation method, device, equipment, storage medium and program product. The method comprises: obtaining coating parameters of a target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multiple single-phase coating components and multiple single-phase coating thicknesses; obtaining a test coating performance value of a test coating generated according to the coating parameters; if the test coating performance value meets a preset first performance indicator, generating a mold coating of the target mold according to the coating parameters. The present application can improve the performance of PVD coatings.

Description

Technical Field

[0001] The present application relates to the technical field of mold surface treatment, and in particular to a mold coating generation method, device, equipment, storage medium and program product. Background Art

[0002] Moulds are essential basic equipment in industrial production and are widely used in key areas such as automobiles, home appliances, transportation, and national defense. The overall strengthening treatment and surface strengthening treatment of moulds are both important ways to increase the life of moulds.

[0003] Taking the Physical Vapor Deposition (PVD) surface coating technology as an example, PVD is a common mold surface strengthening method, which is to coat the mold surface through PVD coating. However, in the related technology, when performing PVD coating, the performance of the generated PVD coating is difficult to guarantee. Summary of the invention

[0004] Based on this, it is necessary to provide a mold coating generation method, device, equipment, storage medium and program product that can improve the performance of PVD coating in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for generating a mold coating, the method comprising:

[0006] Obtain coating parameters of the target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multiple single-phase coating components and multiple single-phase coating thicknesses;

[0007] obtaining a test coating property value of the test coating generated according to the coating parameters;

[0008] If the tested coating performance value meets the preset first performance index, then according to the coating parameters

[0009] Generate a mold coating for the target mold.

[0010] In one embodiment, obtaining coating parameters of a target mold according to a preset coating design method includes:

[0011] obtaining a plurality of different single-phase coating compositions and a plurality of different single-phase coating thicknesses;

[0012] Combining the components of each single-phase coating and the thickness of each single-phase coating to obtain a plurality of different coating parameters to be verified;

[0013] Verifying each coating parameter to be verified to obtain coating parameters that meet the second performance indicator;

[0014] The coating parameters that meet the second performance index are used as the coating parameters of the target mold.

[0015] In one embodiment, a plurality of different single-phase coating compositions are obtained, including:

[0016] Acquire each target area of ​​the experimental microplate, and each target component corresponding to each target area;

[0017] Prepare single-phase test coatings according to target compositions corresponding to each target area;

[0018] The test coating performance value of the coating in each target area is obtained, and the target component corresponding to the test coating performance value that meets the preset third performance index is determined as the single-phase coating component.

[0019] In one embodiment, a single-phase test coating is prepared according to target components corresponding to each target area, including:

[0020] A high-throughput magnetron sputtering coating method was used to prepare single-phase test coatings according to the target composition corresponding to each target area.

[0021] In one embodiment, the test coating property values ​​include nanoindentation test data and nanoscratch test data.

[0022] In one embodiment, each coating parameter to be verified is verified to obtain coating parameters that meet the second performance indicator, including:

[0023] Input each coating parameter to be verified into the simulation model for simulation experiment, and obtain the optimized coating performance value corresponding to each coating parameter to be verified output by the simulation model;

[0024] Each optimized coating performance value is compared with the second performance index to obtain coating parameters that meet the second performance index.

[0025] In one embodiment, the simulation model includes an analytical model and an optimization model;

[0026] Each coating parameter to be verified is input into the simulation model for simulation experiments, and the optimized coating performance values ​​corresponding to each coating parameter to be verified output by the simulation model are obtained, including:

[0027] Inputting each coating parameter to be verified into the analysis model respectively, and obtaining the simulated coating performance value of each coating parameter to be verified generated by the analysis model;

[0028] Each coating parameter to be verified and each simulated coating performance value are input into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0029] In one embodiment, each coating parameter to be verified is input into the analysis model respectively, and the simulated coating performance value of each coating parameter to be verified generated by the analysis model is obtained, including:

[0030] Obtain the initial geometry model, applied load types and constraints;

[0031] For any coating parameter to be verified, the coating parameter to be verified and the constraint conditions are input into the initial geometric model to obtain a processed geometric model;

[0032] The applied load type is applied to the processed geometric model to obtain the simulated coating performance value of the coating parameters to be verified.

[0033] In one embodiment, each coating parameter to be verified and each simulated coating performance value are input into the optimization model to obtain the optimized coating performance value output by the optimization model, including:

[0034] Obtain input variables and output variables, wherein the input variables are single-phase coating composition and single-phase coating thickness, and the output variables are simulated coating performance values;

[0035] The input variables, output variables and each coating parameter to be verified are input into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0036] In one embodiment, applying the applied load type to the processed geometric model to obtain a simulated coating performance value of the coating parameter to be verified includes:

[0037] The applied load type is applied to the top surface, the middle surface and the bottom surface of the processed geometric model; and the simulated coating performance value of the coating parameter to be verified is obtained.

[0038] In one embodiment, the test coating performance value of the test coating includes at least a hardness performance value, a wear resistance performance value and a bonding strength value of the test coating.

[0039] In a second aspect, the present application also provides a mold coating generation device, the device comprising:

[0040] A design module, used to obtain coating parameters of a target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multi-phase coating components and multi-phase coating thicknesses;

[0041] a performance testing module, for obtaining a test coating performance value of the test coating generated according to the coating parameters;

[0042] The screening module is used to generate a mold coating of a target mold according to the coating parameters if the test coating performance value meets a preset first performance index.

[0043] In a third aspect, the present application further provides a computer device, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0044] Obtain coating parameters of the target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multiple single-phase coating components and multiple single-phase coating thicknesses;

[0045] obtaining a test coating property value of the test coating generated according to the coating parameters;

[0046] If the test coating performance value meets the preset first performance index, a mold coating of the target mold is generated according to the coating parameters.

[0047] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0048] Obtain coating parameters of the target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multiple single-phase coating components and multiple single-phase coating thicknesses;

[0049] obtaining a test coating property value of the test coating generated according to the coating parameters;

[0050] If the test coating performance value meets the preset first performance index, a mold coating of the target mold is generated according to the coating parameters.

[0051] In a fifth aspect, the present application further provides a computer program product, the computer program product comprising a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0052] Obtain coating parameters of the target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multiple single-phase coating components and multiple single-phase coating thicknesses;

[0053] obtaining a test coating property value of the test coating generated according to the coating parameters;

[0054] If the test coating performance value meets the preset first performance index, a mold coating of the target mold is generated according to the coating parameters.

