Information processing method, information processing system, and program

Abstract

This information processing method involves: obtaining first porous physical property information which expresses the physical properties of a first porous structure itself which comprises a plurality of particles; obtaining first material physical property information which pertains to the material physical properties of the first porous structure and includes (a) information expressing a physical property or a substance name of a plurality of particles, and / or (b) information expressing a physical property or a substance name of a substance filling a gap between the plurality of particles; obtaining first particle information pertaining to the structure and / or positional relationship of the plurality of particles; generating structure information expressing a structure of a second porous structure in which the structure and / or positional relationship of the plurality of particles of the first porous structure has been taken into consideration, by using the first porous physical property information, the first material physical property information, and the first particle information; and outputting the structure information.

Description

Information processing method, information processing system, and program

[0001] The present disclosure relates to a technique for predicting structural information of a porous structure.

[0002] Porous structures are used as electrode materials in electrochemical devices. The performance of electrochemical devices is highly dependent on the properties of the porous structure. The properties of the porous structure directly affect the overall performance of the electrochemical device, such as the ion transport efficiency and the increase in reaction area.

[0003] Patent Document 1 discloses a technique for searching a database based on the physical properties of an input three-dimensional structure, and extracting a three-dimensional structure that matches the input physical properties.

[0004] US Patent No. 2022 / 0366096

[0005] However, in Patent Document 1, only physical properties are considered, and particle information regarding the structure and positional relationship of particles that constitute the three-dimensional structure is not considered. Therefore, Patent Document 1 may extract a three-dimensional structure that is difficult to actually manufacture.

[0006] The present disclosure provides techniques for generating structural information about porous structures that can actually be manufactured.

[0007] An information processing method in one aspect of the present disclosure is an information processing method executed by a computer, and includes: acquiring first porous property information indicating the physical properties of a first porous structure itself composed of a plurality of particles; acquiring first material property information regarding the material properties of the first porous structure, the first material property information including at least one of (a) information indicating the physical properties or substance name of the plurality of particles and (b) information indicating the physical properties or substance name of the substance filling the voids between the plurality of particles; acquiring first particle information regarding at least one of the structure and positional relationship of the plurality of particles; using the first porous property information, the first material property information, and the first particle information, generating structural information indicating the structure of a second porous structure in which at least one of the structure and positional relationship of the plurality of particles relative to the first porous structure is taken into consideration; and outputting the structural information.

[0008] According to the present disclosure, structural information of a porous structure that can actually be manufactured can be generated.

[0009] 1 is a block diagram showing an overall configuration of a structural information providing system according to a first embodiment of the present disclosure; FIG. 2 is a diagram showing an example of a first image displayed on a display unit; FIG. 3 is a diagram showing an example of a second image displayed on a display unit; FIG. 4 is a diagram showing an example of a third image displayed on a display unit; FIG. 5 is a flowchart showing an example of processing of the structural information providing system according to an embodiment; FIG. 6 is a sequence diagram showing an example of processing of the structural information providing system according to an embodiment; FIG. 7 is a diagram showing how structural information is generated by particle layer stacking; FIG. 8 is a diagram showing how structural information is generated by particle layer stacking; FIG. 9 is a diagram showing how structural information is generated by particle layer stacking; FIG. 10 is a diagram showing how second particle information is calculated; FIG. 11 is a diagram showing how second particle information is calculated; FIG. 12 is a diagram showing how second particle information is calculated.

[0010] (Findings underlying the present disclosure) A porous structure is an aggregate of partial structures having at least one type of material property. Porous structures play an important role as electrode materials for electrochemical devices such as capacitors. In particular, porous structures used as electrode materials are required to have properties such as ion transport efficiency and increased reaction area. These properties are highly dependent on particle information such as the porosity, pore size, pore distribution, and pore shape of the porous structure. Therefore, in order to obtain a porous structure that achieves the desired porous properties, it is necessary to take into account particle information.

[0011] The conventional technology disclosed in Patent Document 1 only takes into consideration porous information indicating porous properties and material property information indicating material properties of the porous structure, but does not take into consideration particle information. Therefore, the conventional technology may generate structural information of a porous structure that is difficult to actually manufacture.

[0012] The present inventors have discovered that structural information of a porous structure that can actually be manufactured can be generated by using particle information in addition to porous property information and material property information, and have arrived at the present disclosure. In other words, according to the present disclosure, structural information of a manufacturable device can be generated without generating structural information of a device that is difficult to manufacture, thereby conserving computing resources.

[0013] (1) An information processing method according to one aspect of the present disclosure is an information processing method executed by a computer, and includes the steps of: acquiring first porous property information indicating the physical properties of a first porous structure itself, which is composed of a plurality of particles; acquiring first material property information regarding the material properties of the first porous structure, the first material property information including at least one of (a) information indicating the physical properties or substance name of the plurality of particles and (b) information indicating the physical properties or substance name of the substance filling the voids between the plurality of particles; acquiring first particle information regarding at least one of the structure and positional relationship of the plurality of particles; using the first porous property information, the first material property information, and the first particle information, generating structural information indicating the structure of a second porous structure in which at least one of the structure and positional relationship of the plurality of particles relative to the first porous structure is taken into consideration; and outputting the structural information.

[0014] According to this configuration, structural information of the second porous structure is generated using the first particle information in addition to the first porous property information and the first material property information. Therefore, structural information of a porous structure that can actually be manufactured can be generated. As a result, it is possible to improve the performance of electrochemical devices while also designing porous structures that can be realized in actual manufacturing processes. This is expected to significantly reduce the time and cost required for commercializing devices and promote technological innovation in the field of electrochemical devices. Furthermore, according to this configuration, more specific first material property information is input, allowing for the generation of more feasible structural information.

