Method and system for generating two-dimensional aggregate structure model of catalyst layer

Abstract

The invention discloses a method and a system for generating a two-dimensional aggregate structure model of a catalyst layer. The method comprises the following steps: acquiring target quantities corresponding to carriers, catalyst particles and ionomers respectively; generating a carrier in the catalyst layer grid, and marking a grid region where the carrier is located by adopting a first mark value; available blank adjacent points of the catalyst layer grid areas marked by adopting the first mark values are obtained, catalyst particles are generated at the available blank adjacent points, and the grid areas where the catalyst particles are located are marked by adopting second mark values; obtaining placement points in the remaining area of the catalyst layer grid to generate an ionomer, and marking the grid area where the ionomer is located by adopting a third mark value; and filling gaps of the generated ionomer, and marking an ionomer connected component meeting an area threshold condition by adopting a third mark value to obtain a catalyst layer two-dimensional aggregate structure model. By utilizing the scheme of the invention, the real distribution state and dependency relationship of each phase in the catalyst layer can be accurately reflected.

Description

Technical Field

[0001] The present application generally relates to the technical field of catalyst layer structure model construction, and more specifically, to a method and system for generating a catalyst layer two-dimensional aggregate structure model. Background Art

[0002] Reconstructing a catalytic layer with real structural characteristics and using numerical methods to study the impact of its internal structure and property changes on the transfer and electrochemical processes are effective ways to optimize the catalytic layer design and improve the performance and durability of fuel cells.

[0003] However, in the prior art, the actual distribution state and dependence of each phase cannot be reflected in the process of constructing the catalyst layer structure model. This leads to deviations in the constructed model when predicting the performance of the catalyst layer and fails to accurately simulate the complex interactions in the actual catalytic process.

[0004] In view of this, there is an urgent need to provide a scheme for generating a two-dimensional aggregate structure model of the catalytic layer, so that the catalytic layer random reconstruction technology provided by the present invention can accurately reflect the actual distribution state and dependence of each phase in the catalytic layer, so that the constructed model has deviations in predicting the performance of the catalytic layer and cannot accurately simulate the complex interactions in the actual catalytic process. Summary of the invention

[0005] In order to at least solve one or more of the technical problems mentioned above, the present application proposes a solution for generating a two-dimensional aggregate structure model of a catalytic layer in multiple aspects.

[0006] In a first aspect, the present application provides a method for generating a two-dimensional agglomerate structure model of a catalytic layer, comprising: setting an area parameter of a catalytic layer grid and a volume fraction of each phase of material in the catalytic layer, and obtaining a target quantity corresponding to each phase of material based on the volume fraction of each phase of material in the catalytic layer, wherein each phase of material in the catalytic layer includes a carrier, catalyst particles, and an ionomer; generating a first number of carriers in the catalytic layer grid, marking a grid area where the generated carriers are located with a first marking value, wherein the first quantity is a target quantity corresponding to the carrier; obtaining available blank adjacent points in the catalytic layer grid area marked with the first marking value, and obtaining the target quantity corresponding to each phase of material in the catalytic layer based on the volume fraction of each phase of material in the catalytic layer. The second number of catalyst particles or the number of available blank adjacent points are generated by using the available blank adjacent points, and the grid area where the catalyst particles are located is marked with a second marking value, wherein the second number is the target number corresponding to the catalyst particles; a third number of placeable points are obtained in the remaining area in the catalytic layer grid, ionomers are generated at the placeable points, and the grid area where the ionomer is located is marked with a third marking value, wherein the third number is the target number corresponding to the ionomer; the gaps of the generated ionomers are filled, and the connected components of the ionomers that meet the area threshold condition are marked with the third marking value to obtain a two-dimensional agglomerate structure model of the catalytic layer.

[0007] In some embodiments, generating a first number of carriers in the catalytic layer grid includes: generating a plurality of initial carriers in the catalytic layer grid whose Euclidean distances satisfy a minimum Euclidean distance threshold condition; in the catalytic layer grid, based on the initial carriers, further generating a plurality of diffusion carriers, the sum of the number of diffusion carriers and the number of initial carriers being a first number.

[0008] In some embodiments, generating multiple initial carriers in the catalytic layer grid whose Euclidean distances with each other satisfy a minimum Euclidean distance threshold condition includes: setting the number of initial carriers and a radius range; randomly selecting a set of coordinates for the first initial carrier in the catalytic layer grid, and assigning a radius within the radius range to the first initial carrier; repeating the step of generating the first initial carrier, generating other initial carriers in the catalytic layer grid, until the number of all generated initial carriers reaches the set number of initial carriers, wherein in the process of generating other initial carriers, the Euclidean distance between the newly generated initial carrier and the already generated initial carrier satisfies the minimum Euclidean distance threshold condition.

[0009] In some embodiments, the minimum Euclidean distance threshold condition is: the minimum Euclidean distance must be greater than the Euclidean distance threshold.

[0010] In some embodiments, in the catalytic layer grid, based on the initial carrier, further generating multiple diffusion carriers includes: setting the diffusion direction of the initial carrier and the diffusion number threshold for each diffusion direction; randomly generating a diffusion radius in each diffusion direction of an initial carrier, and obtaining the diffusion position coordinates corresponding to each diffusion direction based on the diffusion radius according to the size relationship between the current diffusion number and the diffusion number threshold; generating a diffusion carrier corresponding to the initial carrier on the diffusion position coordinates; and repeatedly generating diffusion carriers corresponding to other initial carriers until the sum of the number of generated diffusion carriers and the number of initial carriers is the first number.

[0011] 6. The method for generating a two-dimensional agglomerate structure model of a catalytic layer according to claim 5 is characterized in that the diffusion position coordinates corresponding to each diffusion direction are obtained based on the diffusion radius according to the size relationship between the current diffusion number and the diffusion number threshold, including: judging whether the current diffusion number is less than the diffusion number threshold; in response to the current diffusion number being not less than the diffusion number threshold, adding the diffusion radius and the radius of the initial carrier to the coordinates of the initial carrier in the diffusion direction to obtain the diffusion position coordinates; in response to the current diffusion number being less than the diffusion number threshold, randomly selecting a coordinate in the diffusion direction whose minimum distance from a generated carrier is greater than the diffusion radius as the diffusion position coordinate, wherein the generated carrier includes a generated initial carrier and a generated diffusion carrier.

[0012] In some embodiments, generating a second number or a number of available blank adjacent points of catalyst particles at the available blank adjacent points includes: determining whether the number of available blank adjacent points is greater than the second number; in response to the number of available blank adjacent points being greater than the second number, randomly selecting a second number of available blank adjacent points to generate a second number of catalyst particles; in response to the number of available blank adjacent points being not greater than the second number, generating catalyst particles at all available blank adjacent points.