[0055] The above-mentioned mold coating generation method, device, equipment, storage medium and program product, the mold coating design method designs multi-layer coating parameters that meet the mold test indicators according to multiple single-phase coating compositions and multiple single-phase coating thicknesses. The alternation of multiple layers in the multi-layer coating can make the structure between layers discontinuous, thereby avoiding continuous growth of defects or columnar crystal growth, etc., and the multi-layer coating can regulate the stress between coating layers and between coating bases by matching the coating composition, thickness, and mechanical properties, avoid sudden stress changes, and improve the mold coating performance; then, actual performance tests are performed on multiple test coatings. Through actual performance tests, the changes in the performance of the target mold when the test coating is prepared on the target mold can be more accurately simulated, making the experimental results more reliable, and further screening of multiple test coatings to obtain test coatings with better effects on the target mold. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A diagram showing an application environment of a mold coating generation method in one embodiment;

[0057] Figure 2 A schematic diagram of a process for producing a mold coating in one embodiment;

[0058] Figure 3 A schematic diagram of a process flow of a mold coating design method in one embodiment;

[0059] Figure 4 A schematic diagram of a process for determining the composition of a single-phase coating in another embodiment;

[0060] Figure 5 It is a schematic diagram of a process for verifying each coating to be verified in one embodiment;

[0061] Figure 6 A schematic diagram of a process for obtaining an optimized coating performance value in one embodiment;

[0062] Figure 7 A schematic diagram of a process for obtaining a simulated coating performance value from an analysis model in one embodiment;

[0063] Figure 8 A schematic diagram of a process for obtaining an optimized coating performance value from an optimization model in one embodiment;

[0064] Fig. 9 A schematic diagram of creating an initial geometric model of a coating to be verified in one embodiment;

[0065] Fig.10 A structural block diagram generated for a mold coating in one embodiment;

[0066] Fig.11 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0068] The mold coating generation method provided in this embodiment can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The terminal 102 and the server 104 can both independently execute the mold coating generation method, or they can jointly execute the mold coating generation method. For example, the terminal 102 obtains the coating parameters of the target mold from the server 104 according to the preset coating design method; the preset coating design method is a method for generating coating parameters that meet the mold test index based on a combination of multiple single-phase coating components and multiple single-phase coating thicknesses; the test coating performance value of the test coating generated according to the coating parameter is obtained from the server 104; if the test coating performance value meets the preset first performance index, the mold coating of the target mold is generated according to the coating parameter. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, and tablet computers. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0069] Moulds are essential basic equipment in industrial production and are widely used in key areas such as automobiles, home appliances, transportation, and national defense. The overall strengthening treatment and surface strengthening treatment of moulds are important ways to increase the life of moulds. Taking the physical vapor deposition (PVD) surface coating technology as an example, PVD is a common means of mould surface strengthening, which is achieved by coating the mould surface with PVD coating. However, since the film formed by the PVD coating of the mould on the substrate is usually a hard film with a hardness much higher than that of the substrate, the properties of the film material and the substrate material are very different, and the stress distribution between the inner layers of the film and between the film and the substrate is complex, especially in the mould forming work, the stress field and temperature field are periodically changed, resulting in the generated PVD single-layer binary coating with low bonding strength, not resistant to high temperature oxidation, and difficult to guarantee performance. Therefore, there is an urgent need for a design method that can guarantee the performance of PVD coating.

[0070] In one embodiment, Figure 2 As shown, a method for generating a mold coating is provided, and the method is applied to Figure 1 The terminal 102 in the example is used as an example to illustrate, and the following steps are included:

[0071] Step 202: Obtain coating parameters of a target mold according to a preset coating design method.

[0072] Among them, the preset coating design method is a method based on combining multiple single-phase coating components and multiple single-phase coating thicknesses to generate coating parameters that meet mold test indicators.

[0073] Among them, there are multiple single-phase coating compositions, for example, TiAlSiM-N (M is the added components Cr, Ta, V, Zr, etc.), TiAlSiN, TiAlN and TiN; the thicknesses of the multiple single-phase coatings can be determined based on experience or experimental data, for example, n different thicknesses randomly selected within the range of 0.01um to 5um, taking 10 thicknesses as an example, specifically the first thickness, the second thickness...the tenth thickness. According to the coating design method, a variety of single-phase coating components and a variety of single-phase coating thicknesses are randomly combined, and one of the random combination methods is used as an example for explanation. The first thickness is selected from TiAlSiCr-N, the second thickness is selected from TiAlSiN, the third thickness is selected from TiAlN, and the seventh thickness is selected from TiN. The TiN coating of the seventh thickness is prepared on the target mold, the TiAlSiN coating of the second thickness is prepared on the TiN coating, the TiAlN coating of the third thickness is prepared on the TiN coating, and the TiAlSiCr-N coating of the first thickness is prepared on the upper TiAlN coating, so as to generate a multi-element and multi-layer coating parameter; therefore, according to the combination method corresponding to the coating design method, a variety of different multi-element and multi-layer coating parameters can be generated, and then the coating parameters that meet the mold test indicators are screened out according to the design method, and the coating parameters are used as the coating parameters of the target mold, so that the coating parameters of the target mold obtained are at least one.

[0074] Step 204, obtaining a test coating performance value of the test coating generated according to the coating parameters.

[0075] If the performance test of the test coating is implemented through the terminal 102, the terminal 102 needs to be configured as a device capable of performing performance test on the coating to obtain the test coating performance value of the test coating, such as a multifunctional coating performance automatic tester; or the terminal 102 directly obtains the test coating performance value from an external tester. Specifically, the test coating performance value may include wear resistance, bonding strength, hardness performance, etc.

[0076] Step 206: If the tested coating performance value meets the preset first performance index, a mold coating of the target mold is generated according to the coating parameters.

[0077] Among them, the preset first performance indicator can be a data range set according to an empirical value, or it can be a selection rule for selecting the optimal value from multiple test coating performance values; specifically, the terminal 102 needs to be configured as a device capable of planting a coating to generate a mold coating for the target mold.

[0078] The above-mentioned mold coating generation method and mold coating design method design multi-layer coating parameters that meet mold test indicators based on multiple single-phase coating compositions and multiple single-phase coating thicknesses. The alternation of multiple layers in the multi-layer coating can make the structure between layers discontinuous, thereby avoiding continuous growth of defects or columnar crystal growth, etc., and the multi-layer coating can regulate the stress between coating layers and between coating bases by matching the coating composition, thickness, and mechanical properties, avoid sudden stress changes, and improve the mold coating performance; then, actual performance tests are performed on multiple test coatings. Through actual performance tests, the changes in the performance of the target mold when the test coating is prepared on the target mold can be more accurately simulated, making the experimental results more reliable, and further screening of multiple test coatings to obtain test coatings with better effects on the target mold.

[0079] In one embodiment, the test coating property value of the test coating includes at least a hardness property value, a wear resistance property value and a bonding strength value of the test coating.

