Gradient polycrystalline structure generation method and device, electronic equipment and storage medium

Abstract

The invention relates to the field of material structures, and discloses a gradient polycrystalline structure generation method, a gradient polycrystalline structure generation device, electronic equipment and a computer readable storage medium. The gradient polycrystalline structure generation method comprises the steps that a plurality of node coordinates are generated based on a set distribution function, and the node density of nodes corresponding to the node coordinates is in gradient change in the set direction; and generating an interlocking twin crystal structure at each node based on an interlocking twin crystal model, wherein all the interlocking twin crystal structures form the gradient polycrystalline structure. According to the gradient polycrystalline structure generation method, the gradient polycrystalline structure generation device, the electronic equipment and the computer readable storage medium provided by the invention, the technical problems that in the prior art, the construction process of a gradient polycrystalline structure model with an interlocking twin structure is complex, and the correlation between gradient distribution and actual requirements is low are solved.

Description

Technical Field

[0001] The present application relates to the field of material structure, and specifically to a gradient polycrystalline structure generation method, a gradient polycrystalline structure generation device, an electronic device and a computer-readable storage medium. Background Art

[0002] Interlocked twin structures are three-dimensional microscopic networks formed by the intersecting or nesting of multiple twin boundaries. They demonstrate unique scientific value and engineering application potential in improving the comprehensive properties of crystalline materials and have become a cutting-edge direction in materials design and performance optimization. While conventional single twins can enhance strength by hindering dislocation slip, they are prone to brittle fracture. Interlocked twins can form multiple dislocation barriers with intersecting twin boundaries, significantly improving yield strength and fatigue resistance. Furthermore, nested twins inhibit crack propagation through crack deflection and energy dissipation, preventing catastrophic fracture. Interlocked twin structures exhibit exceptional thermal, radiation, and chemical stability in high-temperature, irradiated, or corrosive environments. On the one hand, the high density of twin boundaries pins grain boundary migration, inhibiting grain coarsening at high temperatures; on the other hand, the twin interfaces act as defect traps, absorbing vacancies and interstitial atoms and slowing radiation swelling; and on the other hand, the dense twin network reduces local electrochemical differences, slowing the corrosion rate.

[0003] Gradient polycrystalline structures refer to polycrystalline materials whose microstructural characteristics, such as grain size, orientation, crystal structure, or chemical composition, exhibit continuous or stepped gradients along a specific direction. Their core characteristic is that this microstructural heterogeneity allows the material to exhibit differentiated properties (such as strength, toughness, and conductivity) in different regions, thereby meeting multifunctional requirements under complex operating conditions.

[0004] To further investigate materials combining interlocking twin structures with gradient polycrystalline structures, constructing a structural model of gradient polycrystalline materials with interlocking twin structures is a prerequisite and foundation for conducting various studies. However, the process of constructing a gradient polycrystalline structural model with interlocking twin structures in related existing technologies is relatively complex, and the gradient distribution has a low relevance to actual needs. Summary of the Invention

[0005] In view of this, it is necessary to provide a gradient polycrystalline structure generation method, device, electronic device and storage medium to solve the technical problems existing in the prior art, such as the complex construction process of the gradient polycrystalline structure model with interlocking twin structure and the low correlation between the gradient distribution and actual needs.

[0006] In order to solve the above technical problems, in the first aspect, the present application provides a method for generating a gradient polycrystalline structure, including: generating multiple node coordinates based on a set distribution function, and the node density of the nodes corresponding to the multiple node coordinates changes gradiently along a set direction; generating an interlocking twin structure at each of the nodes based on an interlocking twin model, and all the interlocking twin structures constitute the gradient polycrystalline structure.

[0007] In a possible embodiment, the interlocking twin structure is generated at each node based on the interlocking twin model, including: obtaining the size data and the number of substructures of the interlocking twin structure, the substructure is composed of multiple grains, a first twin boundary is formed between adjacent grains, and a second twin boundary is formed between adjacent substructures; determining the subnode coordinates based on the size data and the number of substructures; generating the substructure at each subnode coordinate based on the substructure model; generating multiple first rotation angles, each substructure corresponds to a unique first rotation angle, and rotating each substructure to its corresponding first rotation angle.

