Model and simulate material microstructures

Abstract

An embodiment generates a computer-based model (e.g., a computer-aided design (CAD) model) of a material. One such embodiment selects at least one portion of the model that represents a unit of the material. Further, at least one physical or chemical property of the model is estimated based on the proposed modification to the selected at least one portion of the model and the proposed modification to the remaining portions of the model that represent the unit of the material. The selection and estimation are iterated until the estimated at least one physical or chemical property meets a user specification of the at least one physical or chemical property. In this manner, such an embodiment creates a model of the subject material that meets the user-specified physical and chemical properties.

Description

[0001] Related Applications

[0002] This application claims the benefit of U.S. Provisional Application No. 63 / 089,087, filed on October 8, 2020. The entire teachings of the above application are incorporated herein by reference. Background Art

[0003] Existing methods for generating models of material microstructures and simulating them have two common variations: macroscale modeling and mesoscale modeling. For macroscale modeling, elements are defined as "materials" or non-"materials" in discrete simulation boxes. This macroscale modeling provides a way to illustrate microstructures in macroscale models. Mesoscale modeling uses spherical particles of different sizes to fill simulation cells and provides an approximation of medium-sized structures. However, using mesoscale modeling, the model ultimately has only spherical particles. This is an important approximation. Both macroscale and mesoscale methods produce idealized structures that are generally unable to represent real-world materials and the derived properties of these materials. There are atomic methods for generating microporous structural models, but at the atomic level, the system size and time scale that can be handled are limited. Summary of the invention

[0004] Therefore, it is necessary to accurately model and simulate the microstructure of the material. Embodiments provide such functions. Embodiments of the present invention provide an efficient method for generating a computer model of a porous microstructure (porousmicrostructure) for a material that is chemically and physically realistic. This is useful for improving the simulation of material properties at nanoscale and larger scales. Embodiments can be implemented to model and simulate battery electrodes, and other examples. In addition, embodiments can be deployed to model and simulate any material (e.g., coating, composite material, formulated product, enhanced oil recovery and catalysis, and other examples) that is porous at the nanoscale. In an embodiment, after the model is generated, the generated model can be deployed to simulate the real-world use of the material represented by the model. In an exemplary embodiment, the model constructed is used for simulation according to principles known to those skilled in the art.

[0005] Embodiments may also be used to better model and simulate real-world material structures composed of more than one material (eg, materials with surface coatings or heterostructures, among other examples).

[0006] Example embodiments provide a computational method that performs an iterative and random process to obtain a realistic computer model of the microstructure of a material. Such an embodiment begins with an empty box representing a three-dimensional (3D) repeating unit of the material to be modeled, and randomly selects one or more small parts of the box (step 1). Next, the randomly selected parts of the box are filled with beads representing a material with a predetermined density (step 2). Then, the physical properties of the resulting model, such as porosity (percent solid and percent fluid) and tortuosity (step 3), are calculated. Depending on the calculated physical properties, the results of step 1 are used, and one or more new parts of the box are randomly selected to represent the material and filled with beads (repeating steps 1 and 2). The process is repeated until the desired physical properties are achieved. Different models can be generated by repeating the above process to obtain a final statistical average model of a porous material with desired physical properties (i.e., for a non-limiting example, the model is consistent with the material properties known in the real world).

[0007] After identifying a suitable design, an alternative embodiment iterates steps 1 and 3 and performs step 2 to create an actual model. In such an embodiment, one or more small portions of the box are randomly selected (step 1). Then, the physical properties of the model are estimated, in which the selected portions are assumed to be filled with solids and the unselected areas are assumed to be filled with fluids (e.g., gases and / or liquids). If the estimated physical properties meet the expected physical properties (the physical properties of interest), the method continues (associating the selected portions with beads or otherwise filling the selected portions with beads) and creating the model. If the expected physical properties do not meet the expected criteria, the process is repeated.

[0008] Yet another embodiment is directed to a computer-implemented method for generating a model of a material. Such an embodiment begins by selecting at least one portion of a model representing a unit of a material. Next, at least one physical property of the model is estimated based on: (i) a proposed modification to the selected at least one portion of the model; and (ii) a proposed modification to the remainder of the model representing the unit of the material. If the estimated at least one physical property meets the requirements (e.g., a user-specified value or a system-specified value for the at least one property), the method ends (if the model was created to estimate the at least one physical property), or the method continues to create the model based on the proposed modifications. If the estimated property does not meet the requirements, the selection and estimation steps are iterated until the estimated at least one physical property meets the user specification of the at least one physical property. An embodiment may estimate any desired physical property of the model (physical property of interest). For example, an embodiment may consider porosity and / or curvature.

[0009] According to an embodiment, estimating at least one physical property of the model includes: updating the model according to the proposed modification to the selected at least one portion and according to the proposed modification to the remaining portions of the model. In such an embodiment, the model is updated by: filling the selected at least one portion of the model with beads of material representing the at least one portion; and filling the remaining portions of the model representing the units of material with beads of material representing the remaining portions of the units of material. Furthermore, in such an embodiment, the at least one physical property is estimated by calculating the at least one physical property using the updated model.