[0013] In some embodiments, a third number of placeable points are obtained in the remaining area of ​​the catalytic layer grid, and generating ionomers at the placeable points includes: taking points with pixel values ​​of 0 in the catalytic layer grid as placement points to be determined, and obtaining the number of points with non-0 pixel values ​​in the connected neighborhood of the placement points to be determined; calculating the probability of a placement point to be determined being occupied by using an ion placement probability calculation formula; when the probability of the placement point to be determined being occupied is greater than or equal to an occupation probability threshold, taking the placement point to be determined as a placeable point, and generating an ionomer at the placeable point; repeatedly obtaining other placeable points to generate ionomers, until the number of generated ionomers is a third number.

[0014] In some embodiments, the ion placement probability calculation formula is: Where P is the probability that the placement point to be determined is occupied, Np is the number of points whose pixel values ​​are not 0 in the connected neighborhood of the placement point to be determined, and Nc is the set local density value.

[0015] In the second aspect, the present application provides a system for generating a two-dimensional agglomerate structure model of a catalytic layer, which uses a method for generating a two-dimensional agglomerate structure model of a catalytic layer as described in any embodiment of the first aspect to generate a two-dimensional agglomerate structure model of a catalytic layer, and the system includes: a setting module, which is used to set the area parameters of the catalytic layer grid and the volume fraction of each phase material in the catalytic layer, and obtain the target quantity corresponding to each phase material based on the volume fraction of each phase material in the catalytic layer, wherein the each phase material in the catalytic layer includes a carrier, catalyst particles and an ionomer; a first generation module, which is used to generate a first number of carriers in the catalytic layer grid, and mark the grid area where the generated carriers are located with a first marking value, wherein the first number is the target number corresponding to the carrier; and a second generation module, which is used to obtain the acquisition The available blank adjacent points of the catalyst layer grid area are marked with a first marking value, a second number or the number of available blank adjacent points of catalyst particles are generated at the available blank adjacent points, and the grid area where the catalyst particles are located is marked with the second marking value, wherein the second number is the target number corresponding to the catalyst particles; a third generating module is used to obtain a third number of placeable points in the remaining area of ​​the catalyst layer grid, generate ionomers at the placeable points, and mark the grid area where the ionomers are located with a third marking value, wherein the third number is the target number corresponding to the ionomers; a model acquiring module is used to fill the gaps of the generated ionomers, mark the connected components of the ionomers that meet the area threshold condition with the third marking value, and obtain a two-dimensional agglomerate structure model of the catalyst layer.

[0016] Through the method for generating a two-dimensional aggregate structure model of the catalytic layer as provided above, the embodiment of the present application generates a first number of carriers in the catalytic layer grid, marks the grid area where the generated carriers are located with a first marking value, generates catalyst particles at the available blank adjacent points in the catalytic layer grid area marked with the first marking value, and generates ionomeres at the placeable points in the remaining area of ​​the catalytic layer grid, which can accurately reflect the actual distribution state and dependence of each phase in the catalytic layer.

[0017] Furthermore, in some embodiments, by generating multiple initial carriers whose Euclidean distances satisfy the minimum Euclidean distance threshold condition, multiple diffusion carriers are further generated based on the initial carriers, so that the diffusion growth process of the carriers can be simulated and the overlap of carbon carrier particles can be avoided. This allows the final generated catalytic layer structure to maintain the preset porosity and ensure reasonable material distribution.

[0018] Furthermore, in some embodiments, the point with a pixel value of 0 in the catalytic layer grid is used as a placement point to be determined, and the probability of a placement point to be determined being occupied is calculated by the ion placement probability calculation formula. When the probability of the placement point to be determined being occupied is greater than or equal to the occupation probability threshold, the placement point to be determined is used as a placeable point, and an ionomer is generated at the placeable point. The placeable point can be determined based on the probability of being occupied, thereby ensuring that the ionomer is evenly distributed. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present application will become easy to understand. In the accompanying drawings, several embodiments of the present application are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0020] Figure 1 An exemplary flow chart of a method for generating a two-dimensional aggregate structure model of a catalytic layer according to an embodiment of the present application is shown;

[0021] Figure 2A-2E An exemplary flow chart of generating a vector according to an embodiment of the present application is shown;

[0022] Figure 3A-3G A schematic diagram of a generation vector according to an embodiment of the present application is shown;

[0023] Figure 4 An exemplary flow chart of generating catalyst particles according to an embodiment of the present application is shown;

[0024] Figure 5A-Figure 5B A schematic diagram of generating catalyst particles according to an embodiment of the present application is shown;

[0025] Figure 6 An exemplary flow chart of generating ionomers according to an embodiment of the present application is shown;

[0026] Figure 7 A schematic diagram of generating an ionomer according to an embodiment of the present application is shown;

[0027] Fig. 8A A schematic diagram showing a two-dimensional aggregate structure model generated in an embodiment of the present application is shown;

[0028] Figure 8B A schematic diagram of the porosity error of the catalytic layer of an embodiment of the present application is shown;

[0029] Fig. 9 An exemplary structural block diagram of a system for generating a two-dimensional aggregate structure model of a catalytic layer according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0031] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present application indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0032] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this application specification and claims, unless the context clearly indicates otherwise, the singular forms of "a", "an" and "the" are intended to include plural forms. It should also be further understood that the term "and / or" used in this application specification and claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0033] As used in this specification and claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0034] The specific implementation of the present application is described in detail below with reference to the accompanying drawings.

[0035] In the prior art, in the process of constructing the catalytic layer structure model, the quadruple structure generating set (QSGS) method is used to control the growth of carbon carriers of the same size, and only the unit cells adjacent to the carbon seeds are considered for growth, that is, the four directions of up, down, left and right. Then, Pt particles with a size of 5 nanometers are randomly distributed on the generated carbon surface. Next, the QSGS method is used to generate non-uniformly distributed ionomers on the surface of carbon / Pt particles, wherein the generation step of the ionomer is similar to the step of carbon generation.

[0036] Therefore, in the process of constructing the catalytic layer structure model in the prior art, it is assumed that the size of all carbon carriers remains consistent. However, in reality, due to the uncertainty of slurry preparation and bead mill processing, the actual carbon carrier size of the catalytic layer is unevenly distributed; at the same time, in the process of constructing the catalytic layer structure model in the prior art, the platinum particle size is set to 5nm, which makes the size of some carbon carriers close to the size of platinum particles, and does not correctly reflect the size relationship between carbon carriers and platinum particles; in addition, when the prior art generates ionomers, it directly adopts the same method as the production of carbon carriers, assuming that ionomers are randomly generated in the pore space, ignoring that ionomers are attached to carbon carriers and cannot exist independently in the pore space, which is inconsistent with the actual situation. Therefore, in the process of constructing the catalytic layer structure model in the prior art, the real distribution state and dependence of each phase cannot be reflected.