[0008] In a possible embodiment, the determining of sub-node coordinates based on the dimension data and the number of substructures includes: when the second twin boundary is a non-coherent twin, obtaining a preset displacement; dividing the interlocking twin structure into the number of substructure spaces along the stacking direction of the substructure, determining the center point of each of the substructure spaces, and determining the center point coordinates of each of the center points according to the dimension data; the substructure includes a first-class substructure and a second-class substructure, and the center point coordinates of the first-class substructure are used as the sub-node coordinates of the first-class substructure, and the center point of the second-class substructure is moved by a preset displacement along the arrangement direction of the grains to obtain a target sub-node of the second-class substructure, and the coordinates of the target sub-node are used as the sub-node coordinates of the second-class substructure.

[0009] In a possible embodiment, generating a plurality of first rotation angles includes: calculating the first rotation angles according to preset crystal plane indices of any two adjacent second twin boundaries.

[0010] In a possible embodiment, the method further includes: generating a plurality of second rotation angles, each of the interlocking twin structures corresponding to a unique second rotation angle; and rotating each of the interlocking twin structures to its corresponding second rotation angle.

[0011] In a possible embodiment, generating a plurality of second rotation angles includes: randomly generating the second rotation angles based on a random function.

[0012] In a possible embodiment, the method further includes: constructing a potential function based on the material of the gradient polycrystalline structure; and relaxing the gradient polycrystalline structure based on the potential function.

[0013] In the second aspect, the present application also provides a gradient polycrystalline structure generation device, including: a node determination module, the node determination module is used to generate multiple node coordinates based on a set distribution function, and the node density of the nodes corresponding to the multiple node coordinates changes gradiently along the set direction; a polycrystalline structure generation module, the polycrystalline structure generation module is used to generate an interlocking twin structure at each of the nodes based on an interlocking twin model, and all the interlocking twin structures constitute the gradient polycrystalline structure.

[0014] In a third aspect, the present application also provides an electronic device comprising a memory and a processor, wherein the memory is used to store programs; the processor is coupled to the memory and is used to execute the programs stored in the memory to implement the steps in the aforementioned gradient polycrystalline structure generation method.

[0015] In a fourth aspect, the present application also provides a computer-readable storage medium for storing computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the aforementioned gradient polycrystalline structure generation method.

[0016] Beneficial effects of this application: Compared with the related art, in the gradient polycrystalline structure generation method provided in the embodiment of the present application, multiple node coordinates are generated directly based on the distribution function, and each node coordinate corresponds to a node. Subsequently, an interlocking twin structure is generated at each node based on the interlocking twin model. Since the node density of the multiple nodes generated by the distribution function changes gradiently along the set direction, the polycrystalline structure composed of multiple interlocking twin structures generated by the nodes based on the gradient distribution is a gradient polycrystalline structure; the nodes that generate the gradient distribution based on the distribution function only need to configure the relevant function parameters of the distribution function. The construction process of the gradient polycrystalline structure model is relatively simple, and the gradient distribution can be set by customizing the distribution function, so that the gradient distribution of the gradient polycrystalline structure is more relevant to actual needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A schematic flow chart of a method for generating a gradient polycrystalline structure provided in one embodiment of the present application; Figure 2 A schematic diagram of a process for generating an interlocking twin structure in a gradient polycrystalline structure generation method provided in one embodiment of the present application; Figure 3 A schematic structural diagram of an interlocking twin structure provided in one embodiment of the present application; Figure 4 A schematic structural diagram of a substructure in an interlocking twin structure provided in one embodiment of the present application; Figure 5 A schematic structural diagram of a crystal cell model in an interlocking twin structure provided in one embodiment of the present application; Figure 6 A schematic flow chart of a method for generating a gradient polycrystalline structure provided in another embodiment of the present application; Figure 7 A schematic flow chart of a method for generating a gradient polycrystalline structure provided in another embodiment of the present application; Figure 8 A schematic structural diagram of a device for generating a gradient polycrystalline structure according to an embodiment of the present application; Figure 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0020] In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more. "And / or" describes the association relationship between associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone.