[0080] When the test coating is applied to the target mold for performance inspection, the target mold material used in this embodiment is H13 mold steel; specifically, when testing the hardness performance value of the coating, for example, referring to HB5147-1996 "Metal Surface Rockwell Hardness Test Method", the TH310 surface Rockwell hardness tester is used to measure the Rockwell hardness of the coating surface, the applied load is 30N, the holding time is 3s, and 10 points are randomly selected on the coating surface to measure the hardness value and take the average value. When testing the wear resistance value of the coating, for example, referring to GB / T12444-2006 Metal Material Wear Test Method, the CETRUMT-3MO multifunctional friction and wear tester is used to test the coating surface, the grinding medium is Al2O3 ball, the load is 100N, the sliding rate is 10mm / s, the single effective sliding distance is 6mm, the wear time is 2h, and the experimental data is processed using TRIB analysis software. When testing the bonding strength of the coating, for example, a WDH-50A electronic universal testing machine is used to test the bonding strength between the coating and the substrate. The glue model used is FM1000, and the test is performed in accordance with the ASTMC633 standard. The test is performed at a tensile rate of 0.013 to 0.021 mm / s, and the maximum test tensile force before fracture is recorded. The bonding strength of the coating is equal to the ratio of the maximum test force to the cross-sectional area of ​​the specimen.

[0081] In one embodiment, referring to Figure 3In step 202, the coating parameters of the target mold are obtained according to the preset coating design method, including:

[0082] Step 2021, obtaining a plurality of different single-phase coating compositions and a plurality of different single-phase coating thicknesses.

[0083] The multiple different single-phase coating compositions and multiple different single-phase coating thicknesses refer to the example in the above step 202;

[0084] Specifically, when obtaining multiple different single-phase coating compositions and multiple different single-phase coating thicknesses, any one of the following two methods can be used: Method (1) obtaining single-phase coating compositions and single-phase coating thicknesses that meet the preset first screening condition from a preset material library, and directly using them as multiple different single-phase coating compositions and multiple different single-phase coating thicknesses; Method (2) obtaining single-phase coating compositions and single-phase coating thicknesses that meet the preset first screening condition from a preset material library, preparing multiple sample coatings according to each single-phase coating composition and single-phase coating thickness, and performing performance tests on the sample coatings to determine the sample coatings that meet the preset second screening condition.

[0085] Step 2022, combining the components of each single-phase coating and the thickness of each single-phase coating to obtain a plurality of different coating parameters to be verified.

[0086] Among them, the method of combining each single-phase coating component and each single-phase coating thickness, such as the full permutation method, assumes that there are m single-phase coating components and n single-phase coating thicknesses (m and n are both positive integers), and the m single-phase coating components and n single-phase coating thicknesses are fully permuted to obtain coating parameters to be verified. Specifically, when any single-phase coating component among the m single-phase coating components is given a different thickness, it constitutes a different single-phase coating structure. Therefore, the m single-phase coating components constitute a total of m×n different single-phase coating structures. Perform full permutation and combination of m×n to obtain Different multi-layer coating structures, namely different coating parameters to be verified.

[0087] Step 2023, verifying each coating parameter to be verified, obtaining coating parameters that meet the second performance index, and using the coating parameters that meet the second performance index as coating parameters of the target mold.

[0088] Among them, when verifying each coating parameter to be verified, the coating parameter to be verified is verified by simulation software to simulate the mechanical properties of the coating corresponding to the coating parameter to be verified; specifically, mechanical properties refer to the mechanical characteristics exhibited by the material under different environments (for example, temperature, medium, humidity, etc.) when subjected to various external loads (for example, tension, compression, bending, torsion, impact, alternating stress, etc.), such as elastic modulus, damping coefficient, yield stress, etc.

[0089] Among them, the coating parameters that meet the second performance indicator are obtained by at least one of the following two methods: method (a) compares the simulated coating performance values ​​of multiple coating parameters to be verified, screens out the coating parameters with the best performance, and compares the best coating parameters with the second performance indicator; it can also be method (b) further optimizes according to the performance rules of multiple coating parameters to be verified to obtain optimized coating parameters, and compares the optimized coating parameters with the second performance indicator.

[0090] In this embodiment, by combining the components of each single-phase coating and the thickness of each single-phase coating, a variety of multi-component and multi-phase coating combinations are obtained, thereby achieving the effect of establishing a large-scale experimental data source. By obtaining more abundant experimental samples, the reliability of the coating parameters of the target mold is improved.

[0091] In order to further improve the effectiveness of the obtained multiple different single-phase coating components and multiple different single-phase coating thicknesses, this embodiment uses the design idea of ​​method (2) in step 2021 to obtain multiple different single-phase coating components and multiple different single-phase coating thicknesses. Furthermore, in order to balance the complexity of data processing and data reliability, this embodiment adopts the control variable method to control the thickness of all different single-phase coating components to be the same, and test the performance of each different single-phase coating component at the same thickness. Specifically, Figure 4 As shown, in one embodiment, step 2021 obtains various single-phase coating compositions, including:

[0092] Step 20211, obtaining each target area corresponding to the experimental microplate, and each target component corresponding to each target area.

[0093] Among them, the experimental microplate is the substrate for preparing the PVD coating during the experiment. The target areas when preparing the coating on the experimental microplate are determined according to the size and position of the experimental microplate, wherein each target area corresponds to a different target component, and each target component is a single-phase coating component.

[0094] Step 20212, prepare a single-phase test coating according to the target components corresponding to each target area.

[0095] Among them, the coating generated by the simultaneous preparation of each target area is a single-phase test coating. In this embodiment, the diameter of the single-phase thin film wafer of the single-phase test coating is 10 mm. Specifically, in order to obtain a uniform coating, this embodiment adopts a magnetron sputtering coating method to prepare a single-phase test coating. The coating obtained based on this preparation method has no phase change, stable compound composition, and better coating uniformity. In addition, the magnetron sputtering coating method can accurately control the content and sputtering position of each target material, so as to facilitate the preparation of thin film coatings with different content of each element.

[0096] Step 20213, obtaining each test coating performance value of the coating in each target area, and determining the target component corresponding to the test coating performance value that meets the preset third performance index as the single-phase coating component.

[0097] Among them, the test coating performance value includes at least one of the following: film hardness index, coating hardness uniformity, critical load of film-substrate interface adhesion failure, and surface anti-oxidation temperature; specifically, the coating in each target area of ​​the single-phase test coating is tested by an external test device to obtain each test coating performance value; specifically, the test method for obtaining the test coating performance value can adopt nanoindentation method and nanoscratch method, and the nanoindentation parameters are loading load 7500μN, loading rate and unloading rate are both 1000μN / s, loading time and unloading time are both 7.5s, and holding time is 2s; nanoscratch parameters are maximum loading force 100mN, force value resolution 3nN, maximum displacement 50um, and displacement resolution 0.01nm. The third performance index corresponding to the test coating performance value includes at least one of the following: film hardness index ≥250, coating hardness uniformity within 5%, critical load of film-substrate interface adhesion failure ≥80N, and surface anti-oxidation temperature ≥1000℃. Furthermore, in order to facilitate the experimenters to observe the test coating performance values, cloud maps corresponding to the test coating performance values ​​can also be generated by the grid difference method, for example, film hardness cloud map, fracture toughness cloud map and film bonding strength cloud map, etc.