[0037] In view of this, an embodiment of the present application provides a solution for generating a two-dimensional aggregate structure model of a catalytic layer, which can accurately reflect the actual distribution state and dependence of each phase in the catalytic layer.

[0038] Figure 1 An exemplary flow chart of a method 100 for generating a two-dimensional aggregate structure model of a catalytic layer according to an embodiment of the present application is shown.

[0039] like Figure 1 As shown, in step S110, the area parameters of the catalyst layer grid and the volume fraction of each phase of material in the catalyst layer are set, and the target quantity corresponding to each phase of material is obtained based on the volume fraction of each phase of material in the catalyst layer, wherein the each phase of material in the catalyst layer includes a carrier, catalyst particles and an ionomer.

[0040] In an embodiment of the present application, the catalyst layer grid is in a rectangular shape, and the area parameters of the catalyst layer grid include length and width. The area parameters of the catalyst layer grid determine the size of the catalyst layer grid.

[0041] In some embodiments of the present application, the aforementioned carrier is a carbon carrier, and the aforementioned catalyst particles are platinum particles. In other embodiments of the present application, according to the type of fuel cell, application field, etc., the carrier in the catalyst layer may also be other types of carriers except the carbon carrier, and the catalyst particles in the catalyst layer may also be other types of catalyst particles except the platinum particles, and the present application does not limit this.

[0042] In the embodiments of the present application, the carrier volume fraction, the catalyst particle volume fraction and the ionomer volume fraction are set by the carrier volume fraction calculation formula, the catalyst particle volume fraction calculation formula and the ionomer volume fraction calculation formula respectively. Specifically, the carrier volume fraction calculation formula, the catalyst particle volume fraction calculation formula and the ionomer volume fraction calculation formula are respectively:

[0043]

[0044]

[0045]

[0046] In the above calculation formula, V C is the carrier volume fraction, V P is the volume fraction of catalyst particles, V ion is the ionomer volume fraction, ρ C is the density of the carrier, ρ P is the density of catalyst particles, ρ ion is the density of the ionomer, θ P / C is the mass ratio of catalyst to support, θ ion is the electrolyte content of the ionomer (ie, the mass ratio of the electrolyte to the electrode of the ionomer), and ε is the target porosity of the catalyst layer.

[0047] In the embodiment of the present application, based on the volume fraction of each phase of the material in the catalyst layer, the density of each phase of the material in the catalyst layer, and the thickness of the catalyst layer obtained above, the target quantity corresponding to each phase of the material is obtained by the target quantity calculation formula. Specifically, the target quantity calculation formula is: γ=Vρδ, where V is the volume fraction of a phase of the material in the catalyst layer, ρ is the density of the phase of the material, and δ is the thickness of the catalyst layer.

[0048] In the embodiment of the present application, the seed number of the random number generator may also be set so that the random number generator is used to generate the same random number sequence each time subsequently, thereby achieving reproducibility of the experimental results.

[0049] In the embodiments of the present application, the area threshold, Euclidean distance threshold, diffusion number threshold, occupancy probability threshold, etc. involved in the present application are set according to actual needs and application scenarios, and the present application does not limit the specific values.

[0050] After completing step S110, in step S120, a first number of carriers are generated in the catalyst layer grid, and the grid area where the generated carriers are located is marked with a first marking value, wherein the first number is a target number corresponding to the carriers.

[0051] In the embodiment of the present application, generating the first number of carriers in the catalyst layer grid specifically involves the process of generating initial carriers and generating diffusion carriers based on the initial carriers. Figure 2A-2E The specific process involved in step S120 is described, and combined with Figure 3A-3G The simulation construction process of the model involved in step S120 is described.

[0052] Figure 2A An exemplary flow chart for generating a first number of carriers in a catalyst layer grid according to an embodiment of the present application is shown.

[0053] like Figure 2A As shown, a first number of carriers are generated in the catalytic layer grid by executing step S210 and step S220. Specifically, in step S210, a plurality of initial carriers whose Euclidean distances satisfy the minimum Euclidean distance threshold condition are generated in the catalytic layer grid. Then, in step S220, a plurality of diffusion carriers are further generated in the catalytic layer grid based on the initial carriers, wherein the sum of the number of diffusion carriers and the number of initial carriers is the first number.

[0054] Combine the following Figure 2B The specific process involved in step S210 is described.

[0055] Figure 2B An exemplary flow chart for generating an initial carrier in a catalytic layer grid according to an embodiment of the present application is shown.

[0056] like Figure 2B As shown, by executing steps S310 to S320, a plurality of initial carriers whose Euclidean distances satisfy a minimum Euclidean distance threshold condition are generated in the catalytic layer grid.

[0057] In step S310, the number and radius range of initial carriers are set.

[0058] In an embodiment of the present application, by initializing the growth core of the carrier, the estimated number of growth cores is used as the initial carrier of the set initial carrier.

[0059] In some embodiments of the present application, the radius range of the initial carrier is 3-12. In other embodiments of the present application, the radius range of the initial carrier can also be set to other numerical ranges according to actual needs and application scenarios, and the present application does not limit this.

[0060] In step S320, a set of coordinates is randomly selected for the first initial carrier in the catalyst layer grid, and a radius is assigned to the first initial carrier within the radius range. Specifically, since the first initial carrier is only limited by the area where the catalyst layer grid is located, a set of coordinates can be randomly selected in the catalyst layer grid as its coordinates, and the coordinates of the initial carrier are the coordinates of the center of the circular area corresponding to the initial carrier.

[0061] In the embodiments of the present application, an exemplary process of randomly selecting a set of coordinates for the first initial carrier in the catalyst layer grid can be found in Figure 3A . Figure 3A FIG. 1 shows a schematic diagram of randomly selecting a set of coordinates in the catalytic layer grid according to an embodiment of the present application. Figure 3AAs shown, a coordinate point can be selected at any position in the catalyst layer grid, as long as the coordinate point is within the range of the catalyst layer grid.

[0062] In the embodiment of the present application, an exemplary process of allocating a radius within the radius range to the first initial carrier can be found in Figure 3B . Figure 3B FIG. 2 shows a schematic diagram of allocating a radius to the first initial carrier in an embodiment of the present application. Figure 3B As shown, a radius is assigned to the aforementioned selected coordinate points, and the radius is made to be in the range of 3-12, thereby obtaining the first initial carrier.

[0063] In step S330, the step of generating the first initial carrier is repeated to generate other initial carriers in the catalytic layer grid until the number of all generated initial carriers reaches the set number of initial carriers, wherein in the process of generating other initial carriers, the Euclidean distance between the newly generated initial carrier and the generated initial carrier meets the minimum Euclidean distance threshold condition.

[0064] In an embodiment of the present application, the Euclidean distance between carriers is obtained by calculating the distance between the centers of circular areas corresponding to the respective carriers.