[0015] (2) In the information processing method described in (1) above, the method may further include calculating second porous property information indicating the properties of the second porous structure itself using the structural information and the first material property information, and determining whether the second porous property information satisfies the property conditions defined by the first porous property information, and the outputting may include outputting the structural information of the second porous structure that is determined to satisfy the property conditions.

[0016] In this case, the structural information of the second porous structure that satisfies the physical property conditions defined by the first porous property information is output, so that more feasible structural information can be generated.

[0017] (3) In the information processing method described in (1) or (2) above, the method may further include: using the structural information to calculate second particle information relating to at least one of the structure and positional relationship of the multiple particles that constitute the second porous structure; and determining whether the second particle information satisfies the particle conditions defined by the first particle information, and the outputting may include outputting the structural information of the second porous structure that is determined to satisfy the particle conditions.

[0018] In this case, the structural information of the second porous structure that satisfies the particle conditions defined by the first particle information is generated, so that more feasible structural information can be generated.

[0019] (4) In the information processing method described in any one of (1) to (3) above, generating the structural information includes inputting the first porous property information, the first material property information, and the first particle information into a structure predictor, thereby obtaining the structural information output from the structure predictor, and the structure predictor may be trained to receive as input porous property information indicating the properties of the porous structure, material property information regarding the material properties of the porous structure, and particle information regarding at least one of the structure and positional relationship of a plurality of particles constituting the porous structure, and to output structural information indicating the structure of the porous structure.

[0020] In this case, the structural information of the second porous structure is generated using a structure predictor that has been trained in advance, so that more feasible structural information can be generated.

[0021] (5) In the information processing method described in (2) above, if it is determined that the physical property conditions are not satisfied, the information processing method may further include changing the generation parameters used when generating the structural information and regenerating the structural information.

[0022] In this case, multiple pieces of structural information are generated while changing the generation parameters, so that more feasible structural information can be obtained.

[0023] (6) In the information processing method described in (3) above, if it is determined that the particle condition is not satisfied, the information processing method may further include changing a generation parameter used when generating the structural information and regenerating the structural information.

[0024] In this case, multiple pieces of structural information are generated while changing the generation parameters, so that more feasible structural information can be obtained.

[0025] (7) In the information processing method described in any one of (1) to (6) above, generating the structural information may include generating multiple pieces of structural information by changing generation parameters, and may further include calculating, for each of the multiple pieces of structural information, a degree of fulfillment of at least one of the physical property conditions defined by the first porous physical property information and the particle conditions defined by the first particle information, and outputting the multiple pieces of structural information in a display order according to the calculated degree of fulfillment.

[0026] In this case, the plurality of pieces of structural information are output in a display order according to the degree of fulfillment of at least one of the physical property conditions and the particle conditions, so that the structural information with a high degree of fulfillment can be easily grasped.

[0027] (8) An information processing system in another aspect of the present disclosure is an information processing system including a processor, wherein the processor executes the following: acquiring first porous property information indicating the physical properties of a first porous structure itself composed of a plurality of particles; acquiring first material property information regarding the material properties of the first porous structure, including at least one of (a) information indicating the physical properties or substance name of the plurality of particles and (b) information indicating the physical properties or substance name of the substance filling the voids between the plurality of particles; acquiring first particle information regarding at least one of the structure and positional relationship of the plurality of particles; using the first porous property information, the first material property information, and the first particle information, generating structural information indicating the structure of a second porous structure in which at least one of the structure and positional relationship of the plurality of particles relative to the first porous structure is taken into consideration; and outputting the structural information.

[0028] In this case, an information processing system capable of generating more feasible structural information is provided.

[0029] (9) In yet another aspect of the present disclosure, the program causes a computer to execute the following steps: acquire first porous property information indicating the physical properties of a first porous structure itself composed of a plurality of particles; acquire first material property information regarding the material properties of the first porous structure, the first material property information including at least one of (a) information indicating the physical properties or substance name of the plurality of particles and (b) information indicating the physical properties or substance name of the substance filling the voids between the plurality of particles; acquire first particle information regarding at least one of the structure and positional relationship of the plurality of particles; use the first porous property information, the first material property information, and the first particle information to generate structural information indicating the structure of a second porous structure in which at least one of the structure and positional relationship of the plurality of particles relative to the first porous structure is taken into consideration; and output the structural information.

[0030] In this case, a program capable of generating more feasible structural information is provided.

[0031] (10) In yet another aspect of the present disclosure, the information providing system includes a display control unit that displays, on a display unit, a first image that accepts input information including first porous property information indicating the properties of a first porous structure formed by a plurality of particles, first material property information regarding the material properties of the first porous structure, and first particle information regarding at least one of the structure and positional relationship of the plurality of particles, and then causes the display unit to display, based on the input information, a second image that indicates structural information indicating the structure of a second porous structure formed by the plurality of particles.

[0032] In this case, when the first porous property information, the first material property information, and the first particle information are input, a user interface is realized that displays structural information of the second porous structure.

[0033] It goes without saying that the present disclosure allows such computer programs to be distributed on computer-readable non-transitory recording media such as CD-ROMs or via communications networks such as the Internet.

[0034] Note that each of the embodiments described below represents a specific example of the present disclosure. The numerical values, shapes, components, steps, and step orders shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components that are not described in the independent claims that represent the highest concept are described as optional components. Furthermore, in all of the embodiments, the respective contents can be combined.

[0035] 1 is a block diagram showing the overall configuration of a structural information providing system 100 according to a first embodiment of the present disclosure. The structural information providing system 100 includes an information processing system 1, an input unit 2, an information providing system 3, and a structural predictor 4. The information processing system 1 is configured by a computer such as a personal computer or a server. The information processing system 1 may be realized by a cloud server, for example. In the first embodiment, the information processing system 1 will be described as being a stationary computer.