[0098] In this embodiment, by preparing a single-phase test coating containing various single-phase coating components on an experimental microplate at one time, the effect of obtaining a large amount of experimental data in a short time is achieved, and actual performance tests are carried out on the test coatings in each target area respectively, and the target components that meet the third performance indicator are screened out, thereby improving the data validity of the single-phase coating components.

[0099] Furthermore, in one embodiment, a high-throughput magnetron sputtering coating method is used to prepare a single-phase test coating according to a target composition corresponding to a target area.

[0100] In this embodiment, a high-throughput magnetron sputtering coating method and a high-throughput screening method are used to execute the test process with an automated operating system, sensitive and fast detection instruments are used to collect experimental result data, and computers are used to analyze and process the experimental data. Tens of millions of samples are tested at the same time, and multiple groups of experimental schemes are set up on the same single-phase film using magnetron sputtering and experimental data are collected. A large number of control groups are set up through one experiment, which effectively saves time costs.

[0101] In one embodiment, Figure 5 As shown, step 2023 verifies each coating parameter to be verified, obtains coating parameters that meet the second performance index, and uses the coating parameters that meet the second performance index as coating parameters of the target mold, including:

[0102] Step 20231, input each coating parameter to be verified into the simulation model to perform a simulation experiment, and obtain the optimized coating performance value corresponding to each coating parameter to be verified output by the simulation model.

[0103] Among them, for each coating parameter to be verified, the coating parameter to be verified is input into the simulation model, and the simulation model can simulate and analyze the coating corresponding to the coating parameter to be verified to obtain the mechanical properties of the coating corresponding to the coating parameter to be verified, and the mechanical properties are used as the simulated coating performance value of the coating parameter to be verified, wherein the simulated coating performance value includes at least one of the film hardness index, the critical load of film-substrate interface adhesion failure, and the surface anti-oxidation temperature, and the second performance index corresponding to the simulated coating performance value includes at least one of the film hardness index, the critical load of film-substrate interface adhesion failure, and the surface anti-oxidation temperature; further, referring to the method (a) and method (b) in step 2023, the optimized coating performance values ​​corresponding to each coating parameter to be verified output by the simulation model also include two types: type (a) compares the simulated coating performance values ​​of multiple coating parameters to be verified, screens out the coating parameter with the best performance, and uses the best coating parameter as the optimized coating performance value; type (b) further optimizes according to the performance laws of multiple coating parameters to be verified to obtain the optimized coating performance value.

[0104] Step 20232, compare each optimized coating performance value with the second performance index to obtain coating parameters that meet the second performance index.

[0105] In the present embodiment, each coating parameter to be verified is input into the simulation model for simulation experiments. Compared with the "design-preparation-inspection" process in the traditional technology, the test steps of the present embodiment are more targeted, forming a design process of "screening single-phase coatings--verifying the performance of single-phase coatings--obtaining multi-component multi-layer coatings according to the combination of each single-phase coating--simulating and verifying the multi-component multi-component multi-component coating parameters--preparing the verified multi-component multi-component multi-component coating parameters and actually verifying them again". Through multi-level test verification, the performance of the target mold coating finally generated is improved; and the simulation process of the coating parameters to be verified is based on computer software, and the verification speed is fast, which is suitable for the verification of multiple coating parameters to be verified with large-scale data.

[0106] From the process of obtaining the coating parameters to be verified, it can be seen that the variables in the coating parameters to be verified (i.e., single-phase coating composition, single-phase coating thickness) are discrete variables. Since for discrete variables, the number of variables is closely related to the experimental time, a large number of discrete samples can obtain better experimental results. Therefore, if the response relationship between the input variables and the simulated coating performance values ​​can be analyzed, the experimental time can be shortened and the optimized coating parameters can be obtained more easily. Therefore, in order to obtain type (b) in the above step 2023, specifically, in one embodiment, the simulation model includes an analysis model and an optimization model; Figure 6 As shown, in step 2023, each coating parameter to be verified is input into the simulation model for simulation experiment, and the optimized coating performance value corresponding to each coating parameter to be verified output by the simulation model is obtained, including:

[0107] Step 0231, input each coating parameter to be verified into the analysis model respectively, and obtain the simulated coating performance value of each coating parameter to be verified generated by the analysis model.

[0108] Among them, the analytical model is used to perform simulation experiments on the coating parameters to be verified.

[0109] In step 0232, each coating parameter to be verified and each simulated coating performance value are input into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0110] The optimization model is used to analyze each coating parameter to be verified and each simulated coating performance value of the coating parameter to be verified, so as to obtain the correlation (or response relationship) between the coating parameter to be verified and the simulated coating performance value. Specifically, the simulated coating performance value corresponding to each coating parameter to be verified output by the optimization model is the simulated coating performance value in type (b).

[0111] In one embodiment, Figure 7As shown, in step 0231, each coating parameter to be verified is input into the analysis model respectively, and the simulated coating performance value of each coating parameter to be verified generated by the analysis model is obtained, including:

[0112] Step 2311, obtaining the initial geometric model, applied load type and constraint conditions.

[0113] The initial geometric model is determined according to the coating geometry; the applied load type is the type of load applied to the coating, including static load and dynamic load.

[0114] Step 2312: for any coating parameter to be verified, the initial geometric model is processed according to the coating parameter to be verified and the constraint conditions to obtain a processed geometric model.

[0115] Among them, taking the finite element analysis software as an analysis model as an example, the analysis process of the finite element analysis software includes: step 1, establishing or importing a geometric model; defining material properties (or custom editing and adding); meshing the model; step 2, selecting the type of load to be applied and establishing constraints; analysis and calculation; step 3, viewing the analysis results; and judging the correctness of the analysis results.

[0116] Specifically, the process of constructing a finite element model for any coating parameter to be verified in this embodiment specifically includes:

[0117] Sa, defines material properties and type elements.

[0118] Among them, first define the unit number to select the type of shell unit, and then set the composition and thickness of each single-phase coating in turn when the number of single-phase coatings contained in the coating is determined. Specifically, the coating section information and 4 nodes are defined. For multi-layer shell units, the thickness, material and direction of the coating are set. On each layer structure, 1, 3, 5, 7 or 9 integration points are defined along the thickness direction using the section input command, and the thickness of the coating is set as a function of the coordinates or nodes using the function tool.