[0021] The terms "first," "second," and so on, used in the embodiments of this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, technical features designated as "first" or "second" may explicitly or implicitly include at least one such feature.

[0022] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0023] The present application provides a gradient polycrystalline structure generation method, a gradient polycrystalline structure generation device, an electronic device and a computer-readable storage medium, which are described below respectively.

[0024] Please refer to Figure 1 , the embodiment of the present application provides a method for generating a gradient polycrystalline structure, comprising the following steps: Step S101: generating a plurality of node coordinates based on a set distribution function, wherein the node density of the nodes corresponding to the plurality of node coordinates changes gradiently along a set direction.

[0025] Step S102: generating an interlocking twin structure at each node based on the interlocking twin model, and all the interlocking twin structures constitute a gradient polycrystalline structure.

[0026] Compared with the related art, in the gradient polycrystalline structure generation method provided in this embodiment, multiple node coordinates are generated directly based on the distribution function, and each node coordinate corresponds to a node. Subsequently, an interlocking twin structure is generated at each node based on the interlocking twin model. Since the node density of the multiple nodes generated by the distribution function changes gradiently along the set direction, the polycrystalline structure composed of multiple interlocking twin structures generated by the nodes based on the gradient distribution is a gradient polycrystalline structure; the nodes that generate the gradient distribution based on the distribution function only need to configure the relevant function parameters of the distribution function. The construction process of the gradient polycrystalline structure model is relatively simple, and the gradient distribution can be set by customizing the distribution function, so that the gradient distribution of the gradient polycrystalline structure is more relevant to actual needs.

[0027] In step S101, the distribution function may be np.random.normal (Gaussian distribution), np.random.exponential (exponential distribution), np.random.poisson (Poisson distribution), np.random.binomial (binomial distribution), numpy.random.randn (normal distribution), or a custom distribution function using the np.random.choice command. Based on this, generating multiple node coordinates based on the set distribution function may be performed by calling the aforementioned distribution function in Python using the np.random module to generate the multiple node coordinates.

[0028] Furthermore, in an embodiment of the present application, when generating node coordinates, the degree of node gradient change can be controlled by adjusting the characteristics of the set distribution function. For example, when the distribution function is set to np.random.normal (Gaussian distribution), the degree of node gradient change can be controlled by adjusting parameters such as the mean (loc) and standard deviation (scale) of the distribution function; when the distribution function is set to np.random.exponential (exponential distribution), the degree of node gradient change can be controlled by adjusting parameters such as the rate of exponential change (scale) of the distribution function; when the distribution function is set to np.random.poisson (Poisson distribution), the degree of node gradient change can be controlled by adjusting parameters such as the probability of occurrence (lam) of the distribution function; when the distribution function is set to np.random.binomial (binomial distribution), the degree of node gradient change can be controlled by adjusting parameters such as the total number of times the distribution function occurs (n) and the probability of occurrence (p); when the distribution function is set to numpy.random.randn (normal distribution), the degree of node gradient change can be controlled by adjusting parameters such as the mean (loc) and standard deviation (scale) of the distribution function.

[0029] In step S102, the interlocking twin model is specifically a set generation method of the interlocking twin structure. Combined with the relevant parameters of the interlocking twin structure to be constructed, the generation method set by the interlocking twin model can complete the generation of the interlocking twin structure.

[0030] In some embodiments of the present application, the interlocking twin model can be a pre-set interlocking twin model stored in a gradient polycrystalline structure generation device. When generating an interlocking twin structure at each node based on the interlocking twin model in step S102, the stored interlocking twin model is directly called to generate the interlocking twin structure.