[0010] According to an embodiment, the beads filling the selected at least one portion represent a solid. In another embodiment, the beads filling the remaining portion represent a fluid, such as a liquid or a gas. In yet another embodiment, the at least one portion is composed of a first closed volume and a second closed volume, the second closed volume surrounding the first closed volume. In such an example embodiment, filling the at least one portion with beads representing the material of the selected at least one portion of the model includes: filling the first closed volume with beads representing the material of the first closed volume; and filling the second closed volume with beads representing the material of the second closed volume. In an embodiment, the beads filling the second closed volume represent a coating surrounding the first closed volume.

[0011] In an alternative embodiment of the method, at least one physical property of the model is estimated using a template. In such an embodiment, if the estimated physical property meets the requirements, the method updates the model according to the proposed modifications to the selected at least one portion and according to the proposed modifications to the remainder of the model. However, if the estimated physical property (estimated using the template) does not meet the requirements (i.e., the user specification), such an embodiment continues to iterate the steps of selecting and estimating until the estimated at least one physical property meets the user specification of the at least one physical property. Once the iteration determines that the estimated physical property meets the requirements, the model is updated or created according to the proposed modifications to the selected at least one portion and the proposed modifications to the remainder of the model. In such an embodiment, the model is updated by filling the selected at least one portion of the model (which may include all portions selected during the entire iteration) with beads of material representing the at least one portion; and filling the remainder of the model representing the cells of the material (the volume of the model excluding the selected portion) with beads of material representing the remainder of the cells of the material.

[0012] In an embodiment, the unit may be a three-dimensional (3D) repeating unit. In another example embodiment, the 3D repeating unit is cubic or rectangular (e.g., a cuboid or a rectangular prism). According to an embodiment, the selected at least one portion is a closed volume. Example closed volumes that may be utilized in an embodiment include a sphere, a cylinder, and / or an ellipsoid.

[0013] Yet another embodiment is directed to a system comprising a processor and a memory having computer code instructions stored thereon. In such an embodiment, the processor and the memory are configured with the computer code instructions to cause the system to implement any embodiment or combination of embodiments described herein.

[0014] Another embodiment of the present invention is directed to a cloud computing implementation for generating a model of a material. Such an embodiment is directed to a computer program product executed by a server communicating with one or more clients across a network, wherein the computer program product includes instructions that, when executed by one or more processors, cause the one or more processors to implement any of the embodiments described herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The patent or application file contains at least one drawing executed in color. Copies of the patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

[0016] The foregoing will become apparent from the following more particular description of example embodiments, as illustrated in the accompanying drawings, in which like reference numerals refer to the same parts throughout the different views. The drawings are not necessarily drawn to scale, emphasis instead being placed upon illustrating the embodiments.

[0017] Figure 1 is a flow chart of a method for generating a model of a material according to an embodiment.

[0018] Figure 2 Steps of an embodiment for building a model of a material are shown.

[0019] Figure 3 Steps in a process for building a microstructural model of a material having a coating in one embodiment are shown.

[0020] Figure 4 is a simplified block diagram of a computer system for generating a model of a material according to an embodiment.

[0021] Figure 5 is a simplified block diagram of a computer network environment in which embodiments of the present invention may be implemented. DETAILED DESCRIPTION

[0022] The following is a description of example embodiments.

[0023] The teachings of all patents, published applications, and references cited herein are incorporated by reference in their entirety.

[0024] Embodiments can be used for any modeling and simulation, wherein microstructural details contribute to understanding product performance and behavior (e.g., aging, product life cycle, other physical or chemical properties, etc.). For non-limiting examples, embodiments model and implement simulations of coatings, composite materials, formulated products, enhanced oil recovery and catalysis, and other examples. Specific parameters can be developed based on materials of interest for the aforementioned applications. These parameters can be utilized in the embodiments described herein to provide modeling and simulations for these applications (e.g., coatings, composite materials, formulated products, enhanced oil recovery and catalysis). According to an embodiment, application-specific parameters are parameters describing the interactions between beads, wherein each bead represents a different portion of the material. In an example embodiment, the interaction parameters constitute a force field for mesoscale dynamics simulation, and properties such as average porosity and curvature can be measured according to the force field, as described below. Interaction parameters can be defined according to each bead type, wherein each bead type represents a group of well-defined atoms (or particles) within a material (e.g., solid, liquid, or gas). This so-called "coarse-graining" of atoms to beads allows simulations to be performed at lengths and time scales greater than those typically possible in all-atom simulations. For example, embodiments may be deployed to simulate battery materials at the mesoscale level rather than the atomic level. Such embodiments provide key insights into electrode porosity during charging and discharging of the battery.