[0065] In the embodiment of the present application, the minimum Euclidean distance threshold condition is: the minimum Euclidean distance must be greater than the Euclidean distance threshold. That is, in the process of generating other initial carriers, the minimum Euclidean distance between the newly generated initial carrier and all the generated initial carriers is greater than the Euclidean distance threshold. In other words, the Euclidean distance between the newly generated initial carrier and all the generated initial carriers is greater than the Euclidean distance threshold.

[0066] In an embodiment of the present application, the Euclidean distance between the initial carriers is obtained by using the Euclidean distance calculation formula, and the Euclidean distance calculation formula is:

[0067] Among them, x ij is the j-th dimension coordinate of the ith initial vector, x c_num.j is the j-th dimension coordinate of the c_num-th initial vector, where n is the dimension of the space.

[0068] In some embodiments of the present application, the Euclidean distance threshold is set to 20. In other embodiments of the present application, the Euclidean distance threshold may also be set to other values ​​according to actual needs and application scenarios, and the present application does not limit this.

[0069] By making the Euclidean distance between the newly generated initial carrier and the already generated initial carrier satisfy the minimum Euclidean distance threshold condition, the Euclidean distances between all initial carriers generated in the catalytic layer grid satisfy the minimum Euclidean distance threshold condition, thereby avoiding the overlap of the generated initial carriers.

[0070] Combine the following Figure 2C The specific process involved in step S330 is described.

[0071] Figure 2C An exemplary flow chart of generating other initial carriers except the first initial carrier in a catalyst layer grid according to an embodiment of the present application is shown.

[0072] like Figure 2C As shown, in step S410, it is determined whether the number of all the generated initial carriers reaches the number of the set initial carriers. When the number of all the generated initial carriers reaches the number of the set initial carriers, the process of generating the initial carriers ends. When the number of all the generated initial carriers does not reach the number of the set initial carriers, in step S420, the step of generating the first initial carrier is repeated to generate the next initial carrier. Then, in step S430, it is determined whether the Euclidean distance between the next generated initial carrier and the generated initial carrier meets the minimum Euclidean distance threshold condition.

[0073] When the Euclidean distance between the next generated initial vector and the generated initial vector does not meet the minimum Euclidean distance threshold condition, the process returns to step S420 to regenerate the next initial vector. When the Euclidean distance between the next generated initial vector and the generated initial vector meets the minimum Euclidean distance threshold condition, the process returns to step S440 to use the next initial vector as the newly generated initial vector. After executing step S440, the process returns to step S410 to loop to form initial vectors that meet the minimum Euclidean distance threshold condition until the number of all generated initial vectors reaches the set number of initial vectors.

[0074] In the embodiments of the present application, the exemplary process of generating the second initial vector can be found in Figure 3C . Figure 3C FIG. 2 shows a schematic diagram of generating a second initial vector in an embodiment of the present application. Figure 3C As shown, a coordinate point is selected in the catalytic layer grid, and a radius in the range of 3-12 is assigned to the coordinate point. Then, the Euclidean distance between the coordinate point and the center of the first initial carrier is checked. When the Euclidean distance between the coordinate point and the center of the first initial carrier is greater than the Euclidean distance threshold requirement, the second initial carrier is used as the newly generated initial carrier.

[0075] In the embodiments of the present application, the exemplary process of generating the third initial vector can be found in Figure 3D . Figure 3D FIG. 2 shows a schematic diagram of generating a third initial vector in an embodiment of the present application. Figure 3DAs shown, a coordinate point is selected in the catalytic layer grid, and a radius in the range of 3-12 is assigned to the coordinate point. Then, the Euclidean distance between the coordinate point and the center of the first initial carrier and the center of the second initial carrier is checked. When the Euclidean distance between the coordinate point and the center of the first initial carrier and the center of the second initial carrier meets the minimum Euclidean distance threshold condition, the third initial carrier is used as the newly generated initial carrier.

[0076] In the embodiments of the present application, the exemplary process of generating the n+1th initial carrier can be found in Figure 3E . Figure 3E FIG. 2 shows a schematic diagram of generating the n+1th initial carrier in an embodiment of the present application. Figure 3E As shown, a coordinate point is selected in the catalytic layer grid, and a radius in the range of 3-12 is assigned to the coordinate point. Then, the Euclidean distance between the coordinate point and the center of the circle of the first n initial carriers is checked. When the Euclidean distance between the coordinate point and the center of the circle of the first n initial carriers meets the minimum Euclidean distance threshold condition, the n+1th initial carrier is used as the newly generated initial carrier.

[0077] Through the above steps, when the Euclidean distance between the next generated initial vector and the generated initial vector meets the minimum Euclidean distance threshold condition, the next initial vector is used as the newly generated initial vector, otherwise the next initial vector is regenerated. Thus, it is ensured that the Euclidean distance between the newly generated initial vector and the generated initial vector meets the minimum Euclidean distance threshold condition.

[0078] After generating the initial vector, the following combination Figure 2D The specific process involved in the aforementioned step S220 is described.

[0079] Figure 2D An exemplary flow chart for generating a diffusion carrier according to an embodiment of the present application is shown.

[0080] like Figure 2D As shown, in step S510, the diffusion direction of the initial carrier and the diffusion number threshold of each diffusion direction are set.

[0081] In some embodiments of the present application, the number of diffusion directions of the initial carrier is 8, and the initial carrier is used as the origin of the two-dimensional coordinate system, and its diffusion direction includes the positive direction of the x-axis, the negative direction of the x-axis, the positive direction of the y-axis, the negative direction of the y-axis, the diagonal direction of the first quadrant, the diagonal direction of the second quadrant, the diagonal direction of the third quadrant, and the diagonal direction of the first quadrant. In the embodiments of the present application, the number of diffusion directions of the initial carrier can also be more than 8, and the present application does not limit it here.

[0082] In an embodiment of the present application, by setting the number of diffusion directions of the initial carrier to 8 or more than 8, compared with the prior art that only considers 4 diffusion directions, the diffusion direction of the initial carrier can be simulated more carefully, thereby improving the accuracy of simulating the diffusion growth of the carbon carrier in the grid.

[0083] In the embodiment of the present application, in step S510, a diffusion probability threshold for each diffusion direction may be set. The diffusion probability threshold for each diffusion direction may be set according to actual needs and application scenarios, and the present application does not limit this.

[0084] In step S520, a diffusion radius is randomly generated in each diffusion direction of an initial carrier, and the diffusion position coordinates corresponding to each diffusion direction are obtained based on the diffusion radius according to the magnitude relationship between the current diffusion number and the diffusion number threshold.

[0085] In the embodiments of the present application, the diffusion radius can be used to set the diffusion probability threshold of each diffusion direction according to actual needs and application scenarios, and the present application does not limit this.

[0086] In step S530, a diffusion vector corresponding to the initial vector is generated on the diffusion position coordinates.