[0036] The information processing system 1 includes a processor 10 and a memory 11. The processor 10 is, for example, a central processing unit (CPU). The processor 10 includes an acquisition unit 101, a generation unit 102, and an output unit 103. The acquisition unit 101 to the output unit 103 are realized by the CPU executing a program. The acquisition unit 101 to the output unit 103 may be configured as dedicated hardware circuits.

[0037] The information processing system 1 is connected to an input unit 2, an information provision system 3, and a structure predictor 4. The input unit 2 and the information provision system 3 are configured by an information terminal used by a user, such as a smartphone, a tablet terminal, or a personal computer. The input unit 2 and the information provision system 3 may be configured by different computers. The structure predictor 4 may be configured by an external server or may be provided in the processor 10. When the structure predictor 4 is configured by an external server, the information processing system 1 and the structure predictor 4 are connected via a network such as the Internet.

[0038] The information processing system 1, the input unit 2, and the information providing system 3 may be connected to each other so as to be able to communicate with each other via a local area network (LAN). If the information processing system 1 is configured as a server, the information processing system 1, the input unit 2, and the information providing system 3 may be connected to each other so as to be able to communicate with each other via a wide area network (WAN) such as the Internet.

[0039] The input unit 2 is an input interface that accepts user input. The input unit 2 is composed of, for example, a keyboard, a touch sensor, a touchpad, and a mouse. The input unit 2 accepts input operations by the user and outputs a signal corresponding to the input operation to the information processing system 1. In the present embodiment, the information providing system 3 and the input unit 2 are configured independently of each other, but they may be configured integrally, such as a touch panel. In addition, in the present disclosure, the information processing system 1 does not include the information providing system 3 and the input unit 2, but may include these.

[0040] The input unit 2 accepts input operations for first porous property information, first material property information, and first particle information. The first porous property information is information indicating the properties of the first porous structure itself (hereinafter referred to as "porous properties"). The first porous structure is a porous structure that is a design target and is composed of multiple particles. Particles are substances that serve as building blocks of the porous structure. The porous structure is a three-dimensional structure in which substructures are stacked or a three-dimensional structure in which substructures are filled. The substructures are structures that have at least one type of material property. The substructures may be granular, plate-like, or fibrous. Examples of porous structures include components of energy devices such as secondary batteries and fuel cells, polycrystalline ceramic sintered bodies, and fiber composites. An example of an energy device is a capacitor. An example of a component of an energy device is a capacitor electrode. An example of particles in a component of an energy device is carbon particles. An example of particles in a polycrystalline ceramic sintered body is single-crystal ceramics. An example of particles in a fiber composite is fiber.

[0041] For example, the porous properties are properties of a porous structure composed of particles and voids, and include electronic properties such as effective ionic conductivity or effective electrical conductivity, transport properties such as effective transmittance, thermal properties such as effective thermal conductivity, optical properties such as effective light absorptance or effective light reflectance, mechanical properties such as effective Young's modulus, and dielectric properties such as effective dielectric constant.

[0042] The first material property information is information about the properties of the material constituting the first porous structure (hereinafter referred to as "material properties"). The material properties include the properties of the particles constituting the porous structure and the properties of the material (an example of a substance) filling the voids of the particles. The material filling the voids of the particles includes a liquid or a gas.

[0043] For example, the material properties include electronic properties such as ionic conductivity or electrical conductivity, transport properties such as transmittance, thermal properties such as thermal conductivity, optical properties such as optical absorptivity or optical reflectance, mechanical properties such as Young's modulus, and dielectric properties such as dielectric constant. These material properties may be defined for each of the particles and the material filling the voids. Note that the input unit 2 may accept an input operation for the compound name (an example of a substance name) of the particles constituting the first porous structure or the material filling the voids, instead of or in addition to the material properties. In this case, the first material property information includes the compound name.

[0044] The first particle information is particle information of the first porous structure. The particle information is information regarding at least one of the structure and positional relationship of the plurality of particles constituting the porous structure. That is, the particle information is information indicating the geometric characteristics of the plurality of particles. For example, the particle information includes particle size, particle size distribution, particle shape, surface area, porosity, pore size, and pore size distribution.

[0045] The information providing system 3 includes a display control unit 31 and a display unit 32. The display control unit 31 is configured by, for example, a processor, and generates a second image 300 ( FIG. 3 ) and a third image 400 ( FIG. 4 ) based on the structural information output from the output unit 103, and displays the generated second image 300 and third image 400 on the display unit 32.

[0046] The display control unit 31 causes the display unit 32 to display a first image 200 (Figure 2) for accepting input information including first porous property information indicating the properties of the first porous structure, first material property information, and first particle information.

[0047] The display unit 32 displays a second image 300 and a third image 400 that show the structural information of the second porous structure generated based on the input information.

[0048] The display unit 32 displays various images under the control of the display control unit 31. The display unit 32 is, for example, a liquid crystal display, a plasma display, an organic EL (Electro-Luminescence) display, or the like, but is not limited to these.

[0049] The acquisition unit 101 acquires the first porous property information, first material property information, and first particle information received by the input unit 2 from the input unit 2. When a compound name is input as the first material property information, the acquisition unit 101 acquires material property information corresponding to the compound name from the first storage unit 111.

[0050] The generation unit 102 generates structural information of a second porous structure in which at least one of the structure and positional relationship of a plurality of particles relative to the first porous structure is taken into consideration, using the first porous property information, first material property information, and first particle information acquired by the acquisition unit 101. The generation unit 102 inputs the first porous property information, first material property information, and first particle information to the structure predictor 4, and generates the structural information output from the structure predictor 4 as structural information of the second porous structure. The second porous structure is a porous structure generated by the generation unit 102. In other words, the second porous structure is a three-dimensional model of a porous structure generated by a computer.