[0025] An improvement to previously available methods provided by the embodiment is to construct a material model (model of material) that does not result in the superposition of spheres--this is the working mode of computer models so far. On the contrary, the embodiment generates a computational model of a detailed microstructure that can be specifically tailored to accurately represent the structure and properties (e.g., SEM data, BET data, synthetics) observed in the experiment. Specifically, the progress from spherical particle approximation (i.e., existing methods that only use spheres to model materials) to the realistic particle structure provided by the embodiment allows a more accurate model representing physical measurement properties. The embodiment of the present invention can be automatically used with minimal user input, which allows rapid exploration of design parameter space and improved user experience. The embodiment of the present invention can be used as a general tool in other workflows (e.g., simulation workflows) and on existing modeling and simulation platforms. The embodiment can be implemented in existing software suites and software packages. In such an implementation, existing software is modified to perform functions described herein, e.g., method 100.

[0026] Embodiments provide functionality for 3D nanoscale modeling and simulation of materials (eg, battery electrode materials). Figure 1 1 is a flow chart of one such computer-implemented method 100 for generating a model of a material of interest. The method 100 begins at step 101 by selecting at least one portion of a model representing a unit of a subject material. In the method 100, the unit of the material may be a 3D repeating unit. In an embodiment of the method 100, the 3D repeating unit may be cubic or rectangular. In an example embodiment of the method 100, at least one selected portion is a closed volume. Example closed volumes that may be utilized in the method 100 include a sphere, a cylinder, and / or an ellipsoid.

[0027] Next, at step 102, at least one physical property of the model is estimated based on (1) the proposed modifications to at least one portion of the model selected at step 101 and (2) the proposed modifications to the remainder of the model representing the elements of the material. An embodiment may estimate any desired physical property of the model at step 102. For example, an embodiment may estimate porosity and / or curvature.

[0028] In an embodiment of the method 100, estimating at least one physical property of the model at step 102 includes updating the model according to the proposed modifications (modifications to the at least one portion selected at 101 and the proposed modifications to the rest of the model). In such an embodiment, the model is updated at step 102 by filling the selected at least one portion of the model with beads representing the material of the selected at least one portion, and filling the rest of the model representing cells of the material with beads representing the material of the rest of the cells of the material. According to an embodiment, the beads are mesoscale models, where each bead represents a group of atoms. In an embodiment, the bead representation itself is implemented using standard techniques known to those skilled in the art of material modeling (i.e., software programming and supporting data structures). Furthermore, in such an embodiment, at step 102, the at least one physical property is estimated by calculating the at least one physical property using the updated model. In such an embodiment, a new model is generated at each iteration of step 102. According to an embodiment, the beads filling at least one portion represent a solid. In another embodiment, the beads filling the rest represent a fluid.

[0029] As described herein, physical properties are calculated at step 102. Example physical properties that may be calculated at step 102 include porosity (represented by ε) and curvature (represented by τ). In an embodiment, porosity may be estimated by calculating a "volume surface" that separates one portion of a material from another (in a battery simulation, the electrode from the electrolyte). Such a surface may be obtained using standard computational techniques. In an embodiment, the surface divides a simulation cell into the volume occupied by each material. The volume occupied by the material (surface) may be set relative to the total volume of the simulation cell to obtain the porosity. The porosity may be estimated by calculating the diffusion coefficient of the beads in the bulk fluid (D0) and the diffusion coefficient in the actual structure having a porosity ∈ (D e ) to obtain the curvature τ. Then, The diffusion coefficient can be calculated based on the mean square displacement of the beads measured in the mesoscale dynamics simulation for a given force field. In an embodiment, the diffusion coefficient can be calculated as described in Jinliang Yuan, Bengt Sundén, On mechanisms and models of multi-component gas diffusion in porous structures of fuel cell electrodes (International Journal of Heat and Mass Transfer, Volume 69, 2014, pp. 358-374), the content of which is incorporated herein by reference.

[0030] In yet another embodiment of method 100, the at least one portion selected at step 101 is comprised of a first closed volume and a second closed volume, the second closed volume surrounding the first closed volume. In such an example embodiment, at step 102, filling the at least one portion of the selected at least one portion of the model with beads representing a material includes filling the first closed volume with beads representing a material of the first closed volume, and filling the second closed volume with beads representing a material of the second closed volume. In such an embodiment, the beads filling the second closed volume represent a coating surrounding the first closed volume.

[0031] Back to Figure 1If the at least one physical property estimated at step 102 satisfies the requirement (e.g., a user-specified value or a system-specified value), the method ends (if an updated model was created and saved in computer memory at step 102 to estimate the at least one physical property), otherwise the method continues to create the model according to the proposed modification. However, if the estimated property does not meet the requirement, the method moves to step 103, where the selection (step 101) and estimation (step 102) are iterated (i.e., repeated) until, in a given iteration, the at least one physical property estimated at step 102 meets the user specification of the at least one physical property. During each iteration, a new portion of the model representing the element of the material is selected at step 101, and the property is estimated at step 102 based on the proposed modification to all portions that have been selected throughout the iteration.