[0119] Sb, establish the initial geometric model of the coating to be verified.

[0120] Among them, the coating to be verified is the coating corresponding to the coating parameters to be verified. When establishing the finite element model, we first simplified the three-dimensional indentation model into a two-dimensional model, which facilitates modeling and reduces the amount of calculation. The indenter can be equivalent to a conical indenter with the same projection area and depth ratio. The conical indenter is made of diamond, and its elastic modulus is 1140GPa, which is one order of magnitude higher than the elastic modulus of the coating to be verified, the pressed material. Therefore, the diamond indenter is simplified as a rigid contact body in the model. Considering that in the indentation process, only the material to be tested in the area near the indenter is greatly affected by the load, while the material far away is very little affected by the load and approaches zero. When modeling the finite element, only local materials can be taken, that is, the material size in the model is smaller than that in the actual test, so the number of units in the model can be reduced. Since the process of the conical indenter pressing into the material to be tested is a typical axisymmetric problem, a two-dimensional finite element model can be used to simulate this problem. At the same time, considering the symmetry of the structure and load, the calculation time is shortened, and only the right half of the film / substrate system is taken for finite element simulation calculation.

[0121] Specifically, Fig. 9 As shown, key points, lines, and surfaces are created in sequence. Key points 1, 2, 3, and 4 are the coating part, and key points 5 and 6 are the indenter part. Key point 6 can be created by rotating the coordinate system and using the working coordinate system. Key lines L1, L2, L3, L4, and L5 are established, and key surfaces are established based on the key lines.

[0122] Sc, divide the mesh of the established finite element model.

[0123] Among them, in finite element analysis, the meshing situation is directly related to the correctness and accuracy of the calculation results. Generally speaking, the finer the mesh, the more accurate the analysis results, but it will increase the calculation time and require more storage space. When dividing the mesh, you can first select the mesh type of the model as quadrilateral meshing, and specify the meshing method as mapped meshing; then select all the lines in the model except the circumference, group the selected lines into a line group, use the line group to divide the circular surface generated in the previous step, and glue the divided surfaces together; then delete the previous line group, select all the lines in the model, and regroup the selected lines into a new line group; finally, use the new line group to control the mesh density, perform meshing, and generate units and nodes;

[0124] Sd, adds constraints to the nodes in the finite element model to obtain the processed geometric model.

[0125] Specifically, first, define the contact pair, including: target surface: lines, type: Rigid / Pilot, select key line L5, set the indenter as a rigid body, set key point 6 as a control point, define the contact pair: use surface-to-surface contact, set key line L1 as the contact surface, and friction coefficient 0.15. Then apply boundary conditions and load conditions, select three nodes to impose constraints, restrict the movement of the first node in the X, Y, and Z directions; restrict the movement of the second node in the X and Z directions; restrict the movement of the third node in the Z direction. Specifically, constrain the nodes on line 4 in the x direction, constrain the nodes on line 3 in the x and y directions, and apply y-direction displacement to key point 6.

[0126] Step 2313, applying the applied load type to the processed geometric model to obtain the simulated coating performance value of the coating parameter to be verified.

[0127] The load types include static loads and dynamic loads; the static load types and dynamic load types are input into the finite element analysis software to obtain the calculation results, that is, the simulated coating performance values ​​of the coating parameters to be verified. In this embodiment, the analysis calculation in the finite element analysis software only has translational degrees of freedom. This unit is suitable for analyzing application problems with linear, large-angle rotation or nonlinear large strain characteristics. The change of shell thickness is considered in the nonlinear analysis. The accuracy of simulating composite film is controlled by the first-order shear deformation theory (Mindlin-Reissner shell theory).

[0128] Specifically, the nonlinear solution results are solved by geometric nonlinear analysis, and parameter indicators such as stress, total strain, elastic strain and plastic strain are expressed. By obtaining the stress-strain relationship of the thin film coating system at different strain rates, the stress corresponding to 0.2% strain is taken as the yield strength of the thin film coating. The greater the yield strength, the better the mechanical properties.

[0129] In one embodiment, the applied load type is applied to the top surface, the middle surface and the bottom surface of the processed geometric model; and the simulated coating performance value of the coating parameter to be verified is obtained.

[0130] Specifically, in the finite element analysis software, the KEYOPT(8)=2 command stream is used to store the stress, strain and other thin film results of the middle surface, and the KEYOPT(9)=1 is used to read the initial thickness data from the user subroutine.

[0131] In this embodiment, by performing simulation through analysis software, the experimental plan can be adjusted quickly and conveniently at any time, thus shortening the experimental cycle.

[0132] After obtaining each coating parameter to be verified and the simulated coating performance value of each coating parameter to be verified according to the finite element analysis, in order to analyze the corresponding relationship between the input variables and the simulated coating performance value, the response surface equation is applied to fit these coating parameters to be verified, and the quadratic polynomial function expression between the output response value and each input variable can be obtained, that is, the response surface equation, which can be used to replace the finite element simulation result; then the equation is called by the Monte Carlo simulation method, and the output response variable is simulated many times to obtain various statistical parameters of the output response variable, and the output response variable is subjected to probabilistic sensitivity analysis relative to each input variable. Specifically, Figure 8 As shown, in step 0232, each coating parameter to be verified and each simulated coating performance value are input into the optimization model to obtain the optimized coating performance value output by the optimization model, including:

[0133] Step 2321, obtain input variables and output variables.

[0134] The input variables are user-defined input variables. In this embodiment, the input variables are the single-phase coating composition and the single-phase coating thickness, and the output variables are the simulated coating performance values.

[0135] Step 2322, input the input variables, output variables and each coating parameter to be verified into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0136] Among them, the optimization model is Monte Carlo model as an example, the simulated coating performance value is taken as y, and the coating parameter to be verified is taken as variable z. It can be seen that there is a correlation between the simulated coating performance value y and the coating parameter to be verified z, that is, y=f(z). Specifically, the coating parameter to be verified z is: {I1(x1, y1), I2(x2, y2), I3(x3, y3), I4(x4, y4)...I n (x n ,y n )}, the variables in z are x and y, where I i represents the i-th layer in the coating to be verified, x i represents the composition of the i-th single-phase coating, y i Represents the thickness of the i-th single-phase coating.

[0137] Specifically, the input variables are user-defined input variables. For the coating parameters to be verified, the input variables are the single-phase coating composition x and the single-phase coating thickness y. The Monte Carlo method uses a random number generator to generate random numbers within (0, 1), and converts the random numbers into sampling values ​​that conform to the probability distribution of the random variables (x, y) through direct or indirect sampling. Optionally, in this application, the random number generator used in the Monte Carlo model uses a direct sampling method.