[0087] In an embodiment of the present application, the radius range of the diffusion carrier is the same as the radius range of the initial carrier.

[0088] In step S540, it is determined whether the sum of the number of currently generated diffusion carriers and the number of initial carriers is a first number.

[0089] In response to the sum of the number of diffusion carriers currently generated and the number of initial carriers being the first number, the process of generating diffusion carriers is ended.

[0090] In response to the sum of the number of currently generated diffusion carriers and the number of initial carriers not being the first number, the process returns to step S520 to repeatedly generate diffusion carriers corresponding to other initial carriers until the sum of the number of generated diffusion carriers and the number of initial carriers is the first number.

[0091] In the embodiments of the present application, an exemplary process of generating a diffusion carrier can be found in Figure 3F . Figure 3F FIG. 2 shows a schematic diagram of generating a diffusion carrier according to an embodiment of the present application. Figure 3F As shown, the distance between the generated diffusion carrier and the initial carrier may be different according to the current diffusion times and the diffusion radius.

[0092] In an embodiment of the present application, after the process of generating a diffusion carrier is completed, when the grid area where the generated carriers including the initial carrier and the diffusion carrier are located is marked with a first marking value, the circular area corresponding to the carrier is marked with the first marking value in the grid, indicating that these area positions in the grid have been occupied by the carrier.

[0093] In some embodiments of the present application, the first mark value is 1. In other embodiments of the present application, the first mark value may also be other values, which is not limited in the present application.

[0094] In an embodiment of the present application, by generating diffusion carriers at the diffusion position coordinates corresponding to each diffusion direction, and making the sum of the number of generated diffusion carriers and the number of initial carriers a first number, the total number of generated carriers can be obtained as the target number, and the volume fraction and spatial distribution of the carriers in the catalytic layer can be accurately controlled.

[0095] In the examples of this application, all vectors generated can be found in Figure 3G . Figure 3G Schematic diagrams of all carriers of the embodiments of the present application are shown. Figure 3G As shown, the generated carriers can be evenly distributed without any carrier overlap.

[0096] Combine the following Figure 2E The specific process involved in step S520 is described.

[0097] Figure 2E An exemplary flow chart of obtaining diffusion position coordinates according to some embodiments of the present application is shown.

[0098] like Figure 2E As shown, in step S610, it is determined whether the current diffusion times is less than the diffusion times threshold.

[0099] In response to the current diffusion number being not less than the diffusion number threshold, in step S620, the diffusion position coordinates are obtained by adding the diffusion radius and the radius of the initial carrier to the coordinates of the initial carrier in the diffusion direction. That is, when the current diffusion number reaches the diffusion number threshold, the diffusion position coordinates are obtained by adding the diffusion radius and the radius of the initial carrier to the coordinates of the initial carrier in the diffusion direction.

[0100] In an embodiment of the present application, when the diffusion times reach a diffusion times threshold, the diffusion position of the carrier will be calculated based on the diffusion radius and the initial carrier radius, which helps to simulate the growth and aggregation behavior of the carrier.

[0101] In response to the current diffusion times being less than the diffusion times threshold, in step S630, a coordinate whose minimum distance from a generated carrier is greater than the diffusion radius is randomly selected in the diffusion direction as the diffusion position coordinate, wherein the generated carrier includes a generated initial carrier and a generated diffusion carrier.

[0102] In an embodiment of the present application, when the number of diffusion times does not reach a threshold, by randomly selecting coordinates that meet the minimum distance requirement in the diffusion direction as diffusion position coordinates, uniform distribution between generated carriers can be ensured, thereby avoiding overlap between carriers.

[0103] Therefore, the diffusion process of the carrier can be effectively controlled based on the relationship between the current diffusion number and the diffusion number threshold, ensuring that the distribution of the carrier in the catalyst layer is neither too concentrated nor too dispersed. This method combines determinism and randomness, which not only ensures the orderliness of the carrier distribution, but also introduces the necessary randomness to simulate the actual growth process, so that the final generated catalyst layer structure model is more in line with actual needs.

[0104] In an embodiment of the present application, in the process of randomly selecting a coordinate whose minimum distance from the generated carrier is greater than the diffusion radius as the diffusion position coordinate in the diffusion direction, the following steps are mainly involved: first, randomly selecting a position coordinate in the catalyst layer grid. Then, judging whether the randomly selected position coordinate is within the range of the catalyst layer grid. In response to the randomly selected position coordinate not being within the effective range of the catalyst layer grid, the diffusion position coordinate is no longer acquired in the diffusion direction.

[0105] In response to the randomly selected position coordinate being within the effective range of the catalytic layer grid, a random number is generated by the random number generator set by the seed number, and it is determined whether the generated random number is less than the diffusion probability threshold of the diffusion direction set above. In response to the generated random number being not less than the diffusion probability threshold of the diffusion direction set above, the diffusion position coordinate is no longer obtained in the diffusion direction.

[0106] In response to the generated random number being smaller than the aforementioned diffusion probability threshold of the diffusion direction, it is determined whether the minimum distance between the randomly selected position coordinates and all generated carriers including the diffusion carrier and the initial carrier is greater than the diffusion radius.

[0107] When the minimum distance between the randomly selected position coordinates and all generated carriers is greater than the diffusion radius, it means that the randomly selected position coordinates will not overlap with the generated carriers and can be successfully diffused, then the randomly selected position coordinates will be used as the diffusion position coordinates.

[0108] When the minimum distance between the randomly selected position coordinates and all generated carriers is not greater than the diffusion radius, it means that the randomly selected position coordinates may overlap with the generated carriers, and no diffusion position coordinates are obtained in the diffusion direction.

[0109] After the carrier is generated through step S120, in step S130, available blank adjacent points of the catalyst layer grid area marked with the first marking value are obtained, a second number or the number of available blank adjacent points of catalyst particles are generated at the available blank adjacent points, and the grid area where the catalyst particles are located is marked with the second marking value, wherein the second number is the target number corresponding to the catalyst particles.

[0110] Combine the following Figure 4 The specific process involved in step S130 is described, and combined with Figure 5A-Figure 5B The simulation construction process of the model involved in step S130 is described.

[0111] Figure 4 An exemplary flow chart for generating catalyst particles according to an embodiment of the present application is shown.

[0112] like Figure 4 As shown, in step S710, it is determined whether the number of available blank adjacent points is greater than the second number. In response to the number of available blank adjacent points being greater than the second number, in step S720, the second number of available blank adjacent points are randomly selected to generate the second number of catalyst particles. In response to the number of available blank adjacent points being not greater than the second number, in step S730, catalyst particles are generated at all available blank adjacent points.