[0032] In an alternative embodiment of method 100, a template (e.g., as described below with respect to Figure 2 and Figure 3 The template 222 and template 332 described above are used to estimate at least one physical property of the model. Thus, in embodiments, the property calculation may be based on the template or on a model derived from the template. According to embodiments, the porosity is calculated by calculating the "volume surface" that separates one portion of the material from another portion as described above, and the porosity may be calculated by calculating the diffusion coefficient of the beads in the bulk fluid (D0) and the diffusion coefficient in the actual structure having the porosity ∈ (D e ) to obtain the curvature τ. In such an embodiment, the template provides a surface. According to an embodiment, once the estimated physical properties meet the requirements, the method updates / creates the model according to the proposed modifications to the selected at least one portion and according to the proposed modifications to the rest of the model. However, if at step 102, the physical properties estimated using the template do not meet the requirements (i.e., the user specification), the method moves to step 103, in which the selection (step 102) and estimation (step 103) are iterated until the estimated at least one physical property meets the user specification of the at least one physical property. Once the estimated physical properties meet the requirements, the model is updated according to the proposed modifications to the selected at least one portion and according to the proposed modifications to the rest of the model. In such an embodiment, the model is updated by filling the selected at least one portion of the model with beads of material representing the at least one portion, and filling the rest of the model representing the unit of material with beads of material representing the rest of the unit of material. In this embodiment, after identifying a design that meets the requirements (the proposed modifications to the selected at least one portion and the proposed modifications to the rest of the model, which modifications are reflected in the template), a single model is generated.

[0033] Figure 2 Steps of a method 220 for building a model of a porous microstructured material (e.g., an active material in a battery electrode or separator) are shown. Process 220 uses a bead-type simulation (mesoscale model or submodel), where each bead represents a group of atoms. According to an embodiment, the bead representation itself is implemented using standard programming techniques known to those skilled in the art of material modeling. In the overall model built by process 220, beads can be connected to simulate the solid portion of the material. Method 220 is iteratively performed until an overall model that meets user requirements (e.g., the user's desired physical properties of the material) is generated.

[0034] Method 220 utilizes model templates 222a, 222b, 222c, and 222n (generally referred to as 222). In an embodiment of method 220, the size of model template 222 is selected before starting the iterative process of method 220. In another embodiment, template 222 has a default size. According to an embodiment, template 222 is a three-dimensional (3D) repeating unit box representing a material. It should be noted that the template can be cubic or rectangular (e.g., a cuboid or a rectangular prism). Another embodiment also selects the step size of each iteration 221a-221n by selecting the number of new regions 223 before starting the iterative process to select each iteration 221a-221n.

[0035] Step 1 of the first iteration 221a begins by selecting new areas 223a-223c in the model template 222a to be filled with a specific material. Figure 2 In the first iteration 221a, the regions 223a-223c are selected. It should be noted that Figure 2 In the embodiment, the regions 223a-223c are depicted as spheres, but embodiments of the present invention are not limited thereto. The selected regions 223a-223c may be any closed volume, such as a cylinder, an ellipsoid, or a cube. It should also be noted that the size and position of the regions 223a-223c selected at step 1 may be randomly selected or may be based on user-selected settings or default settings.

[0036] If the selected area (e.g., area 223b) crosses the boundary of the template frame 222a, it is assumed that the selected area is reflected from the other side. In other words, method 220 applies periodic boundary condition rules. Therefore, if the selected area crosses the template boundary, the required number of copies are performed to ensure the continuity of the periodicity. For illustration, consider the area 223b that is partially located outside the template frame 222a. In operation, the template frame 222 is a repeating unit, and therefore any number of frames are combined (i.e., connected to each other) to represent the entire material and object being simulated. In order to ensure the continuity of the periodicity, each template frame is updated to reflect the selected area that crosses the boundary. Therefore, in this example illustration, the portion of the selected area 223b that is located outside the boundary of the template frame 222a is placed inside each adjacent frame that overlaps with the sphere (the selected area 223b). In this way, when the template boxes are connected to make a model of the entire object being simulated (e.g., a battery terminal having the material represented by the model created by the embodiment), the portion of region 223b that is outside of template box 222a is located inside of the template box adjacent to (connected to) box 222a.

[0037] Next, step 2 of iteration 221a is performed by using solid beads (e.g., Figure 2 The yellow area 225 in FIG. 2 is filled with solid material areas (which correspond to the selected template areas 223a-223c) to create a model 224a. It should be noted that Figure 2 The beads in are depicted as spherical, but embodiments are not limited thereto, and the beads may have different shapes. For example, in embodiments, the beads are elliptical. Additionally, during iteration 221a, solvent beads (e.g., Figure 2 The remaining portion of the model 224a (which corresponds to the volume of the cell 222a excluding the selected regions 223a-223c) is filled in with the purple region 226 shown in FIG. 221A . At this point (step 2 of iteration 221a ), the model 224a is now a complete representation of the material being modeled.

[0038] Process 220 may optionally include a step (step 2a) of cross-linking the beads according to a distance criterion. Such cross-linking creates continuous solid particles representing the solid active material.

[0039] Next (step 3 of iteration 221a), the physical properties (e.g., porosity) of the model 224a are calculated and compared to the requirements. If the physical properties meet the requirements, the process 220 ends, otherwise the process 220 is iterated until a model that meets the requirements is generated. The model that meets the requirements is stored, and the model can then be used in simulation to simulate the real-world use of the material represented by the model. Storing the model can include storing the following in a data structure in a computer memory: (a) the coordinates of each selected area 223, (b) an indication of the type of beads used to fill the model (e.g., adhesive, solid, fluid), (c) link information between beads, (d) an indication of the value representing the physical or chemical property, such as the porosity of the model, and (e) the template (box) size, as well as other examples.