[0031] Or in some embodiments of this application, please refer to Figure 2 In step S102, the interlocking twin structure is generated at each node based on the interlocking twin model, and specifically, the interlocking twin structure can be generated as follows: Step S201: Acquire the dimension data and the number of substructures of the interlocking twin structure.

[0032] In this step, refer to Figure 3 、 Figure 4The interlocking twin structure 100 includes a plurality of substructures 200, with second twin boundaries 300 formed between adjacent substructures 200. Each substructure 200 includes a plurality of grains 400, with first twin boundaries 500 formed between adjacent grains 400. Each grain is composed of a plurality of atoms 600. The first twin boundaries 500 and the second twin boundaries 300 intersect with each other to form an interlocking twin structure.

[0033] The size data of the interlocking twin structure is specifically the boundary size data of the interlocking twin structure, such as Figure 3 As shown, the dimensional data may specifically include the boundary length l, width d, and height h of the interlocking twin structure.

[0034] Furthermore, in the embodiments of the present application, second twin boundaries 300 are formed between adjacent substructures 200. The greater the number of superimposed substructures 200, the greater the number of second twin boundaries 300 formed. Based on this, the number of second twin boundaries 300 in the gradient polycrystalline structure can be determined based on modeling requirements, and the number of substructures can then be determined based on the number of second twin boundaries 300.

[0035] Step S202: Determine the coordinates of the child nodes based on the size data and the number of child structures.

[0036] In this step, the subnode coordinates can be determined in a corresponding manner according to the twin type of the second twin boundary 300. For example, when the second twin boundary 300 is a coherent twin, the interlocking twin structure is evenly divided into substructure spaces of the number of substructures along the stacking direction of the multiple substructures in the interlocking twin structure, and the center point coordinates of each substructure space are determined as the subnode coordinates of the substructure. Taking the size data of length l, width d, height h, the number of substructures is N, and N substructures are stacked along the height h direction as an example, the interlocking twin structure is evenly divided into N substructure spaces along the height h direction, and the subnode coordinates of the nth substructure are (0.5*l, d / 2, (2n-1) / 2N*c), where n is the order of the multiple substructures in the interlocking twin structure along the stacking direction.

[0037] For another example, when the second twin boundary 300 is an incoherent twin, some substructures must be slightly displaced along the grain arrangement direction. In this embodiment, the substructures that are not displaced are considered as Class I substructures, and the substructures that are displaced are considered as Class II substructures. Still taking the dimension data of length l, width d, and height h, and the number of substructures N as an example, for Class II substructures, the center point of the Class II substructure is moved along the grain arrangement direction by a preset displacement amount to obtain a target subnode of the Class II substructure, and the coordinates of the target subnode are used as the subnode coordinates of the Class II substructure, that is, the subnode coordinates corresponding to the Class II substructure are (0.5*l±x, d / 2, (2n-1) / 2N*c); for Class I substructures, its subnode coordinates are also (0.5*l, d / 2, (2n-1) / 2N*c).

[0038] Step S203: generating a substructure at each subnode coordinate based on the substructure model.

[0039] In this step, refer to Figure 5 Specifically, a crystal cell model composed of multiple atoms 600 can be constructed, and then a cell widening operation can be performed on the crystal cell model in the grain area 700, that is, the crystal model is simultaneously copied several times along the three-dimensional axis until the entire grain area 700 is filled to form a grain 400.

[0040] After the crystal model fills the entire grain region 700 , atoms escaping from the grain region 700 may be removed, thereby confining the grains 400 within the grain region 700 and preventing the atoms escaping from the grain region 700 from subsequently forming additional grain boundaries.

[0041] Please refer to Figure 4 After the grain 400 is constructed, the grain 400 can be mirrored to form a mirror grain, and further multiple grains can be merged into a substructure according to the structure of "grain-mirror grain-grain-mirror grain-grain..."

[0042] After synthesizing the substructure, it is also possible to delete atoms whose atomic distance is less than a distance threshold, thereby removing duplicate atoms during the merging process.

[0043] Generating a substructure at the subnode coordinates specifically means that the coordinates of the center point of the substructure generated based on the above method are the subnode coordinates.