[0051] The output unit 103 outputs the structural information generated by the generation unit 102 to the display control unit 31 , thereby displaying the first image 200 to the third image 400 on the display unit 32 .

[0052] The structure predictor 4 is trained to receive as input porous property information indicating the properties of the porous structure, material property information relating to the material properties of the porous structure, and particle information relating to at least one of the structure and positional relationship of the multiple particles that make up the porous structure, and to output structural information of the porous structure.

[0053] The structure predictor 4 is constructed in advance by training a large number of data sets using a machine learning model. Each of the large number of data sets includes porous property information of the porous structure, material property information corresponding to the porous structure, particle information of the porous structure, and structural information of the porous structure. The structure predictor 4 is composed of generative AI (artificial intelligence). Examples of generative AI include generative adversarial networks (GAN), variational auto encoder (VAE), generative pre-trained transformer (GPT), and a diffusion model.

[0054] The generation unit 102 calculates second porous property information indicating the properties of the second porous structure using the structural information of the second porous structure generated using the structure predictor 4 and the first property information acquired by the acquisition unit 101. Details of the process for calculating the second porous property information will be described later.

[0055] The generating unit 102 determines whether the second porous property information satisfies a property condition defined by the first porous property information. The property condition may be a condition that the porous property indicated by the second porous property information is within a predetermined range including the porous property indicated by the first porous property information, a condition that the porous property indicated by the second porous property information is larger than the porous property indicated by the first porous property information, or a condition that the porous property indicated by the second porous property information is smaller than the porous property indicated by the first porous property information.

[0056] For example, when an effective ionic conductivity is input as the first porous property information, if the effective ionic conductivity of the second porous property information is within a predetermined range including the effective ionic conductivity of the first porous property information, it is determined that the physical property conditions are satisfied. Note that when two or more types of porous properties are input as the first porous property information, the generation unit 102 determines whether the porous property indicated by the second porous property information for each type satisfies the physical property conditions. In this case, the generation unit 102 may ultimately determine that the physical property conditions are satisfied if all types of porous properties satisfy the physical property conditions.

[0057] In the example of FIG. 2 , "effective ionic conductivity greater than 1 mS / cm" is entered as the first porous physical property information in the porous physical property information input field 210. In this case, "effective ionic conductivity greater than 1 mS / cm" becomes the physical property condition. Note that if "effective ionic conductivity less than 1 mS / cm" is entered as the first porous physical property information in the porous physical property information input field 210, "effective ionic conductivity less than 1 mS / cm" becomes the physical property condition. Also, if "effective ionic conductivity equal to 1 mS / cm" is entered in the porous physical property information input field 210, "a predetermined range including 1 mS / cm" becomes the physical property condition.

[0058] When the generating unit 102 determines that the physical property conditions are satisfied, the output unit 103 outputs the structural information of the second porous structure determined to satisfy the physical property conditions.

[0059] The generation unit 102 calculates second particle information, which is particle information of the second porous structure, using the structural information generated by the structure predictor 4. Details of the process by which the generation unit 102 calculates the second particle information will be described later. The generation unit 102 determines whether the second particle information satisfies a particle condition defined by the first particle information. The particle condition may be a condition that the second particle information is contained within a predetermined range that includes the first particle information, a condition that the second particle information is larger than the first particle information, or a condition that the second particle information is smaller than the first particle information.

[0060] For example, when a particle size is input as the first particle information, it is determined that the particle condition is met if the particle size indicated by the second particle information is within a predetermined range including the particle size indicated by the first particle information.

[0061] When two or more types of particle information are input as the first particle information, the generation unit 102 determines whether or not the second particle information satisfies the particle condition for each type. In this case, if all types of second particle information satisfy the particle condition, the generation unit 102 may finally determine that the particle condition is satisfied.

[0062] In the example of FIG. 2 , an average particle diameter of "3 μm" is entered as the first particle information in the particle information input field 230. In this case, a predetermined range including the average particle diameter of "3 μm" becomes the particle condition. Note that if "average particle diameter is greater than 3 μm" is entered as the first particle information in the particle information input field 230, "average particle diameter is greater than 3 μm" becomes the particle condition. Also, if "average particle diameter is smaller than 3 μm" is entered as the first particle information in the particle information input field 230, "average particle diameter is smaller than 3 μm" becomes the particle condition. Multiple conditions may be specified, such as "average particle diameter is smaller than 3 μm" and "porosity is 60% or more."

[0063] When the generation unit 102 determines that the second porous property information does not satisfy the property conditions, it changes the generation parameters used when generating the structural information and regenerates the structural information. The generation parameters are parameters of the generation AI that constitutes the structure predictor 4. When the generation AI is a GAN, the generation parameters are random noise input to the generator that constitutes the GAN. When the generation AI is a VAE, the generation parameters correspond to points randomly sampled in the latent space.

[0064] When the generation unit 102 determines that the second particle information does not satisfy the particle condition, it changes the generation parameters and regenerates the structural information in the same way as when the physical property condition is not satisfied.

[0065] The generation unit 102 may determine whether or not both the physical property conditions and the particle conditions are satisfied. The generation unit 102 may regenerate the structural information until both the physical property conditions and the particle conditions are satisfied. In this case, the particle conditions may be determined before the physical property conditions. The particle conditions have a higher screening effect than the physical property conditions. Therefore, by determining the particle conditions before the physical property conditions, structural information that satisfies the physical property conditions and the particle conditions can be efficiently calculated.