[0040] like Figure 2 As depicted in FIG. 2 , after iteration 221a, process 220 includes iterations 221b-221n. In each iteration 221b-221n, a new region of template 222 is selected, for example, regions 223d-223f (and other regions). At step 2 of each iteration 221b-221n, the template 222 is selected by using solid beads (in Figure 2 Models 224b-224n are created by filling solid material regions of models 224b-224n (which correspond to the selected template regions) and using solvent beads ( Figure 2 221c) fills in the rest of the models 224b-224n. At this point (step 2) of iterations 221b-221n, the models 224a-224n are now complete representations of the material being modeled (the subject material). At step 3 of each iteration 221b-221n, the physical properties of the models 224b-224n are calculated and compared to the requirements. In iterations 221b and 221c, the corresponding models 224b and 224c do not meet the requirements, and the process 220 moves to the next iteration. However, in iteration 221n, the physical properties and chemical properties of the model 224n calculated thereafter meet the requirements, and the process 220 ends.

[0041] It should be noted that process 220 is described herein as iterating three steps: (step 1) selecting a region 223 of a model template 222; (step 2) creating or generating a model from the template by filling the model region corresponding to the selected template region with beads representing solid materials and filling the rest with beads representing fluids; and (step 3) calculating the physical and chemical properties of the created model, and determining whether the created model (and the current model behavior) meets the requirements. However, process 220 can be modified so that instead of creating a model (e.g., models 224a-224n) at each iteration, only the final model 224n is created and saved to computer memory. In such an alternative implementation, step 1 of each iteration selects a region of a model template. However, at step 2 of the alternative implementation, the physical properties of the proposed model (i.e., the model that has not yet been created) are estimated based on the template (e.g., cell 222a) and the selected template region (e.g., region 223a-223c). If the estimated physical properties meet the requirements, the iteration ends and the model is created or generated by filling the solid material area (which corresponds to the selected template area) with solid beads and filling the rest of the model (the volume of the model not including the corresponding selected template area) with beads representing fluid.

[0042] To illustrate, in method 220, templates (e.g., cells 222a-222n with their selected regions (generally referred to as 223) are all created, and properties of these templates are determined. The properties of the templates in iterations 221a-221c do not meet the requirements, and therefore models 224a-224c are not built. However, the templates in iteration 221n meet the requirements, and model 224n is created, as described herein.

[0043] Figure 3 Steps of an iterative method 330 for building a model of a porous microstructured material with a coating are shown. The method 330 can be used to simulate a material with a coating that mechanically binds particles, provides conductivity, and / or provides a solid electric interphase (i.e., the entire phase of the material). The process 330 uses a bead type simulation (mesoscale model or submodel), where each bead represents a group of atoms. In the model (e.g., 334a-334n) built by the process 330, beads can be connected to simulate the solid portion of the material. The method 330 is iteratively performed until a model that meets the user's requirements (e.g., the user's desired physical properties of the material represented by the model) is generated.

[0044] Method 330 utilizes model templates 332a, 332b, 332c, and 332n (generally referred to as 332). In an embodiment of method 330, the size of model template 332 is selected before starting the iterative process of method 330. In another embodiment, template 332 has a default size. In an embodiment, the template size is maintained for iterations 331a-331n. However, method 330 can be repeated using templates of different sizes. According to an embodiment, template 332 is a three-dimensional (3D) repeating unit box representing a material.

[0045] Step 1 of the first iteration 331a begins by selecting one or more new regions 333a-333c in the model template 332a to be filled with solid material. Figure 3 In FIG. 3 , regions 333a-333c are selected during the first iteration 331a. In addition to the selected regions 333a-333c, at step 1 of iteration 331a, additional regions 336a-336c (shown in green) are created that surround or wrap around the initially selected regions 333a-333c. The additional regions 336a-336c will contain the "coating" or second material type. It should be noted that in Figure 3 In the embodiment, the regions 333a-333c are depicted as spheres, but embodiments of the present invention are not limited thereto. The selected regions 333a-333c may be any closed volume, such as a cylinder, an ellipsoid, or a cube. It should also be noted that the size and position of the regions 333a-333c selected at step 1 of the iteration may be randomly selected or may be based on user selected settings or default settings.

[0046] If the selected area (e.g., area 333b) passes through the boundary of frame 332a, it is assumed that the selected area is reflected from the other side. In other words, method 330 applies periodic boundary condition rules. Therefore, if the selected area passes through the template boundary, the required number of copies is performed to ensure the continuity of periodicity. For illustration, consider extending to the area 333b outside the template frame 332a. In operation, the template frame 332 is a repeating unit, and therefore any number of frames are combined (i.e., connected to each other) to represent the entire material and object being simulated. In order to ensure the continuity of periodicity, each template frame is updated to reflect the selected area passing through the boundary. Therefore, in this example, the part of the selected area 333b located outside the boundary of the template frame 332a is placed inside each other template frame. In this way, when the template frame is connected to make a model of the entire object being simulated, the part of the area 333b located outside the frame 332a is located inside the template frame adjacent to (connected to) the frame 332a.