[0113] In an embodiment of the present application, the process of obtaining available blank adjacent points is as follows: the boundary pixels whose values ​​are the first mark values ​​are identified by the bwperim function. Then the pixel values ​​in the 4-connected neighborhoods of each boundary pixel are obtained. The isinbox(neighbors,box) function is used to check whether all connected neighborhoods are within the range of the catalyst layer grid. Points with a pixel value of 0 in the connected neighborhoods within the range of the catalyst layer grid are taken as blank adjacent points, and the blank adjacent points are stored. Then, the length function is used to calculate the number of all blank adjacent points in the catalyst layer grid.

[0114] In an embodiment of the present application, when the number of blank adjacent points is greater than the second number, blank adjacent points are randomly selected to generate a second number of catalyst particles, so that the deposition process of the catalyst particles is randomly matched based on the characteristic positions of the carrier surface, thereby ensuring that the catalyst particles are evenly distributed and meet the target volume fraction requirements.

[0115] In the embodiments of the present application, an exemplary process for generating catalyst particles can be found in Figure 5A . Figure 5A Schematic diagram of generating catalyst particles according to an embodiment of the present application is shown. Figure 5A As shown, when the number of blank adjacent points in the figure is greater than the second number, blank adjacent points can be randomly selected, and catalyst particles on the surface of the carrier in the figure.

[0116] In an embodiment of the present application, when the number of available blank adjacent points is not greater than the second number, catalyst particles are generated at all available blank adjacent points, which may make the actual catalyst particle volume fraction different from its target volume fraction. Therefore, after the catalyst particles are generated at all available blank adjacent points, the actual catalyst particle volume fraction is calculated, and a warning message is issued to prompt the user to cover the entire surface of the carrier, which may affect the performance or structural integrity, so that the user can adjust the model as needed.

[0117] In the embodiment of the present application, in the process of generating catalyst particles at the blank adjacent points, constraints between the size relationship between the catalyst particles and the carrier are imposed according to the size relationship between the catalyst particles and the carrier, so as to realize free control of the size of the catalyst particles. Thus, the catalyst particles and the carrier always maintain the correct ratio.

[0118] In the examples of the present application, the generated catalyst particles can be found in Figure 5B . Figure 5B Schematic diagram of the catalyst particles generated in the embodiment of the present application is shown. Figure 5B As shown, the size between the generated catalyst particles and the carrier is consistent with the actual situation.

[0119] In the embodiment of the present application, after the catalyst particles are generated, when the grid regions where the generated catalyst particles are located are marked with the second marking value, it indicates that these regional positions in the grid have been occupied by the catalyst particles.

[0120] In some embodiments of the present application, the second mark value is 2. In other embodiments of the present application, the second mark value may also be other values ​​different from the first mark value, and the present application does not limit this.

[0121] After catalyst particles are generated through step S130, in step S140, a third number of placeable points are obtained in the remaining area in the catalyst layer grid, ionomers are generated at the placeable points, and the grid area where the ionomers are located is marked with a third marking value, where the third number is the target number corresponding to the ionomers.

[0122] Combine the following Figure 6 The specific process involved in step S140 is described, and combined with Figure 7 The simulation construction process of the model involved in step S130 is described.

[0123] Figure 6 An exemplary flow chart for producing ionomers according to an embodiment of the present application is shown.

[0124] like Figure 6 As shown, in step S810, the points with pixel values ​​of 0 in the catalyst layer grid are taken as the placement points to be determined, and the number of points with non-0 pixel values ​​in the connected neighborhood of the placement points to be determined is obtained.

[0125] In an embodiment of the present application, the points with pixel values ​​of 0 in the catalyst layer grid are points not occupied by carriers and catalyst particles. The points in the catalyst layer grid not occupied by carriers and catalyst particles may be occupied by ionomers, so these points are used as placement points to be determined.

[0126] In an embodiment of the present application, the number of points whose pixel values ​​are not 0 in the 8-connected neighborhood of the point to be placed is obtained.

[0127] In step S820, the probability of a placement point to be determined being occupied is calculated using the ion placement probability calculation formula.

[0128] In an embodiment of the present application, the ion placement probability calculation formula is: Where P is the probability that the placement point to be determined is occupied, Np is the number of points whose pixel values ​​are not 0 in the connected neighborhood of the placement point to be determined, and Nc is the set local density value.

[0129] The local density value is used to control the local environment for ion placement. By determining the ion placement probability based on the local density value and the number of points with non-zero pixel values ​​in the connected neighborhood of the placement point to be determined, fine control of the ionomer distribution can be achieved.

[0130] In step S830, when the probability that the placement point to be determined is occupied is greater than or equal to the occupation probability threshold, the placement point to be determined is regarded as a placeable point, and an ionomer is generated at the placeable point.

[0131] In the embodiment of the present application, the occupation probability threshold is a random number generated by the aforementioned random number generator set with a seed number. The random number generated by the random number generator is used to determine whether to generate an ionomer at a certain position, which can simulate the random formation process of the ionomer, ensure the rationality and accuracy of the ionomer distribution, increase the realism and complexity of the final two-dimensional agglomerate structure model of the catalytic layer, and make the simulation results closer to the actual situation. Although the random number generated by the random number generator introduces randomness, the relationship between the probability of being occupied and the occupation probability threshold can avoid completely random disordered distribution, ensuring that the generated ionomer has a certain regularity.

[0132] In the embodiments of the present application, an exemplary process for generating ionomers can be found in Figure 7 . Figure 7 Schematic diagram of generating ionomer according to an embodiment of the present application is shown. Figure 7 As shown, there are multiple placement points to be determined. Only when the probability of the placement point to be determined being occupied is greater than or equal to the occupation probability threshold, the placement point to be determined is regarded as a placeable point, and an ionomer is generated at the placeable point.

[0133] In step S840 , it is determined whether the amount of the generated ionomer is a third amount.

[0134] In response to the number of generated ionomers not being the third number, the process returns to step S820 to repeatedly acquire other placeable points to generate ionomers until the number of generated ionomers is the third number.

[0135] In response to the amount of the generated ionomer being the third amount, the process of generating the ionomer is ended.

[0136] In the embodiment of the present application, after the ionomer is generated, when the grid regions where the generated ionomer is located are marked with a third marking value, it indicates that these regional positions in the grid have been occupied by the ionomer.

[0137] In some embodiments of the present application, the third mark value is 3. In other embodiments of the present application, the third mark value may also be other values ​​different from the first mark value and the second mark value, and the present application does not limit this.

[0138] After the ionomer is generated in step S140, in step S150, the gaps of the generated ionomer are filled, and the connected components of the ionomer that meet the area threshold condition are marked with a third marking value to obtain a two-dimensional aggregate structure model of the catalyst layer.

[0139] Combine the following Fig. 8A The simulation construction process of the model involved in step S150 is described.

[0140] In the embodiment of the present application, the voids of the generated ionomer are filled by the imfill function.