[0066] The output unit 103 outputs the structural information of the second porous structure determined by the generation unit 102 to satisfy the particle condition.

[0067] The output unit 103 calculates the degree of fulfillment of at least one of the physical property conditions and the particle conditions for each of the plurality of structural information, and outputs the plurality of structural information in a display order according to the calculated degrees of fulfillment. The degree of fulfillment takes a larger value as the second porous physical property information fulfills the physical property conditions, and the degree of fulfillment takes a larger value as the second particle information fulfills the particle conditions. The degree of fulfillment may be calculated using only either the physical property conditions or the particle conditions.

[0068] In the example of FIG. 2 , the physical property condition is specified as "effective ionic conductivity greater than 1 mS / cm." In this case, the degree of fulfillment is higher for second porous structures in which the effective ionic conductivity indicated by the second porous property information is greater than 1 mS / cm and closer to 1 mS / cm. In the example of FIG. 2 , the particle condition is specified as an average particle size of "3 μm." In this case, the degree of fulfillment is higher for second porous structures in which the average particle size indicated by the second particle information is closer to "3 μm." Note that when both the physical property condition and the particle condition are used, the output unit 103 may calculate the sum of the degree of fulfillment of the physical property condition and the degree of fulfillment of the particle condition as the final degree of fulfillment.

[0069] Referring back to Figure 1, the memory 11 is configured as a non-volatile rewritable storage device such as a hard disk drive or a solid state drive.

[0070] The memory 11 includes a first memory unit 111 and a second memory unit 112. The first memory unit 111 stores a material property database. The material property database is a database that stores a large number of data sets in which the compound names of the particles that make up the porous structure or the materials that fill the voids in the particles are associated with the material properties of the compounds indicated by the compound names. An example of a compound name stored in the material property database is LiCoO2, and an example of a material property stored in the material property database is the ionic conductivity of LiCoO2.

[0071] The second storage unit 112 stores structural information indicating the structure of the second porous structure generated by the generation unit 102, for which a user has input a save instruction. The second porous structure has, for example, a crystalline structure. The structural information is configured as a three-dimensional model that represents the structure of the second porous structure using a large number of voxels within a space of a predetermined size. The space is configured as, for example, a rectangular parallelepiped of a predetermined size.

[0072] 2 is a diagram showing an example of a first image 200 displayed on the display unit 32. The first image 200 includes a porous property information input field 210, a material property information input field 220, a particle information input field 230, and an execute button 240. The porous property information input field 210 is an input field for first porous property information. In this example, "effective ionic conductivity" is input as the first porous property information. Furthermore, "1 mS / cm" is input as the value of the effective ionic conductivity. Furthermore, "greater than" is input as the condition for the effective ionic conductivity.

[0073] That is, in this example, "effective ionic conductivity is greater than 1 mS / cm" is input as the first porous property information. The porous property information input field 210 may include input fields for one or more porous properties other than the first porous property information and effective ionic conductivity. In this case, the user can input one or more porous properties, the value of each porous property, and the conditions for each value as the first porous property information.

[0074] The material property information input field 220 is an input field for first material property information. In this example, the material property information input field 220 includes an input field for the material properties (here, ionic conductivity) of each of the two types of particles A and B that constitute the first porous structure, and an input field for the material properties (here, ionic conductivity) of the voids between particles A and B. In this case, the first material property information includes the ionic conductivities between particles A and B and the ionic conductivity of the material of the voids between particles A and B. The material property information input field 220 may include an input field for one type of particle, or may include input fields for three or more types of particles. Furthermore, the material property information input field 220 may input material properties other than ionic conductivity for each particle and void. Furthermore, the material property information input field 220 may include input fields for two or more material properties for each particle and void.

[0075] The particle information input field 230 is an input field for first particle information. In this example, the average particle diameter of the particles is input into the particle information input field 230. When the first porous structure includes only particles A identified by a first element symbol, the average particle diameter may be calculated as follows: (average particle diameter) = (particle diameter of particles A x predetermined number of particles A) / predetermined number of particles A. When the first porous structure includes particles A identified by a first element symbol and particles B identified by a second element symbol, but does not include particles identified by element symbols other than the first element symbol and the second element symbol, the average particle diameter may be calculated as follows: (average particle diameter) = ((average particle diameter of particles A) + (average particle diameter of particles B)) / 2. The particle information input field 230 may also have an input field for particle information other than the average particle diameter. When multiple material property databases are stored in the first memory unit 111, the first image 200 may include a selection field for selecting one of the material property databases. The multiple material property databases include a database storing material properties based on experimental results and a database storing material properties based on calculation results. The first image 200 may include an input field for specifying the number of pieces of structural information to be output.

[0076] 3 is a diagram showing an example of a second image 300 displayed on the display unit 32. The second image 300 includes an index display field 310, a structural information display field 320, and a save button 340.

[0077] The index display field 310 displays the index used to calculate the degree of sufficiency. In this example, the effective ionic conductivity is used as the physical property condition, and this effective ionic conductivity is used to calculate the degree of sufficiency. Therefore, the index display field 310 displays "effective ionic conductivity" as the index.

[0078] The structural information display field 320 displays the structural information of the second porous structures in descending order of satisfaction. In this example, the structural information display field 320 displays structural information with a higher satisfaction level in the upper left and structural information with a lower satisfaction level in the lower right. In this example, six second porous structures satisfied the physical property conditions and particle conditions. Therefore, the structural information display field 320 displays six pieces of structural information, ranked from first to sixth.

[0079] The save button 340 is a button for saving one or more pieces of structural information displayed in the structural information display field 320 in the second storage unit 112. The user uses the pointer 330 to select structural information that the user wishes to save from the list of structural information displayed in the structural information display field 320, and presses the save button 340. This causes the output unit 103 to save the selected structural information in the second storage unit 112. The selection operation may be, for example, a click or tap operation performed by positioning the pointer 330 on the desired structural information.