[0138] For example, the sampling value obtained by the first sampling is: 11 (x 11 ,y 11 ), I 21 (x 21 ,y 21 ), I 31 (x 31 ,y 31 ), I 41 (x 41 ,y 41 )……I n1 (x n1 ,y n1 )},

[0139] The sampling value obtained by the second sampling is {I 12 (x 12 ,y 12 ), I 22 (x 22 ,y 22 ), I 32 (x 32 ,y 32 ), I 42 (x 42 ,y 42 )……I n2 (x n2 ,y n2 )},

[0140] The sampling value obtained by the Nth sampling is {I 1N (x 1N ,y 1N ), I 2N (x 2N ,y 2N ), I 3N (x 3N ,y 3N ), I 4N (x 4N ,y 4N )……I nN (x nN ,y nN )}

[0141] Among them, I ij represents the i-th single-phase coating obtained by sampling the j-th sampling, x ij represents the single-phase coating composition of the i-th single-phase coating obtained by the sampling value obtained by the j-th sampling, y ij Represents the single-phase coating thickness of the i-th single-phase coating obtained by the sampling value obtained by the j-th sampling.

[0142] Repeated independent sampling (simulation) N times, when the number of simulations is large enough, the probability distribution and digital characteristics of the simulated coating performance value y can be approximately the same as the actual situation.

[0143] After determining the probability distribution and digital characteristics of the simulated coating performance value y, the simulated coating performance value y that meets the preset optimization conditions is determined, and the parameters to be verified corresponding to the simulated coating performance value y that meets the preset optimization conditions are used as the optimized coating performance value.

[0144] Obtain each target area corresponding to the experimental microplate, and each target component corresponding to each target area; adopt a high-throughput magnetron sputtering coating method to prepare a single-phase test coating according to the target component corresponding to each target area; obtain each test coating performance value of the coating in each target area, and determine the target component corresponding to the test coating performance value that meets the preset third performance index as the single-phase coating component; obtain a plurality of different single-phase coating thicknesses; combine each single-phase coating component and each single-phase coating thickness to obtain a plurality of different coating parameters to be verified; obtain an initial geometric model, applied load type and constraint conditions; for any coating parameter to be verified, input the coating parameter to be verified and the constraint conditions into the initial geometric model to obtain a processed geometric model; The load type is applied to the processed geometric model to obtain the simulated coating performance value of the coating parameter to be verified; the input variable and the output variable are obtained, wherein the input variable is the single-phase coating composition and the single-phase coating thickness, and the output variable is the simulated coating performance value; the input variable, the output variable and each coating parameter to be verified are input into the optimization model to obtain the optimized coating performance value output by the optimization model; each optimized coating performance value is compared with the second performance index to obtain the coating parameter that meets the second performance index; the coating parameter that meets the second performance index is used as the coating parameter of the target mold; the test coating performance value of the test coating generated according to the coating parameter of the target mold is obtained; if the test coating performance value meets the preset first performance index, the mold coating of the target mold is generated according to the coating parameter. Compared with "design-preparation-inspection", the test steps in the design process of this embodiment are more targeted, forming "screening single-phase coating--verifying single-phase coating performance--obtaining multi-layer coating according to each single-phase coating combination--simulating and verifying the multi-layer coating parameters--preparing the verified multi-layer coating parameters and actually verifying them again", and the coating performance of the target mold finally generated is improved through multi-level test verification. Moreover, the alternation of multiple layers in the multi-layer coating can make the structure between layers discontinuous, thereby avoiding continuous growth of defects or columnar crystal growth, etc., and improving the surface performance of the mold. In addition, the multi-layer coating can regulate the stress between coating layers and between coating bases by matching the coating composition, thickness, and mechanical properties, avoiding sudden stress changes, thereby improving the comprehensive performance of the mold coating.

[0145] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0146] Based on the same inventive concept, this embodiment also provides a mold coating generation device for implementing the mold coating generation method involved above. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above method, so the specific limitations in one or more embodiments of the mold coating generation device provided below can refer to the limitations of the mold coating generation method above, and will not be repeated here.

[0147] In one embodiment, Fig.10 As shown, a mold coating generation device 100 is provided, comprising: an acquisition module 110, a performance testing module 120 and a screening module 130, wherein:

[0148] An acquisition module 110 is used to acquire coating parameters of a target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multi-phase coating components and multi-phase coating thicknesses;

[0149] A performance testing module 120, for obtaining a test coating performance value of the test coating generated according to the coating parameters;

[0150] The screening module 130 is used to generate a mold coating of a target mold according to the coating parameters if the tested coating performance value meets a preset first performance indicator.

[0151] In one embodiment, the device further comprises a design module, the design module comprising:

[0152] An acquisition submodule, used for acquiring a plurality of different single-phase coating compositions and a plurality of different single-phase coating thicknesses;

[0153] A combination submodule, used for combining each single-phase coating component and each single-phase coating thickness to obtain a plurality of different coating parameters to be verified;

[0154] A verification submodule, used to verify each coating parameter to be verified, and obtain coating parameters that meet the second performance index;

[0155] The screening submodule is used to use the coating parameters that meet the second performance index as the coating parameters of the target mold.

[0156] In one embodiment, the acquisition submodule includes:

[0157] A division unit is used to obtain each target area of ​​the experimental microplate and each target component corresponding to each target area;

[0158] A preparation unit, used for preparing a single-phase test coating according to target components corresponding to each target area;

[0159] The testing unit is used to obtain the test coating performance value of the coating in each target area, and determine the target component corresponding to the test coating performance value that meets the preset third performance index as the single-phase coating component.

[0160] In one embodiment, the preparation unit is further used to prepare a single-phase test coating according to target components corresponding to each target area by adopting a high-throughput magnetron sputtering coating method.

[0161] In one embodiment, the test coating property values ​​include nanoindentation test data and nanoscratch test data.

[0162] In one embodiment, the verification submodule includes:

[0163] A simulation unit is used to input each coating parameter to be verified into a simulation model to perform a simulation experiment, and obtain an optimized coating performance value corresponding to each coating parameter to be verified output by the simulation model;

[0164] The output unit is used to compare each optimized coating performance value with the second performance index to obtain coating parameters that meet the second performance index.

[0165] In one embodiment, the simulation unit includes:

[0166] The analysis subunit is used to input each coating parameter to be verified into the analysis model respectively, and obtain the simulated coating performance value of each coating parameter to be verified generated by the analysis model;

[0167] The optimization subunit is used to input each coating parameter to be verified and each simulated coating performance value into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0168] In one embodiment, the analysis subunit further comprises:

[0169] Acquisition components, used to obtain the initial geometric model, applied load type and constraint conditions;

[0170] A processing component, for inputting the coating parameter to be verified and the constraint conditions to the initial geometric model for any coating parameter to be verified, so as to obtain a processed geometric model;

[0171] The simulation component is used to apply the applied load type to the processed geometric model to obtain the simulated coating performance value of the coating parameter to be verified.