[0044] Step S204: Generate multiple first rotation angles, each substructure corresponds to a unique first rotation angle, and rotate each substructure by its corresponding first rotation angle.

[0045] In this step, the first rotation angle can be calculated based on the preset crystal plane index of any two adjacent second twin boundaries. The preset crystal plane index can be a crystal plane index set in advance according to actual needs, and the angle between the two adjacent second twin boundaries can be calculated based on the preset crystal plane index of the two adjacent second twin boundaries. , the first rotation angle is .

[0046] Further, calculate the angle Specifically, the angle calculation formula can be determined based on the crystal system of the gradient polycrystalline structure, and the angle angle can be calculated based on the angle calculation formula and the preset crystal plane index of the two adjacent second twin boundaries. .

[0047] For example, the crystal system of the gradient polycrystalline structure is a cubic system, and the preset crystal plane indices of the two adjacent second twin boundaries are (h1, k1, l1) and (h2, k2, l2), respectively. The angle calculation formula is: ; The crystal system of the gradient polycrystalline structure is the orthorhombic system, the lattice constants are a, b, c, and the preset crystal plane indices of the two adjacent second twin boundaries are (h1, k1, l1) and (h2, k2, l2), respectively. The angle calculation formula is: ; The crystal system of the gradient polycrystalline structure is the tetragonal system, the lattice constants are a, a, c, and the preset crystal plane indices of the two adjacent second twin boundaries are (h1, k1, l1) and (h2, k2, l2), respectively. The angle calculation formula is: ; The crystal system of the gradient polycrystalline structure is hexagonal, the lattice constants are a, a, c, and the preset crystal plane indices of the two adjacent second twin boundaries are (h1, k1, l1) and (h2, k2, l2), respectively. The angle calculation formula is: .

[0048] Please refer to Figure 6 The method for generating a gradient polycrystalline structure provided in the embodiment of the present application may further include: Step S103: generating a plurality of second rotation angles, wherein each interlocking twin structure corresponds to a unique second rotation angle.

[0049] In this step, the second rotation angle may be a randomly generated angle, for example, a rotation angle randomly generated by a random command.

[0050] Step S104: rotating each interlocking twin structure by its corresponding second rotation angle.

[0051] Please refer to Figure 7 The method for generating a gradient polycrystalline structure provided in the embodiment of the present application may further include: Step S105: constructing a potential function based on the material of the gradient polycrystalline structure.

[0052] In this step, if the gradient polycrystalline structure is made of a covalently bonded material, the interactions between the covalently bonded atoms are described using the Tersoff multi-body potential function. If the gradient polycrystalline structure is made of a metal, the interactions within the metal are described using the EAM potential.

[0053] The expression of Tersoff multi-body potential function is as follows:

[0054] in, is the total energy of the system, is the binding energy of the i-th atom, Decomposed into bond energy The sum of , where i and j represent the atomic pairs in the system, is the distance between atoms i and j, function is a truncation function, which is used to limit the effective range of potential. and represent the repulsive and attractive potentials, respectively. is the bond angle function, defines the effective coordination number of atom i, is the angle between key ij and key ik, and is the fitting parameter value, R and D are the cutoff radius parameters, A 、 B 、 、 and are the two-body potential parameters, 、 , c, d and m are the three-body potential parameters.

[0055] The expression of the EAM potential function is as follows:

[0056] in, is the electron density of a single atom, is the two-body interaction potential between atoms, is the multi-body interaction potential, 、 、 and is the basic potential parameter.

[0057] For example, the basic potential parameters in the EAM potential of aluminum =33.232 nm -1 、 =14.859 nm -1 、 =0.21176nm, =3.7760 eV.

[0058] The parameter values ​​in the Tersoff many-body potential function of diamond are as follows:

[0059] Step S106: Relaxing the gradient polycrystalline structure based on the potential function.

[0060] "Relaxation" is a concept widely used in physics, chemistry, biology, engineering and other fields. Its core meaning is the process of a system gradually recovering from a non-equilibrium state to an equilibrium state.