[0080] Furthermore, the user can enlarge any one of the structural information items displayed in the structural information display field 320. This enlargement can be instructed, for example, by positioning the pointer 330 on the desired structural information item and double-clicking or double-tapping the item.

[0081] When an instruction for enlarged display is input, the output unit 103 displays a third image 400 on the display unit 32. Fig. 4 is a diagram showing an example of the third image 400 displayed on the display unit 32. The third image 400 displays an index display field 410, a ranking display field 420, a structural information display field 430, a porous physical property information display field 440, a particle information display field 450, and a save button 460.

[0082] The index display field 410 is the same as the index display field 310. The ranking display field 420 displays the ranking of the structures displayed in the structure information display field 430.

[0083] The structural information display field 430 displays the structural information that is instructed to be enlarged in the second image 300 .

[0084] The porous property information display field 440 displays second porous property information of the structural information displayed in the structural information display field 430. In this example, since "effective ionic conductivity" was calculated as the second porous property information, the porous property information display field 440 displays the effective ionic conductivity of the structural information displayed in the structural information display field 430.

[0085] The particle information display field 450 displays the second particle information of the structure displayed in the structure information display field 430. In this example, since the "average particle size" of the particles is calculated as the second particle information, the particle information display field 450 displays the average particle size of the structure information displayed in the structure information display field 430.

[0086] The save button 460 is a button for saving the structural information displayed in the structural information display field 430. When the save button 340 is pressed by the user, the output unit 103 saves the structural information displayed in the structural information display field 430 in the second storage unit 112.

[0087] FIG. 5 is a flowchart showing an example of processing performed by the structural information providing system 100 according to the embodiment.

[0088] (Step S1) The acquisition unit 101 acquires, from the input unit 2, the first porous property information received by the input unit 2. Here, it is assumed that effective ionic conductivity has been input as the first porous property information.

[0089] (Step S2) The acquisition unit 101 acquires from the input unit 2 the first material property information received by the input unit 2. Here, as shown in FIG. 2, the ionic conductivity of each of particles A and B and the ionic conductivity of the material filling the voids between particles A and B are input as the first material property information. Note that the material property indicated by the first material property information is the same as the porous property indicated by the first porous property information. For example, if effective ionic conductivity is input as the first porous property information, ionic conductivity is input as the first material property information.

[0090] When a compound name is input as the first material property information, the acquiring unit 101 acquires material property information corresponding to the compound name from the first storage unit 111. For example, when LiCoO2 is input as the compound name, the ionic conductivity of LiCoO2 is acquired.

[0091] (Step S3) The acquisition unit 101 acquires the first particle information received by the input unit 2 from the input unit 2. An example of the first particle information is the average particle size of the particles.

[0092] (Step S4) The generation unit 102 generates structural information of the second porous structure using the first porous property information, first material property information, and first particle information acquired by the acquisition unit 101. As described above, the generation unit 102 inputs the first porous property information, first material property information, and first particle information to the structure predictor 4, thereby acquiring the structural information of the second porous structure output from the structure predictor 4.

[0093] The generation unit 102 may generate structural information about the second porous structure using, for example, a particle stacking method. FIGS. 7A, 7B, 7C, and 7D are diagrams illustrating how structural information is generated by the particle stacking method. The particle stacking method is a method for generating structural information about a porous structure in which particles 701 are stacked by repeatedly applying an appropriate acceleration to particles 701 and causing the particles 701 to fall from their initial positions into a space 700. First, in FIG. 7A, a first particle 701 is being dropped. Next, in FIG. 7B, a second particle 701 is being dropped. Next, in FIG. 7C, a third particle 701 is being dropped. Finally, in FIG. 7D, the processes of FIGS. 7A to 7C are repeated, resulting in a multiplicity of particles 701 being stacked. Each time the generation unit 102 repeats the dropping of the particles 701, the position of the dropped particles 701 may be changed according to conditions such as the particle 701 overlapping condition and the particle 701 packing rate. Alternatively, the generating unit 102 may change the arrangement of the fallen particles 701 until a particle filling rate (or a similar stopping criterion) is reached. The shape of the particles 701 may be a sphere, an ellipsoid, a prism, a polyhedron, etc. The generating unit 102 may adjust the size of the particles 701 to satisfy the average particle size specified by the first particle information.

[0094] (Step S5) The generation unit 102 calculates second particle information from the structural information of the second porous structure. FIGS. 8A, 8B, and 8C are diagrams illustrating how the second particle information is calculated. Hereinafter, the second particle information will be described as a pore size distribution. The pore size distribution is information indicating the spatial distribution of particles 701. FIG. 8A shows structural information of a second porous structure in which particles 701 are arranged within a space 700. The generation unit 102 sets a three-dimensional lattice 710 in the space 700 ( FIG. 8B ). Next, the generation unit 102 places a sphere 730 at a certain lattice point 720 and calculates the maximum diameter at which the sphere 730 does not come into contact with particles or other spheres 730 ( FIG. 8C ). The generation unit 102 calculates the pore size distribution by performing this process for each lattice point 720. Therefore, the pore size distribution is information representing the distribution of particles 701 using the position and radius of each sphere 730.

[0095] (Step S6) The generation unit 102 determines whether the second particle information satisfies the particle condition. If the particle condition is satisfied (YES in step S6), the process proceeds to step S7. If the particle condition is not satisfied (NO in step S6), the process returns to step S4. If the second particle information does not satisfy the particle condition, the generation unit 102 changes the generation parameters and regenerates the structural information of the second porous structure.