[0172] In one embodiment, the optimization subunit is further used to obtain input variables and output variables, wherein the input variables are single-phase coating composition and single-phase coating thickness, and the output variable is a simulated coating performance value;

[0173] The input variables, output variables and each coating parameter to be verified are input into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0174] In one embodiment, the simulation component is further used to apply the applied load type to the top surface, the middle surface and the bottom surface of the processed geometric model; and obtain the simulated coating performance value of the coating parameter to be verified.

[0175] Each module in the above-mentioned mold coating generation device can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0176] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.11 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a mold coating generation method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0177] Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0178] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0179] Obtain coating parameters of the target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multiple single-phase coating components and multiple single-phase coating thicknesses;

[0180] obtaining a test coating property value of the test coating generated according to the coating parameters;

[0181] If the test coating performance value meets the preset first performance index, a mold coating of the target mold is generated according to the coating parameters.

[0182] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining multiple different single-phase coating compositions and multiple different single-phase coating thicknesses; combining each single-phase coating composition and each single-phase coating thickness to obtain multiple different coating parameters to be verified; verifying each coating parameter to be verified to obtain a coating parameter that meets a second performance indicator; and using the coating parameter that meets the second performance indicator as the coating parameter of the target mold.

[0183] In one embodiment, the processor also implements the following steps when executing the computer program: obtaining each target area of ​​the experimental microplate, and each target component corresponding to each target area; preparing a single-phase test coating according to the target components corresponding to each target area; obtaining the test coating performance value of the coating in each target area, and determining the target component corresponding to the test coating performance value that meets the preset third performance indicator as the single-phase coating component.

[0184] In one embodiment, when the processor executes the computer program, the following steps are also implemented: a single-phase test coating is prepared according to the target composition corresponding to each target area by using a high-throughput magnetron sputtering coating method.

[0185] In one embodiment, the test coating property values ​​include nanoindentation test data and nanoscratch test data.

[0186] In one embodiment, when the processor executes the computer program, the following steps are also implemented: each coating parameter to be verified is input into the simulation model for simulation experiments, and the optimized coating performance value corresponding to each coating parameter to be verified output by the simulation model is obtained; each optimized coating performance value is compared with the second performance indicator to obtain the coating parameters that meet the second performance indicator.

[0187] In one embodiment, the simulation model includes an analysis model and an optimization model; when the processor executes the computer program, the following steps are also implemented: each coating parameter to be verified is input into the analysis model respectively to obtain the simulated coating performance value of each coating parameter to be verified generated by the analysis model; each coating parameter to be verified and each simulated coating performance value are input into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0188] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining an initial geometric model, an applied load type, and constraints; for any coating parameter to be verified, inputting the coating parameter to be verified and the constraints into the initial geometric model to obtain a processed geometric model; applying the applied load type to the processed geometric model to obtain a simulated coating performance value of the coating parameter to be verified.

[0189] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining input variables and output variables, wherein the input variables are the single-phase coating composition and the single-phase coating thickness, and the output variables are the simulated coating performance values; inputting the input variables, output variables and each coating parameter to be verified into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0190] In one embodiment, when the processor executes the computer program, the following steps are also implemented: applying the applied load type to the top surface, the middle surface and the bottom surface of the processed geometric model; and obtaining the simulated coating performance value of the coating parameter to be verified.

[0191] In one embodiment, the test coating performance value of the test coating includes at least a hardness performance value, a wear resistance performance value and a bonding strength value of the test coating.

[0192] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0193] Obtain coating parameters of the target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multiple single-phase coating components and multiple single-phase coating thicknesses;

[0194] obtaining a test coating property value of the test coating generated according to the coating parameters;

[0195] If the test coating performance value meets the preset first performance index, a mold coating of the target mold is generated according to the coating parameters.

[0196] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining multiple different single-phase coating compositions and multiple different single-phase coating thicknesses; combining each single-phase coating composition and each single-phase coating thickness to obtain multiple different coating parameters to be verified; verifying each coating parameter to be verified to obtain a coating parameter that meets a second performance indicator; and using the coating parameter that meets the second performance indicator as the coating parameter of the target mold.

[0197] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining each target area of ​​the experimental microplate, and each target component corresponding to each target area; preparing a single-phase test coating according to the target component corresponding to each target area; obtaining the test coating performance value of the coating in each target area, and determining the target component corresponding to the test coating performance value that meets the preset third performance indicator as the single-phase coating component.

[0198] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: a single-phase test coating is prepared according to the target composition corresponding to each target area by using a high-throughput magnetron sputtering coating method.

[0199] In one embodiment, the test coating property values ​​include nanoindentation test data and nanoscratch test data.

[0200] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: each coating parameter to be verified is input into the simulation model for simulation experiments, and the optimized coating performance value corresponding to each coating parameter to be verified output by the simulation model is obtained; each optimized coating performance value is compared with the second performance indicator to obtain the coating parameters that meet the second performance indicator.

[0201] In one embodiment, the simulation model includes an analysis model and an optimization model; when the processor executes the computer program, the following steps are also implemented: each coating parameter to be verified is input into the analysis model respectively to obtain the simulated coating performance value of each coating parameter to be verified generated by the analysis model; each coating parameter to be verified and each simulated coating performance value are input into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0202] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining an initial geometric model, an applied load type, and constraints; for any coating parameter to be verified, inputting the coating parameter to be verified and the constraints into the initial geometric model to obtain a processed geometric model; applying the applied load type to the processed geometric model to obtain a simulated coating performance value of the coating parameter to be verified.

[0203] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining input variables and output variables, wherein the input variables are the single-phase coating composition and the single-phase coating thickness, and the output variables are the simulated coating performance values; inputting the input variables, output variables and each coating parameter to be verified into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0204] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: applying the applied load type to the top surface, the middle surface and the bottom surface of the processed geometric model; and obtaining the simulated coating performance value of the coating parameter to be verified.

[0205] In one embodiment, the test coating performance value of the test coating includes at least a hardness performance value, a wear resistance performance value and a bonding strength value of the test coating.

[0206] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0207] Obtain coating parameters of the target mold according to a preset coating design method; the preset coating design method is a method for generating coating parameters that meet mold test indicators by combining multiple single-phase coating components and multiple single-phase coating thicknesses;

[0208] obtaining a test coating property value of the test coating generated according to the coating parameters;

[0209] If the test coating performance value meets the preset first performance index, a mold coating of the target mold is generated according to the coating parameters.