[0141] In an embodiment of the present application, the area threshold condition is that the area of ​​the ionomer connected component is less than the area threshold. In some embodiments of the present application, the area threshold is set to 50. In other embodiments of the present application, the area threshold may also be set to other values, which are not limited in the present application.

[0142] By marking the ionomer connected components whose areas are smaller than the area threshold with the same marking value as the ionomer, it can be ensured that the connected components finally adopted are within a certain area range and the ionomer can be made more complete and continuous.

[0143] In the examples of the present application, the generated two-dimensional aggregate structure model of the catalyst layer can be found in Fig. 8A . Fig. 8A Schematic diagram of the two-dimensional aggregate structure model of the catalyst layer of the embodiment of the present application is shown. Fig. 8A As shown, the two-dimensional agglomerate structure model of the catalytic layer is composed of carriers, catalyst particles and ionomers, which can accurately reflect the actual distribution state and dependence of each phase in the catalytic layer.

[0144] In an embodiment of the present application, after the two-dimensional aggregate structure model of the catalyst layer is obtained, the time required for the two-dimensional aggregate structure model of the catalyst layer to run can be output, and the porosity of the catalyst layer can be calculated.

[0145] In the embodiment of the present application, a corresponding mathematical model is constructed based on the set seed number of the random number generator and the target porosity characteristics of the catalytic layer, and the actual porosity value of the catalytic layer is generated using a script parameterized modeling method. Specifically, the script parameterized modeling is a modeling method based on a MATLAB script.

[0146] In the embodiments of the present application, Figure 8B Get the error between the actual porosity and the target porosity. Figure 8B As shown in FIG8 , the error between the actual porosity of the catalyst layer and the target porosity is maintained at -3×10 -3 ~3×10 -3 This indicates that the two-dimensional aggregate structure model of the catalytic layer obtained in this application can accurately control the porosity.

[0147] In summary, through the scheme for generating the two-dimensional agglomerate structure model of the catalytic layer as provided above, the embodiment of the present application generates a first number of carriers in the catalytic layer grid, marks the grid area where the generated carriers are located with a first marking value, generates catalyst particles at the available blank adjacent points in the catalytic layer grid area marked with the first marking value, and generates ionomeres at the placeable points in the remaining area of ​​the catalytic layer grid, which can accurately reflect the actual distribution state and dependence of each phase in the catalytic layer.

[0148] Furthermore, in some embodiments, by generating multiple initial carriers whose Euclidean distances satisfy the minimum Euclidean distance threshold condition, multiple diffusion carriers are further generated based on the initial carriers, so that the diffusion growth process of the carriers can be simulated and the overlap of carbon carrier particles can be avoided. This allows the final generated catalytic layer structure to maintain the preset porosity and ensure reasonable material distribution.

[0149] Furthermore, in some embodiments, the point with a pixel value of 0 in the catalytic layer grid is used as a placement point to be determined, and the probability of a placement point to be determined being occupied is calculated by the ion placement probability calculation formula. When the probability of the placement point to be determined being occupied is greater than or equal to the occupation probability threshold, the placement point to be determined is used as a placeable point, and an ionomer is generated at the placeable point. The placeable point can be determined based on the probability of being occupied, thereby ensuring that the ionomer is evenly distributed.

[0150] The embodiment of the present application also provides a catalyst layer two-dimensional agglomerate structure model generation system, which can use the aforementioned catalyst layer two-dimensional agglomerate structure model generation method 100 to control the generation of the two-dimensional agglomerate structure model, and can also use other catalyst layer two-dimensional agglomerate structure model generation methods to control the generation of the two-dimensional agglomerate structure model.

[0151] Fig. 9 An exemplary structural block diagram of a system 900 for generating a two-dimensional aggregate structure model of a catalytic layer according to an embodiment of the present application is shown.

[0152] like Fig. 9 As shown, the system 900 includes a setting module 910, a first generation module 920, a second generation module 930, a third generation module 940, and a model acquisition module 950. In an embodiment of the present application, the setting module 910, the first generation module 920, the second generation module 930, the third generation module 940, and the model acquisition module 950 may be separate units or may be integrated in the same controller.

[0153] Specifically, the setting module 910 is used to set the area parameters of the catalyst layer grid and the volume fraction of each phase of material in the catalyst layer, and obtain the target quantity corresponding to each phase of material based on the volume fraction of each phase of material in the catalyst layer, wherein the each phase of material in the catalyst layer includes a carrier, catalyst particles and an ionomer.

[0154] Specifically, the first generation module 920 is used to generate a first number of carriers in the catalytic layer grid, and mark the grid area where the generated carriers are located with a first marking value, wherein the first number is a target number corresponding to the carriers.

[0155] Specifically, the second generation module 930 is used to obtain available blank adjacent points of the catalyst layer grid area marked with a first marking value, and generate a second number or a number of available blank adjacent points of catalyst particles at the available blank adjacent points, wherein the second number is a target number corresponding to the catalyst particles.

[0156] Specifically, the third generation module 940 is used to obtain a third number of placeable points in the remaining area of ​​the catalyst layer grid, generate ionomers at the placeable points, and mark the grid area where the ionomer is located with a third marking value, wherein the third number is a target number corresponding to the ionomer;

[0157] The model acquisition module 950 is used to fill the gaps of the generated ionomers, mark the connected components of the ionomers that meet the area threshold condition with a third marking value, and obtain a two-dimensional aggregate structure model of the catalyst layer.

[0158] When the system 900 uses the above-mentioned catalyst layer two-dimensional agglomerate structure model generation method 100 to generate a catalyst layer two-dimensional agglomerate structure model, the setting module 910 performs the above-mentioned step S110, the first generation module 920 performs the above-mentioned step S120, the second generation module 930 performs the above-mentioned step S130, the third generation module 940 performs the above-mentioned step S140, and the model acquisition module 950 performs the above-mentioned step S150. The specific execution process can be referred to the above text and will not be repeated here.

[0159] Although multiple embodiments of the present application have been shown and described herein, it is obvious to those skilled in the art that such embodiments are provided only by way of example. Those skilled in the art can think of many changes, modifications and alternatives without departing from the thought and spirit of the present application. It should be understood that in the process of practicing the present application, various alternatives to the embodiments of the present application described herein can be adopted. The attached claims are intended to limit the scope of protection of the present application, and therefore cover equivalents or alternatives within the scope of these claims.