[0047] Next, (step 2 of iteration 331a of process 330) the precipitate is removed by first using solid beads (e.g., Figure 3 Model 334a is created by filling the solid material areas (which correspond to the selected areas 333a-333c) with yellow areas 335 in FIG. Next, the model areas corresponding to areas 336a-336c surrounding areas 333a-333c are filled with beads representing coatings. These coating beads are depicted in pink, for example, Figure 3 In this manner, in method 330, inner sphere 333a is filled first, and then the area between inner spheres 333a-333c and outer spheres 336a-336c is filled with beads representing the coating. Additionally, at step 2 of iteration 331a, solvent beads (e.g., Figure 3 338) to fill in the remainder of model 334a (which corresponds to the volume of template element 332a excluding the selected regions 333a-333c and the created coating regions 336a-336c). At this point (step 2), model 334a is now a complete representation of the subject material being modeled.

[0048] Process 330 may optionally include a step (step 2a) of cross-linking the beads according to a distance criterion. Such cross-linking creates continuous solid particles representing the solid active material.

[0049] Next (step 3 of iteration 331a), the properties (e.g., physical and / or chemical properties) of the model 334a are calculated and compared to the requirements. If the physical properties meet the requirements, process 330 ends, otherwise process 330 is iterated until a model that meets the requirements is generated. The model that meets the requirements is stored in a computer memory, and the model can then be used in a simulation to simulate the real-world use of the material represented by the model. Storing the model can include storing the following in a data structure in the computer memory: (a) the coordinates of each selected area 333, (b) a label of the type of beads used to fill the model (e.g., adhesive, solid, fluid), (c) link information between beads, (d) labels and / or measurements of physical or chemical properties, such as the porosity of the model, and (e) template (frame) size, as well as other examples.

[0050] like Figure 3 As depicted in FIG. 3 , after iteration 331a, process 330 performs iterations 331b-331n. In each iteration 331b-331n, a new region of template 332 (e.g., regions 333d-333f (and other regions)) is selected, and a region (e.g., regions 336d-336f (and other regions)) is created around the selected region. At step 2 of each iteration 331b-331n, the process 330 is performed by using solid beads (in Figure 3Models 334b-334n are created by filling the solid material regions (which correspond to the selected template regions) with beads representing the coating, and filling the model regions surrounding the selected regions (e.g., which correspond to regions 336d-336f) with beads representing the coating. Figure 3 331c) fills in the rest of the model 334. At this point (step 2) of iterations 331b-331n, models 334a-334n are now complete representations of the material being modeled. At step 3 of each iteration 331b-331n, the physical properties of models 334b-334n are calculated and compared to the requirements. In iterations 331b and 331c, models 334b ​​and 334c do not meet the requirements, and process 330 moves to the next iteration. However, in iteration 331n, the physical and chemical properties of model 334n meet the requirements, and process 330 ends.

[0051] It should be noted that process 330 is described herein as iterating three steps: (step 1) selecting an area 333 of a model template 332 and creating an area 336 around the selected area; (step 2) creating or generating a model by filling the model area corresponding to the selected template area with beads representing solid materials, filling the created coating area around the selected area with beads representing the coating, and filling the rest with beads representing the fluid; and (step 3) calculating the physical and chemical properties of the created model and determining whether the created model meets the requirements. However, process 330 can be modified so that a model (e.g., models 334a-334n) is not created at each iteration, but only the final model 334n is created and saved to computer memory. In such an alternative implementation, step 1 of each iteration selects an area of ​​the model template and creates an area around the selected area. However, at step 2 of this alternative implementation, physical properties of the proposed model (i.e., the model that has not yet been created) are estimated based on the template (e.g., cell 332a), the selected template region (e.g., regions 333a-333c), and the surrounding regions 336a-336c. In an embodiment, the template-based estimation is performed as described above. For example, the porosity is calculated by calculating the "volume surface" that separates one portion of the material from another portion, and the diffusion coefficient of the bead in the bulk fluid (D0) and the diffusion coefficient in the actual structure with porosity ∈ (D e) to obtain the curvature τ. In an embodiment, the template defines a certain amount of solid volume, for example, the solid volume is defined by the selected area, and the porosity and curvature are calculated by comparing the defined amount of solid volume with the total volume of the template. If the estimated properties (physical and / or chemical properties estimated using the template) meet the requirements, the iteration ends and the curvature is calculated by first using solid beads (for example, Figure 3 The first fills the solid material area (which corresponds to the selected template area) and the second fills the area corresponding to the created coating area surrounding the selected template area (e.g., Figure 3 ), and thirdly creating a model by filling the remainder of the model 334 (the volume of the model excluding the corresponding selected and created regions) with solvent beads.