[0061] In this step, the relaxed gradient polycrystalline structure can be specifically achieved by using the Velocity command in the LAMMPS software to give all atoms in the system a random initial velocity, then using the Minimize command to perform an energy minimization operation on the system, and then using the isothermal and isobaric NPT ensemble to release the stress within the system. Finally, the entire system will gradually converge to a stable size, and a relaxed gradient polycrystalline model will be obtained.

[0062] Taking the construction of a gradient diamond model with an interlocking twin structure as an example, the following steps may be specifically included: S1: Construct a basic diamond model. Use the create command in the atomsk software to construct a diamond unit cell with the lattice type set to diamond, lattice parameters set to 3.567, atomic species set to C, and crystal orientations set to X = [1-11], Y =

[110] , and Z = [-112]. Use the duplicate command to duplicate this unit cell to form a 3×3×4 supercell. Then, shift all atoms in the supercell by 0.6 in the X, Y, and Z directions, and export the result to C_unit1.xsf.

[0063] S2: Construct a diamond basic twin model. Use the mirror command in the atomsk software to apply a mirror plane along the X-axis at a distance of 0 to obtain a diamond mirror model. Then use the merge command to merge the five models along the X-axis in the "base model - mirror model - base model - mirror model - base model" mode and output them to C_twin.xsf.

[0064] S3: Construct the diamond interlocking twin model. First, create the polycrystalline seed file (polyX.txt) for the interlocking twin model. Then, use the C_twin.xsf file from step 2 as the node file. This rotates twin boundary 1 in the basic twin model by 15° or -15° and stacks it four times along the z-axis to form the diamond interlocking twin model (final.xsf). At this point, the angle between the first and second twin boundaries is 75°.

[0065] The contents of Poly.txt are as follows: box 100 100 100 (dimension data of the substructure) node 0.5*box 0 0.125*box (child node coordinates) 0° -15° 0° (first rotation angle) node 0.5*box 0 0.375*box (child node coordinates) 0° 15° 0° (first rotation angle) node 0.5*box 0 0.625*box (child node coordinates) 0° -15° 0° (first rotation angle) node 0.5*box 0 0.875*box (child node coordinates) 0° 15° 0° (first rotation angle).

[0066] S4: Use Python to construct a gradient polycrystalline seed file. Set the dimensions of the interlocking twin structure to 200 × 200 × 400, select the function type as linear, and set the slope to 0.6 to obtain the polycrystalline seed file grain.txt. The main Python program code is as follows: #Linear distribution distribution_config = { 'type': 'linear', 'params': {'linear': {'slope': 0.6, 'reverse': False}} def generate_distribution(config): dist_type = config['type'] params = config['params'].get(dist_type, {}) if dist_type == 'linear': slope = np.clip(params.get('slope', 0.5), 0.01, 0.99) base = np.random.rand(num_points) z = z_size * (base ** (1 / (slope+1e-8))) if params.get('reverse', False): z = z_size - z else: raise ValueError("Unsupported distribution type") return np.clip(z, 0, z_size) #Generate coordinates num_points = 15 np.random.seed(20) z = generate_distribution(distribution_config) x = np.random.uniform(0, x_size, num_points) y = np.random.uniform(0, y_size, num_points) #Export file with open('3d_points_custom_size.txt', 'w') as f: for i in range(num_points): f.write(f"node {x[i]:.6f} {y[i]:.6f} {z[i]:.6f} random\n") The generated grain.txt is as follows: Box 200 200 400 (Dimensional data for interlocking twin structure) node 7.332861 135.882224 329.036043 (node ​​coordinates) random (second rotation angle) node 23.338747 130.157183 217.601615 (node ​​coordinates) random (second rotation angle) node 150.256140 53.759048 222.296931 (node ​​coordinates) random (second rotation angle) node 47.843643 13.464933 264.645069 (node ​​coordinates) random (second rotation angle) node 50.961203 154.289028 397.076044 (node ​​coordinates) random (second rotation angle) node 171.525106 96.196826 305.850501 (node ​​coordinates) random (second rotation angle) node 189.955805 65.841282 361.927156 (node ​​coordinates) random (second rotation angle) node 112.337372 102.128211 341.530258 (node ​​coordinates) random (second rotation angle) node 35.756104 52.725766 314.175789 (node ​​coordinates) random (second rotation angle) node 154.050387 62.102310 382.761142 (node ​​coordinates) random (second rotation angle) node 98.476208 125.370688 374.568885 (node ​​coordinates) random (second rotation angle) node 126.250613 111.489962 298.560062 (node ​​coordinates) random (second rotation angle) node 167.899585 63.715912 277.770035 (node ​​coordinates) random (second rotation angle) node 92.207879 78.968644 248.055469 (node ​​coordinates) random (second rotation angle) node 99.588015 51.594917 280.580489 (node ​​coordinates) random (second rotation angle).