[0096] (Step S7) The generation unit 102 calculates second porous property information from the structural information of the second porous structure and the first material property information. The material properties indicated by the first material property information include the properties of the particles or the material filling the voids, as described above. The material properties include, for example, the ionic conductivity of the particles and the ionic conductivity of the material filling the voids. The porous properties indicated by the second porous property information include, as described above, the properties of the porous structure composed of particles and voids. The porous properties include, for example, the effective ionic conductivity of the porous structure. The material properties of the particles may be anisotropic.

[0097] The porous properties indicated by the second porous property information may be expressed by decomposing them into tensor forms for the x, y, and z directions, or by the average or variance of the tensor components of the porous properties, or by the tensor components of the porous properties in a direction specified in advance by the user. The following describes a case where electrical conductivity and effective electrical conductivity are used as the first material property information and the second porous property information, respectively. The generator 102 calculates the spatial distribution of the effective electrical conductivity by solving a partial differential equation expressed using the electrical conductivity indicated by the first material property information. This partial differential equation is derived from Ohm's law and expresses the distribution of the effective electrical conductivity in three components: x, y, and z. This partial differential equation also includes spatial constraints defined by the structural information of the second porous structure. The generator 102 calculates the spatial distribution of the calculated effective electrical conductivity as the second porous property information. This allows the generator 102 to calculate the effective electrical conductivity of the porous structure.

[0098] (Step S8) The generator 102 determines whether the second porous physical property information satisfies the physical property conditions. If the physical property conditions are satisfied (YES in step S8), the process proceeds to step S9. If the physical property conditions are not satisfied (NO in step S8), the process returns to step S4. If the second porous physical property information does not satisfy the physical property conditions, the generator 102 changes the generation parameters and regenerates the structural information of the second porous structure.

[0099] (Step S9) The generation unit 102 determines whether a termination condition is satisfied. The termination condition can be, for example, a condition that a predetermined number or more pieces of structural information of the second porous structure that satisfy the physical property conditions and particle conditions have been obtained, or a condition that the number of times structural information of the second porous structure has been generated has reached a predetermined number. If the termination condition is satisfied (YES in step S9), the process proceeds to step S10. If the termination condition is not satisfied (NO in step S10), the process returns to step S4.

[0100] (Step S10) The output unit 103 calculates a degree of fulfillment for each of a plurality of pieces of structural information that satisfy the physical property conditions and the particle conditions. Here, the output unit 103 calculates a larger value of the degree of fulfillment as the effective ionic conductivity of each piece of structural information is closer to the effective ionic conductivity defined as the physical property conditions.

[0101] (Step S11) The output unit 103 determines the display order of the structural information according to the degree of sufficiency calculated in step S10, and displays the second image 300 in which the structural information is arranged in the determined display order on the display unit 32. Note that the degree of sufficiency may be determined simply in descending order of effective ionic conductivity. In this case, the second image 300 displays the structural information in descending order of effective ionic conductivity.

[0102] (Step S12) The input unit 2 determines whether or not a save instruction has been received. The save instruction is input by pressing the save button 340 on the second image 300 or the save button 460 on the third image 400. If the input unit 2 has received the save instruction (YES in step S12), the output unit 103 stores the specified structural information in the second storage unit 112 (step S13). If the input unit 2 has not received the save instruction (NO in step S12), the process waits in step S12.

[0103] 6 is a sequence diagram showing an example of processing by the structural information providing system 100 according to the embodiment. The same step numbers in FIG. 6 and FIG. 5 represent the same processing. The information processing system 1 acquires first porous property information, first material property information, and first particle information from the input unit 2 (steps S1, S2, and S3). When a compound name is input as the first material property information, the information processing system 1 acquires material property information corresponding to the compound name from the first storage unit 111 (step S2').

[0104] The information processing system 1 executes steps S4 to S10, thereby obtaining structural information about the second porous structure that satisfies the physical property conditions and particle conditions.

[0105] The information providing system 3 displays the structural information of the second porous structure that satisfies the physical property conditions and the particle conditions on the display unit 32 (step S11). In this case, the structural information is displayed using the second image 300 and the third image 400.

[0106] The information processing system 1 acquires the save instruction received by the input unit 2 (step S12).

[0107] The information processing system 1 stores the specified structure information in the second storage unit 112 (step S13).

[0108] As described above, according to this embodiment, structural information of the second porous structure is generated using the first particle information in addition to the first porous property information and the first material property information. Therefore, structural information of a porous structure that can actually be manufactured can be generated. As a result, it is possible to improve the performance of electrochemical devices and to design porous structures that can be realized in actual manufacturing processes. This is expected to significantly reduce the time and cost required for commercializing devices and promote technological innovation in the field of electrochemical devices.

[0109] In each of the above embodiments, each component may be configured with dedicated hardware, or may be realized by executing a software program suitable for that component. Each component may be realized by a program execution unit such as a CPU (Central Processing Unit) or a processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

[0110] The present disclosure can employ the following aspects.

[0111] (1) Some or all of the components of the structural information providing system 100 are a computer system composed of a microprocessor, ROM (Read Only Memory), RAM (Random Access Memory), a hard disk unit, a display unit, a keyboard, a mouse, etc. The RAM or hard disk unit stores a computer program. The information processing system 1 achieves its functions by the microprocessor operating in accordance with the computer program. The computer program is composed of a combination of multiple instruction codes that indicate commands to the computer to achieve a specified function.

[0112] (2) Some or all of the components of the structural information providing system 100 may be configured as a single system LSI (Large Scale Integration). A system LSI is an ultra-multifunctional LSI manufactured by integrating multiple components on a single chip, and specifically, is a computer system including a microprocessor, ROM, RAM, etc. The RAM stores a computer program. The system LSI achieves its functions when the microprocessor operates in accordance with the computer program.