[0052] To illustrate this alternative implementation, in method 330, templates (e.g., cells 332a-332n having their selected regions (e.g., generally 333) and created regions surrounding the selected regions (e.g., generally 336)) are all generated, and properties of these templates are determined. In iterations 331a-331c, the properties of template 332 do not meet the requirements, and therefore models 334a-334c are not built. However, in iteration 331n, template 332n having the selected regions and created regions (e.g., 333f and 336f) meets the requirements, and model 334n is created, as described herein.

[0053] Another embodiment of the present invention is directed to a computer-implemented process for creating a CAD model of a porous microstructure. Such an embodiment first identifies the desired porosity of the target porous microstructure material. Next, an empty 3D repeating cell of the material to be modeled is created within the CAD program, and a small portion of the empty repeating cell is selected. Then, the selected small portion of the empty repeating cell is filled with a model of a solid bead, and the rest of the repeating cell is filled with a model of a solvent bead. The porosity of the filled repeating cell is calculated, and the calculated porosity of the filled repeating cell is compared with the required porosity of the target porous microstructure material. The process is repeated until the desired porosity for the repeating cell is reached.

[0054] Figure 44 is a simplified block diagram of a computer-based system 440 that can be used to build a model of a subject material (or material of interest) according to any of the various embodiments of the present invention described herein. The system 440 includes a bus 443. The bus 443 serves as an interconnection between the various components of the system 440. An input / output device interface 446 is connected to the bus 443, and the input / output device interface 446 is used to connect various input and output devices such as keyboards, mice, touch screens, displays, speakers, etc. to the system 440. A central processing unit (CPU) 442 is connected to the bus 443 and provides execution of computer instructions. A memory 445 provides volatile storage of data for executing computer instructions. A storage device 444 provides non-volatile storage of software instructions such as an operating system (not shown). The system 440 also includes a network interface 441 for connecting to any of the various networks known in the art, including a wide area network (WAN) and a local area network (LAN).

[0055] It should be understood that the example embodiments described herein can be implemented in many different ways. In some instances, the various methods and machines described herein can each be implemented by a physical, virtual, or hybrid general-purpose computer (e.g., computer system 440) or a computer network environment (e.g., as described below in conjunction with Figure 5 The computer system 440 can be implemented by using the computer environment 550 described in the embodiment of the present invention. For example, by loading the software instructions implementing the method 100 into the memory 445 or the non-volatile storage device 444 for execution by the CPU 442, the computer system 440 can be converted into a machine for performing the methods described herein. It should be further understood by those of ordinary skill in the art that the system 440 and its various components can be configured to perform any embodiment or combination of embodiments of the present invention described herein. In addition, the system 440 can implement the various embodiments described herein using any combination of hardware, software, and firmware modules that are operably coupled internally or externally to the system 440.

[0056] Figure 5 A computer network environment 550 is shown in which embodiments of the present invention may be implemented. In the computer network environment 550, a server 551 is linked to clients 553a-553n via a communication network 552. The environment 550 may be used to allow the clients 553a-553n to perform any of the embodiments described herein, either alone or in combination with the server 551. For non-limiting examples, the computer network environment 550 provides a cloud computing environment, a software as a service (SAAS) embodiment, and the like.

[0057] Embodiments or aspects thereof may be implemented in the form of hardware, firmware, or software. If implemented in software, the software may be stored in any non-transitory computer-readable medium configured to enable a processor to load the software or a subset of its instructions. The processor then executes the instructions and is configured to operate the device or cause the device to operate in the manner described herein.

[0058] In addition, firmware, software, routines or instructions may be described herein as performing certain actions and / or functions of a data processor. However, it should be appreciated that such descriptions included herein are merely for convenience, and such actions are actually produced by a computing device, processor, controller, or other device that executes firmware, software, routines, instructions, etc.

[0059] It should be understood that flow charts, block diagrams, and network diagrams may include more or fewer elements, be arranged differently, or be represented differently. However, it should also be understood that certain implementations may specify that the block diagrams and network diagrams illustrating the execution of the embodiments and the number of block diagrams and network diagrams are implemented in a specific manner.

[0060] Therefore, further embodiments may also be implemented in various computer architectures, physical, virtual, cloud computing, and / or some combination thereof, and therefore, the data processors described herein are intended to be used for illustration purposes only and not for limitation of the embodiments.

[0061] While example embodiments have been particularly shown and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the embodiments covered by the appended claims.

Claims

1. A computer-implemented method for generating a model of a material, the method comprising: selecting at least one portion of the model of an element representing a material; estimating at least one physical property of the model based on the proposed modification to the selected at least one portion of the model and the proposed modification to the remaining portions of the model representing elements of the material, wherein the estimating comprises: Updating the model according to the proposed modification to the selected at least one portion and the proposed modification to the remaining portions of the model by: filling the selected at least one portion of the model with beads representing the material of the at least one portion; and filling the remainder of the model with beads representing the material of the remainder of the cells of the material; and estimating the at least one physical property by calculating the at least one physical property using the updated model; and iterating the selecting and estimating until the estimated at least one physical property meets a user specification of the at least one physical property, Each bead represents a group of atoms.