[0067] S5: Construct a gradient polycrystalline diamond model with interlocking twins. Use the polycrystal command in the Atomsk software, using grain.txt as the seed file and final.xsf as the node file, to construct a gradient polycrystalline diamond model with interlocking twins and write it to the poly.lmp file.

[0068] Please refer to Figure 8 , the present application also provides a gradient polycrystalline structure generation device, comprising: The node determination module 801 is used to generate a plurality of node coordinates based on a set distribution function, wherein the node density of the nodes corresponding to the plurality of node coordinates changes gradiently along a set direction; The polycrystalline structure generating module 802 is used to generate an interlocking twin structure at each node based on the interlocking twin model, and all the interlocking twin structures constitute a gradient polycrystalline structure.

[0069] Please refer to Figure 9 The present application also provides an electronic device 900. The electronic device 900 includes a processor 901, a memory 902, and a display 903. Figure 9 Only some of the components of the electronic device 900 are shown, but it should be understood that implementation of all of the shown components is not required, and more or fewer components may be implemented instead.

[0070] In some embodiments, the processor 901 may be a central processing unit (CPU), a microprocessor, or other data processing chip, configured to execute program codes or process data stored in the memory 902 , such as the gradient polycrystalline structure generation method in the present application.

[0071] In some embodiments, processor 901 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, processor 901 may be local or remote. In some embodiments, processor 901 may be implemented on a cloud platform. In one embodiment, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an on-premises cloud, a multi-cloud, or any combination thereof.

[0072] In some embodiments, the memory 902 may be an internal storage unit of the electronic device 900, such as a hard disk or memory of the electronic device 900. In other embodiments, the memory 902 may also be an external storage device of the electronic device 900, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 900.

[0073] Furthermore, the memory 902 may include both an internal storage unit of the electronic device 900 and an external storage device. The memory 902 is used to store application software installed in the electronic device 900 and various data.

[0074] In some embodiments, the display 903 can be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display 903 is used to display information on the electronic device 900 and to display a visual user interface. Components 901-903 of the electronic device 900 communicate with each other via a system bus.

[0075] In one embodiment, when the processor 901 executes the gradient polycrystalline structure generation program in the memory 902, the following steps may be implemented: Generate multiple node coordinates based on a set distribution function, and the node density of the nodes corresponding to the multiple node coordinates changes gradiently along the set direction; Based on the interlocking twin model, an interlocking twin structure is generated at each node, and all the interlocking twin structures constitute a gradient polycrystalline structure.

[0076] It should be understood that, when the processor 901 executes the gradient polycrystalline structure generation program in the memory 902 , in addition to the above functions, it can also implement other functions. For details, please refer to the description of the corresponding method embodiment above.

[0077] Furthermore, the embodiment of the present application does not specifically limit the type of the electronic device 900 mentioned. The electronic device 900 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, or the like. Exemplary embodiments of portable electronic devices include but are not limited to portable electronic devices equipped with IOS, Android, Microsoft, or other operating systems. The above-mentioned portable electronic devices may also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present application, the electronic device 900 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0078] Accordingly, an embodiment of the present application also provides a computer-readable storage medium, which is used to store computer-readable programs or instructions. When the program or instructions are executed by a processor, the steps or functions in the gradient polycrystalline structure generation method provided in the above-mentioned method embodiments can be implemented.