[0210] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining multiple different single-phase coating compositions and multiple different single-phase coating thicknesses; combining each single-phase coating composition and each single-phase coating thickness to obtain multiple different coating parameters to be verified; verifying each coating parameter to be verified to obtain a coating parameter that meets a second performance indicator; and using the coating parameter that meets the second performance indicator as the coating parameter of the target mold.

[0211] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining each target area of ​​the experimental microplate, and each target component corresponding to each target area; preparing a single-phase test coating according to the target component corresponding to each target area; obtaining the test coating performance value of the coating in each target area, and determining the target component corresponding to the test coating performance value that meets the preset third performance indicator as the single-phase coating component.

[0212] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: a single-phase test coating is prepared according to the target composition corresponding to each target area by using a high-throughput magnetron sputtering coating method.

[0213] In one embodiment, the test coating property values ​​include nanoindentation test data and nanoscratch test data.

[0214] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: each coating parameter to be verified is input into the simulation model for simulation experiments, and the optimized coating performance value corresponding to each coating parameter to be verified output by the simulation model is obtained; each optimized coating performance value is compared with the second performance indicator to obtain the coating parameters that meet the second performance indicator.

[0215] In one embodiment, the simulation model includes an analysis model and an optimization model; when the processor executes the computer program, the following steps are also implemented: each coating parameter to be verified is input into the analysis model respectively to obtain the simulated coating performance value of each coating parameter to be verified generated by the analysis model; each coating parameter to be verified and each simulated coating performance value are input into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0216] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining an initial geometric model, an applied load type, and constraints; for any coating parameter to be verified, inputting the coating parameter to be verified and the constraints into the initial geometric model to obtain a processed geometric model; applying the applied load type to the processed geometric model to obtain a simulated coating performance value of the coating parameter to be verified.

[0217] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining input variables and output variables, wherein the input variables are the single-phase coating composition and the single-phase coating thickness, and the output variables are the simulated coating performance values; inputting the input variables, output variables and each coating parameter to be verified into the optimization model to obtain the optimized coating performance value output by the optimization model.

[0218] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: applying the applied load type to the top surface, the middle surface and the bottom surface of the processed geometric model; and obtaining the simulated coating performance value of the coating parameter to be verified.

[0219] In one embodiment, the test coating performance value of the test coating includes at least a hardness performance value, a wear resistance performance value and a bonding strength value of the test coating.

[0220] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0221] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited thereto. The processors involved in each embodiment provided in this application may be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, data processing logic devices based on quantum computing, etc., but are not limited thereto.

[0222] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0223] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for producing a mold coating, characterized in that: The method comprises: obtaining a plurality of different single-phase coating compositions and a plurality of different single-phase coating thicknesses; Combining the components of each single-phase coating and the thickness of each single-phase coating to obtain a plurality of different coating parameters to be verified; each coating parameter to be verified is a multi-element multi-layer coating parameter; Obtaining an initial geometric model, applied load type and constraint conditions; the initial geometric model is determined according to the coating geometry, and the initial geometric model is a finite element model in a finite element analysis software; For each coating parameter to be verified, the initial geometric model is processed according to the coating parameter to be verified and the constraint condition to obtain a processed geometric model; Applying the applied load type to the processed geometric model, and obtaining a simulated coating performance value of the coating parameter to be verified based on finite element analysis; Inputting each coating parameter to be verified and the simulated coating performance value of each coating parameter to be verified into the Monte Carlo model to obtain the optimized coating performance value output by the Monte Carlo model; Comparing each optimized coating performance value with the second performance index to obtain coating parameters that meet the second performance index; Using the coating parameters that meet the second performance index as coating parameters of the target mold; Obtaining a test coating performance value of the test coating generated according to the coating parameters of the target mold; If the test coating performance value meets the preset first performance index, the mold coating of the target mold is generated according to the coating parameters.

2. The method according to claim 1, characterized in that The method of obtaining a plurality of different single-phase coating compositions comprises: Acquire each target area of ​​the experimental microplate, and each target component corresponding to each target area; preparing a single-phase test coating according to the target composition corresponding to each of the target areas; The test coating performance value of the coating in each of the target areas is obtained, and the target component corresponding to the test coating performance value that meets the preset third performance index is determined as the single-phase coating component.

3. The method according to claim 1, characterized in that The combining of the single-phase coating components and the single-phase coating thicknesses comprises: The single-phase coating composition and the single-phase coating thickness are fully arranged.

4. The method according to claim 1, characterized in that: The applied load types include static loads and dynamic loads.

5. The method according to claim 1, characterized in that Apply load types to the top, mid, and bottom faces of the processed geometry.

6. The method according to claim 1, characterized in that The step of inputting each coating parameter to be verified and the simulated coating performance value of each coating parameter to be verified into the Monte Carlo model to obtain the optimized coating performance value output by the Monte Carlo model comprises: The coating parameters to be verified are used as independent variables, and the simulated coating performance values ​​are used as dependent variables; the coating parameters to be verified include the composition and thickness of each single-phase coating; Using a random number generator to generate random numbers, and converting the random numbers into sampling coating parameters that conform to the probability distribution of the coating parameters to be verified; Determining probability distribution and numerical characteristics of simulated coating performance values ​​based on the sampled coating parameters; The simulated coating performance value that meets the preset optimization conditions is used as the optimized coating performance value output by the Monte Carlo model.

7. A mold coating generating device, characterized in that: The device comprises: A design module is used to obtain a plurality of different single-phase coating compositions and a plurality of different single-phase coating thicknesses; each coating parameter to be verified is a multi-element multi-layer coating parameter; Obtaining an initial geometric model, applied load type and constraint conditions; the initial geometric model is determined according to the coating geometry, and the initial geometric model is a finite element model in a finite element analysis software; For each coating parameter to be verified, the initial geometric model is processed according to the coating parameter to be verified and the constraint condition to obtain a processed geometric model; Applying the applied load type to the processed geometric model to obtain a simulated coating performance value of the coating parameter to be verified; Inputting each coating parameter to be verified and the simulated coating performance value of the coating parameter to be verified into the Monte Carlo model to obtain the optimized coating performance value output by the Monte Carlo model; Combining the single-phase coating components and the single-phase coating thicknesses to obtain a plurality of different coating parameters to be verified; comparing the optimized coating performance values ​​with the second performance index to obtain coating parameters that meet the second performance index; Using the coating parameters that meet the second performance index as coating parameters of the target mold; a performance testing module, used to obtain a test coating performance value of the test coating generated according to the coating parameters of the target mold; The screening module is used to generate the mold coating of the target mold according to the coating parameters if the test coating performance value meets the preset first performance index.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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