Claims

1. A method for generating a two-dimensional aggregate structure model of a catalyst layer, characterized in that: include: Setting the area parameters of the catalyst layer grid and the volume fraction of each phase of the catalyst layer, and obtaining the target quantity corresponding to each phase of the catalyst based on the volume fraction of each phase of the catalyst layer, wherein each phase of the catalyst layer includes a carrier, catalyst particles and an ionomer; Generating a first number of carriers in the catalytic layer grid, and marking the grid area where the generated carriers are located with a first marking value, wherein the first number is a target number corresponding to the carriers; Obtaining available blank adjacent points of the catalyst layer grid area marked with a first marking value, generating a second number of catalyst particles or the number of available blank adjacent points at the available blank adjacent points, and marking the grid area where the catalyst particles are located with the second marking value, wherein the second number is a target number corresponding to the catalyst particles; Obtaining a third number of placeable points in the remaining area of ​​the catalyst layer grid, generating ionomers at the placeable points, and marking the grid area where the ionomer is located with a third marking value, wherein the third number is a target number corresponding to the ionomer; The gaps of the generated ionomers are filled, and the connected components of the ionomers that meet the area threshold condition are marked with a third marking value to obtain a two-dimensional aggregate structure model of the catalytic layer.

2. The method for generating a two-dimensional aggregate structure model of a catalyst layer according to claim 1, characterized in that: Generating a first number of carriers in the catalyst layer grid includes: Generating a plurality of initial carriers in the catalytic layer grid, the Euclidean distances between the carriers satisfying a minimum Euclidean distance threshold condition; In the catalytic layer grid, a plurality of diffusion carriers are further generated based on the initial carriers, and the sum of the number of the diffusion carriers and the number of the initial carriers is a first number.

3. The method for generating a two-dimensional aggregate structure model of a catalyst layer according to claim 2, characterized in that: Generating a plurality of initial carriers in the catalytic layer grid whose Euclidean distances satisfy a minimum Euclidean distance threshold condition comprises: Set the number and radius of initial carriers; randomly selecting a set of coordinates for a first initial carrier in the catalyst layer grid, and assigning a radius within a radius range to the first initial carrier; Repeat the step of generating the first initial carrier, and generate other initial carriers in the catalytic layer grid until the number of all generated initial carriers reaches the set number of initial carriers, wherein in the process of generating other initial carriers, the Euclidean distance between the newly generated initial carrier and the generated initial carrier meets the minimum Euclidean distance threshold condition.

4. The method for generating a two-dimensional aggregate structure model of a catalyst layer according to claim 3, characterized in that: The minimum Euclidean distance threshold condition is: the minimum Euclidean distance must be greater than the Euclidean distance threshold.

5. The method for generating a two-dimensional aggregate structure model of a catalyst layer according to claim 2, characterized in that: In the catalytic layer grid, based on the initial carrier, further generating multiple diffusion carriers includes: Set the diffusion direction of the initial carrier and the diffusion number threshold for each diffusion direction; A diffusion radius is randomly generated in each diffusion direction of an initial carrier, and the diffusion position coordinates corresponding to each diffusion direction are obtained based on the diffusion radius according to the magnitude relationship between the current diffusion number and the diffusion number threshold; generating a diffusion vector corresponding to the initial vector at the diffusion position coordinates; Repeat the generation of diffusion carriers corresponding to other initial carriers until the sum of the number of generated diffusion carriers and the number of initial carriers reaches the first number.

6. The method for generating a two-dimensional aggregate structure model of a catalyst layer according to claim 5, characterized in that: According to the relationship between the current diffusion times and the diffusion times threshold, the diffusion position coordinates corresponding to each diffusion direction are obtained based on the diffusion radius, including: Determine whether the current diffusion times are less than the diffusion times threshold; In response to the current diffusion number being not less than the diffusion number threshold, adding the diffusion radius and the radius of the initial carrier to the coordinates of the initial carrier in the diffusion direction to obtain the diffusion position coordinates; In response to the current diffusion times being less than the diffusion times threshold, a coordinate whose minimum distance from a generated carrier is greater than the diffusion radius is randomly selected in the diffusion direction as the diffusion position coordinate, wherein the generated carrier includes a generated initial carrier and a generated diffusion carrier.

7. The method for generating a two-dimensional aggregate structure model of a catalyst layer according to claim 1, characterized in that: Generating a second number or a number of available blank adjacent points of catalyst particles at the available blank adjacent points includes: Determine whether the number of available blank adjacent points is greater than the second number; In response to the number of available blank adjacent points being greater than a second number, randomly selecting a second number of available blank adjacent points to generate a second number of catalyst particles; In response to the number of available blank adjacent points being no greater than a second number, catalyst particles are generated at all available blank adjacent points.

8. The method for generating a two-dimensional aggregate structure model of a catalyst layer according to claim 1, characterized in that: Acquiring a third number of placeable points in the remaining area of ​​the catalyst layer grid, wherein generating ionomers at the placeable points comprises: Taking a point with a pixel value of 0 in the catalyst layer grid as a placement point to be determined, and obtaining the number of points with a pixel value not being 0 in a connected neighborhood of the placement point to be determined; The probability of a placement point to be determined being occupied is calculated by using the ion placement probability calculation formula; When the probability that the placement point to be determined is occupied is greater than or equal to the occupation probability threshold, the placement point to be determined is regarded as a placeable point, and an ionomer is generated at the placeable point; The other placeable points are repeatedly acquired to generate ionomers until the number of generated ionomers reaches a third number.

9. The method for generating a two-dimensional aggregate structure model of a catalyst layer according to claim 8, characterized in that: The ion placement probability calculation formula is: Where P is the probability that the placement point to be determined is occupied, Np is the number of points whose pixel values ​​are not 0 in the connected neighborhood of the placement point to be determined, and Nc is the set local density value.

10. A system for generating a two-dimensional aggregate structure model of a catalytic layer, characterized in that: The method for generating a two-dimensional aggregate structure model of a catalyst layer according to any one of claims 1 to 9 is used to generate a two-dimensional aggregate structure model of a catalyst layer, wherein the system comprises: A setting module, used to set the area parameters of the catalyst layer grid and the volume fraction of each phase of the catalyst layer, and obtain the target quantity corresponding to each phase of the catalyst based on the volume fraction of each phase of the catalyst layer, wherein each phase of the catalyst layer includes a carrier, catalyst particles and ionomer; A first generating module is used to generate a first number of carriers in the catalytic layer grid, and mark the grid area where the generated carriers are located with a first marking value, wherein the first number is a target number corresponding to the carriers; A second generation module is used to obtain available blank adjacent points of the catalyst layer grid area marked with the first marking value, generate a second number of catalyst particles or the number of available blank adjacent points at the available blank adjacent points, and mark the grid area where the catalyst particles are located with the second marking value, wherein the second number is a target number corresponding to the catalyst particles; A third generation module is used to obtain a third number of placeable points in the remaining area of ​​the catalyst layer grid, generate ionomers at the placeable points, and mark the grid area where the ionomer is located with a third marking value, wherein the third number is a target number corresponding to the ionomer; The model acquisition module is used to fill the gaps of the generated ionomers, mark the connected components of the ionomers that meet the area threshold condition with a third marking value, and obtain a two-dimensional agglomerate structure model of the catalytic layer.

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