[0079] Those skilled in the art will appreciate that all or part of the process flow of the above-described method embodiment can be implemented by instructing related hardware (such as a processor, controller, etc.) through a computer program, and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a magnetic disk, an optical disk, a read-only memory, or a random access memory.

[0080] The above is a detailed introduction to the gradient polycrystalline structure generation method, gradient polycrystalline structure generation device, electronic device and computer-readable storage medium provided by the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for generating a gradient polycrystalline structure, characterized in that: include: Generate a plurality of node coordinates based on a set distribution function, wherein the node density of the nodes corresponding to the plurality of node coordinates changes gradiently along a set direction; An interlocking twin structure is generated at each of the nodes based on an interlocking twin model, and all of the interlocking twin structures constitute the gradient polycrystalline structure.

2. The method for generating a gradient polycrystalline structure according to claim 1, wherein: The generating of an interlocking twin structure at each node based on an interlocking twin model comprises: Acquiring size data and the number of substructures of the interlocking twin structure, wherein the substructure is composed of a plurality of grains, a first twin boundary is formed between adjacent grains, and a second twin boundary is formed between adjacent substructures; determining child node coordinates based on the size data and the number of child structures; generating the substructure at each of the subnode coordinates based on the substructure model; A plurality of first rotation angles are generated, each substructure corresponds to a unique first rotation angle, and each substructure is rotated by the corresponding first rotation angle.

3. The method for generating a gradient polycrystalline structure according to claim 2, wherein: The determining of the subnode coordinates based on the size data and the number of substructures includes: When the second twin boundary is an incoherent twin, obtaining a preset displacement; Dividing the interlocking twin structure into substructure spaces equal to the number of the substructures along the stacking direction of the substructures, determining the center point of each of the substructure spaces, and determining the center point coordinates of each of the center points according to the size data; The substructure includes a first-class substructure and a second-class substructure. The center point coordinates of the first-class substructure are used as the subnode coordinates of the first-class substructure. The center point of the second-class substructure is moved by a preset displacement along the arrangement direction of the grains to obtain the target subnode of the second-class substructure. The coordinates of the target subnode are used as the subnode coordinates of the second-class substructure.

4. The method for generating a gradient polycrystalline structure according to claim 2, wherein: Generating a plurality of first rotation angles includes: The first rotation angle is calculated based on preset crystal plane indices of any two adjacent second twin boundaries.

5. The method for generating a gradient polycrystalline structure according to claim 1, wherein: Also includes: generating a plurality of second rotation angles, each of the interlocking twin structures corresponding to a unique second rotation angle; Each of the interlocking twin structures is rotated by its corresponding second rotation angle.

6. The method for generating a gradient polycrystalline structure according to claim 5, wherein: Generating a plurality of second rotation angles includes: The second rotation angle is randomly generated based on a random function.

7. The method for generating a gradient polycrystalline structure according to any one of claims 1 to 6, characterized in that: Also includes: Constructing a potential function based on the material of the gradient polycrystalline structure; The gradient polycrystalline structure is relaxed based on the potential function.

8. A gradient polycrystalline structure generating device, characterized in that: include: A node determination module, configured to generate a plurality of node coordinates based on a set distribution function, wherein the node density of the nodes corresponding to the plurality of node coordinates varies gradiently along a set direction; A polycrystalline structure generation module is used to generate an interlocking twin structure at each node based on an interlocking twin model, and all of the interlocking twin structures constitute the gradient polycrystalline structure.

9. An electronic device, characterized in that: comprising a memory and a processor, wherein, The memory is used to store programs; The processor is coupled to the memory and is configured to execute the program stored in the memory to implement the steps of the method for generating a gradient polycrystalline structure as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the gradient polycrystalline structure generation method according to any one of claims 1 to 7.

Images