2. The method according to claim 1, wherein: The beads filling the at least one portion represent a solid.

3. The method according to claim 1, wherein: The beads filling the remainder represent a fluid.

4. The method according to claim 1, wherein: The at least one portion is comprised of a first closed volume and a second closed volume, the second closed volume enclosing the first closed volume, and wherein filling the selected at least one portion of the model with beads representing a material of the at least one portion comprises: filling the first closed volume with beads representing the material of the first closed volume; and The second closed volume is filled with beads representing the material of the second closed volume.

5. The method according to claim 4, wherein: The beads filling the second closed volume represent a coating surrounding the first closed volume.

6. A computer-implemented method for generating a model of a material, the method comprising: selecting at least one portion of the model of an element representing a material; estimating at least one physical property of the model using a template based on the proposed modification to the selected at least one portion of the model and the proposed modification to the remaining portions of the model representing elements of the material; iterating the selecting and estimating until the estimated at least one physical property meets a user specification of the at least one physical property; as well as After iteratively selecting and estimating until the estimated at least one physical property meets the user specification of the at least one physical property, updating the model according to the proposed modification to the selected at least one portion and the proposed modification to the remainder of the model by: filling the selected at least one portion of the model with beads representing the material of the at least one portion; as well as fill the rest of the model with beads of material representing the rest of the cell of that material, Each bead represents a group of atoms.

7. The method according to claim 1, wherein: The unit is a three-dimensional (3D) repeating unit.

8. The method according to claim 7, wherein: The 3D repeating unit is cubic or rectangular.

9. The method according to claim 1, wherein: The at least one portion is a closed volume.

10. The method according to claim 9, wherein: The closed volume is a sphere, a cylinder or an ellipsoid.

11. The method according to claim 1, wherein: The at least one physical property is at least one of: porosity and curvature.

12. A system for generating a model of a material, the system comprising: processor; as well as A memory having computer code instructions stored thereon, the processor and the memory being configured with the computer code instructions to cause the system to perform the following operations: selecting at least one portion of the model of an element representing a material; estimating at least one physical property of the model based on the proposed modification to the selected at least one portion of the model and the proposed modification to the remaining portions of the model representing elements of the material, wherein the estimating comprises: Updating the model according to the proposed modification to the selected at least one portion and the proposed modification to the remaining portions of the model by: filling the selected at least one portion of the model with beads representing the material of the at least one portion; and filling the remainder of the model with beads representing the material of the remainder of the cells of the material; and estimating the at least one physical property by calculating the at least one physical property using the updated model; and iterating the selecting and estimating until the estimated at least one physical property meets a user specification of the at least one physical property, Each bead represents a group of atoms.

13. The system according to claim 12, wherein: The beads filling the at least one portion represent a solid, and the beads filling the remaining portion represent a liquid or a gas.

14. The system according to claim 12, wherein: The at least one portion is comprised of a first closed volume and a second closed volume, the second closed volume enclosing the first closed volume, and wherein, to fill the selected at least one portion of the model with beads representing a material of the at least one portion, the processor and the memory are further configured with the computer code instructions to cause the system to: filling the first closed volume with beads representing the material of the first closed volume; and The second closed volume is filled with beads representing the material of the second closed volume.

15. The system of claim 14, wherein: The beads filling the second closed volume represent a coating surrounding the first closed volume.

16. A system for generating a model of a material, the system comprising: processor; as well as a memory having computer code instructions stored thereon, the processor and the memory being configured with the computer code instructions to cause the system to: selecting at least one portion of the model of an element representing a material; estimating at least one physical property of the model using a template based on the proposed modification to the selected at least one portion of the model and the proposed modification to the remaining portions of the model representing elements of the material; iterating the selecting and estimating until the estimated at least one physical property meets a user specification of the at least one physical property; as well as After iteratively selecting and estimating until the estimated at least one physical property meets the user specification of the at least one physical property, updating the model according to the proposed modification to the selected at least one portion and the proposed modification to the remainder of the model by: filling the selected at least one portion of the model with beads representing the material of the at least one portion; as well as fill the rest of the model with beads of material representing the rest of the cell of that material, Each bead represents a group of atoms.

17. The system of claim 12, wherein: The at least one physical property is at least one of: porosity and curvature.

18. A non-transitory computer program product for generating a model of a material, the computer program product being executed by a server in communication with one or more clients across a network, and comprising: A computer readable medium comprising program instructions which, when executed by a processor, cause the processor to perform the following operations: selecting at least one portion of the model of an element representing a material; estimating at least one physical property of the model based on the proposed modification to the selected at least one portion of the model and the proposed modification to the remaining portions of the model representing elements of the material, wherein the estimating comprises: Updating the model according to the proposed modification to the selected at least one portion and the proposed modification to the remaining portions of the model by: filling the selected at least one portion of the model with beads representing the material of the at least one portion; and filling the remainder of the model with beads representing the material of the remainder of the cells of the material; and estimating the at least one physical property by calculating the at least one physical property using the updated model; and iterating the selecting and estimating until the estimated at least one physical property meets a user specification of the at least one physical property, Each bead represents a group of atoms.

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