[0113] (3) Some or all of the components constituting the structural information providing system 100 may include a removable IC card or a standalone module as a component. The IC card or module is a computer system composed of a microprocessor, ROM, RAM, etc. The IC card or module may include the above-mentioned ultra-multifunctional LSI. The IC card or module achieves its functions when the microprocessor operates according to a computer program. This IC card or module may be tamper-resistant.

[0114] (4) The present disclosure may be embodied as the methods described above, a computer program for implementing these methods on a computer, or a digital signal comprising the computer program.

[0115] The present disclosure may also be a computer program or a digital signal recorded on a computer-readable recording medium, such as a flexible disk, a hard disk, a CD (Compact Disc)-ROM, a DVD, a DVD-ROM, a DVD-RAM, a BD (Blu-ray (registered trademark) Disc), a semiconductor memory, etc. Alternatively, the present disclosure may be a digital signal recorded on such a recording medium.

[0116] In addition, the present disclosure may transmit a computer program or digital signal via a telecommunications line, a wireless or wired communication line, a network such as the Internet, data broadcasting, or the like.

[0117] In addition, the present disclosure may be implemented by another independent computer system by recording the program or digital signal on a recording medium and transferring it, or by transferring the program or digital signal via a network or the like.

[0118] The present disclosure has the effect of, for example, being able to appropriately assist a user in exploring the production process of an inorganic material, and can be used in a computer device or system for displaying information about the production process.

[0119] REFERENCE SIGNS LIST 1: Information processing system 2: Input unit 3: Information provision system 4: Structure predictor 10: Processor 11: Memory 31: Display control unit 32: Display unit 100: Structural information provision system 101: Acquisition unit 102: Generation unit 103: Output unit 111: First storage unit 112: Second storage unit 200: First image

Claims

1. An information processing method executed by a computer, comprising: acquiring first porous property information indicating the physical properties of a first porous structure itself composed of a plurality of particles; acquiring first material property information regarding the material properties of the first porous structure, including at least one of (a) information indicating the physical properties or substance name of the plurality of particles and (b) information indicating the physical properties or substance name of the substance filling the voids between the plurality of particles; acquiring first particle information regarding at least one of the structure and positional relationship of the plurality of particles; using the first porous property information, the first material property information, and the first particle information, generating structural information indicating the structure of a second porous structure in which at least one of the structure and positional relationship of the plurality of particles relative to the first porous structure is taken into consideration; and outputting the structural information.

2. The information processing method according to claim 1, further comprising: calculating second porous property information indicating the properties of the second porous structure itself using the structural information and the first material property information; and determining whether the second porous property information satisfies the property conditions defined by the first porous property information; and wherein the outputting includes outputting the structural information of the second porous structure that is determined to satisfy the property conditions.

3. The information processing method according to claim 1 or 2, further comprising: calculating second particle information relating to at least one of the structure and positional relationship of the plurality of particles constituting the second porous structure using the structural information; and determining whether the second particle information satisfies the particle conditions defined by the first particle information; and wherein the outputting includes outputting the structural information of the second porous structure that is determined to satisfy the particle conditions.

4. The information processing method of claim 1 or 2, wherein generating the structural information includes obtaining the structural information output from a structure predictor by inputting the first porous property information, the first material property information, and the first particle information into a structure predictor, and the structure predictor is trained to receive as input porous property information indicating the properties of the porous structure, material property information related to the material properties of the porous structure, and particle information related to at least one of the structure and positional relationship of a plurality of particles constituting the porous structure, and to output structural information indicating the structure of the porous structure.

5. The information processing method according to claim 2, further comprising, when it is determined that the physical property conditions are not satisfied, changing generation parameters used in generating the structural information and regenerating the structural information.

6. The information processing method according to claim 3, further comprising, when it is determined that the particle condition is not satisfied, changing generation parameters used in generating the structural information and regenerating the structural information.

7. An information processing method according to claim 1 or 2, wherein generating the structural information includes generating a plurality of pieces of structural information by changing generation parameters, and further includes calculating, for each of the plurality of pieces of structural information, a degree of fulfillment of at least one of the property conditions defined by the first porous property information and the particle conditions defined by the first particle information, and outputting the plurality of pieces of structural information in a display order according to the calculated degree of fulfillment.

8. An information processing system including a processor, wherein the processor performs the following operations: acquire first porous property information indicating the physical properties of a first porous structure itself composed of a plurality of particles; acquire first material property information regarding the material properties of the first porous structure, including at least one of (a) information indicating the physical properties or substance name of the plurality of particles and (b) information indicating the physical properties or substance name of the substance filling the voids between the plurality of particles; acquire first particle information regarding at least one of the structure and positional relationship of the plurality of particles; use the first porous property information, the first material property information, and the first particle information to generate structural information indicating the structure of a second porous structure in which at least one of the structure and positional relationship of the plurality of particles relative to the first porous structure is taken into consideration; and output the structural information.

9. A program that causes a computer to execute the following steps: acquire first porous property information that indicates the physical properties of a first porous structure itself composed of a plurality of particles; acquire first material property information regarding the material properties of the first porous structure, including information regarding at least one of (a) information indicating the physical properties or substance name of the plurality of particles, and (b) information indicating the physical properties or substance name of the substance that fills the voids between the plurality of particles; acquire first particle information regarding at least one of the structure and positional relationship of the plurality of particles; use the first porous property information, the first material property information, and the first particle information to generate structural information that indicates the structure of a second porous structure that takes into account at least one of the structure and positional relationship of the plurality of particles relative to the first porous structure; and output the structural information.

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