Method, device, medium and equipment for calculating curie temperature of multi-component magnetic alloy

Abstract

The application provides a Curie temperature calculation method, device, medium and equipment of a multi-component magnetic alloy, which comprises the following steps: defining alloy components to be calculated, and generating input files required by an EMTO calculation program based on preset calculation parameters; traversing each alloy component, and generating corresponding KGRN and KFCD input files in combination with preset crystal structure types and magnetic configuration configurations; calling the EMTO calculation program, performing a calculation task in batches based on the input files, including sequentially performing KGRN and KFCD tasks; automatically extracting state equation data based on the output results of the calculation task; performing batch fitting based on the extracted state equation data to predict ferromagnetic state ground state total energy and paramagnetic state ground state total energy; and calculating the Curie temperature by using an average field theory formula based on the ferromagnetic state ground state total energy and the paramagnetic state ground state total energy obtained by fitting. The method greatly reduces the time component of experimental trial and error and saves the cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Curie temperature calculation of magnetic materials, and in particular to a Curie temperature calculation method, device, medium and equipment for multi-component magnetic alloys. BACKGROUND

[0002] Multi-component soft magnetic alloys have broad application prospects in the fields of power electronics, electric transportation and advanced functional devices due to their excellent comprehensive performance. For example, soft magnetic materials used in rotating equipment such as generators and motors not only need to have excellent soft magnetic properties, but also must withstand specific mechanical loads during service to ensure the stability and reliability of the structure.

[0003] In all the above magnetic-based applications, the Curie temperature, as the key temperature point for the transition from magnetism to paramagnetism, is a fundamental factor in determining the highest service temperature of the material and designing its composition system. Therefore, quickly and accurately predicting the intrinsic relationship between alloy composition and Curie temperature is a core challenge in the design of new high-performance soft magnetic alloys.

[0004] To address this challenge, data-driven machine learning methods have become a powerful method for exploring the relationship between the chemical composition of alloy materials and their Curie temperature. However, traditional composition design based on experimental trial-and-error methods have significant drawbacks such as long development cycle, high cost of manpower and resources, low efficiency, and are difficult to generate large-scale and high-quality data sets required for machine learning model training, thereby severely restricting the application performance of data-driven methods in material design. SUMMARY

[0005] Based on the above background, the purpose of the present application is to provide a Curie temperature calculation method for multi-component magnetic alloys, which solves the technical problems of long development cycle, high cost, low data output efficiency, and inability to meet the massive data requirements of machine learning methods when using traditional experimental trial-and-error methods to study the Curie temperature of multi-component soft magnetic alloys.

[0006] To achieve the above purpose, the present application adopts the following technical solutions:

[0007] In a first aspect, the present application provides a Curie temperature calculation method for multi-component magnetic alloys, comprising,

[0008] defining the alloy composition to be calculated, and writing the alloy composition information into a composition configuration file in a preset format;

[0009] based on the composition configuration file and the preset calculation parameters, automatically generating a standardized input file required by the EMTO calculation program and creating a hierarchical input directory;

[0010] traversing each alloy component in the component configuration file, for each determined alloy component, combining preset crystal structure type and magnetic configuration configuration, generating corresponding KKR self-consistent calculation and total charge density calculation KFCD input file, and writing the generated input file into the hierarchical subdirectory;

[0011] calling the EMTO calculation program, based on the input file in the hierarchical subdirectory, batch executing the calculation task, the calculation task including sequentially executed KKR self-consistent calculation task and total charge density calculation task;

[0012] Based on the output results of the calculation task, the state equation data is automatically extracted by parallel tools; and based on the extracted state equation data, batch fitting is performed to predict the ferromagnetic state ground state total energy and paramagnetic state ground state total energy ; the state equation data is the total energy of the system corresponding to different Wigner-Seitz radii;

[0013] Based on the ferromagnetic state ground state total energy and paramagnetic state ground state total energy , the Curie temperature is directly calculated by using the mean field theory formula.

[0014] In the second aspect, the application provides a Curie temperature calculation device for multi-component magnetic alloy, the device comprises,

[0015] An alloy component definition module is used to define the alloy component to be calculated, and write the alloy component information in a preset format into a component configuration file;

[0016] A hierarchical input directory construction module is used to automatically generate normalized input files required by the EMTO calculation program and create a hierarchical input directory based on the component configuration file and preset calculation parameters;

[0017] A calculation task input file generation module is used to traverse each alloy component in the component configuration file, for each determined alloy component, combine preset crystal structure type and magnetic configuration configuration, generate corresponding KKR self-consistent calculation and total charge density calculation KFCD input file, and write the generated input file into the hierarchical subdirectory;

[0018] An energy calculation module is used to call the EMTO calculation program, based on the input file in the hierarchical subdirectory, batch execute the calculation task, the calculation task including sequentially executed KKR self-consistent calculation task and total charge density calculation task;

[0019] An equation of state fitting module is configured to automatically extract equation of state data based on the output of the calculation task by the parallel tool, and to perform batch fitting based on the extracted equation of state data to predict the total energy of the ferromagnetic state ground state and the total energy of the paramagnetic state ground state The equation of state data corresponds to different Wigner-Seitz radii.

[0020] A Curie temperature calculation module is configured to directly calculate the Curie temperature based on the total energy of the ferromagnetic state ground state and the total energy of the paramagnetic state ground state obtained by fitting, using an average field theory formula.

[0021] In a third aspect, the present application provides a non-transitory computer-readable storage medium, which stores a computer program, and the computer program is loaded and executed by a processor to implement the Curie temperature calculation method of the multi-component magnetic alloy as described above.

[0022] In a fourth aspect, the present application provides an electronic device, which includes a processor, a memory, and a computer program stored on the memory and executable on the processor, and the processor implements the Curie temperature calculation method of the multi-component magnetic alloy as described above when executing the computer program.

[0023] Compared with the prior art, the present application has the following advantages:

[0024] The present application provides a Curie temperature calculation method of a multi-component magnetic alloy, which meets the needs of data-driven alloy magnetism and Curie temperature research. According to the composition and crystal structure of a given alloy, the method calls a first-principle calculation program to calculate the Curie temperature of the alloy in large quantities, greatly reducing the time and cost of experimental trial and error. In addition, the final data is organized in a structured data manner, which has flexibility and scalability, is conducive to subsequent query and use, and is suitable for machine learning algorithms. Specifically:

[0025] (1) The present application shortens the research work of several months or even years in the traditional experimental trial and error mode through a high-throughput and automated calculation process, greatly reduces the material consumption, equipment use and labor cost required by experiments, and realizes exponential improvement of research efficiency and effective control of cost.

[0026] (2) The data produced by the method provided by the present application has high consistency, accuracy and traceability. Each set of data is obtained based on a unified theoretical framework and calculation parameters, avoiding errors introduced by sample preparation and testing conditions in experiments, and providing a high-quality and standardized data basis for subsequent research.

[0027] (3) The data output by the application is organized in a structured form, and has excellent flexibility, scalability and machine readability. The database can be directly used as a training set, a verification set or a test set to build and train a high-precision machine learning model for predicting the Curie temperature based on components, thereby accelerating the discovery and optimization process of new materials. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0029] Figure 1 A flow chart of a Curie temperature calculation method of a multi-component magnetic alloy provided by the embodiment of the application is shown in the figure.

[0030] Figure 2 A working directory structure corresponding to an alloy component provided by the embodiment of the application is shown in the figure.

[0031] Figure 3 A flow chart of fitting a state equation provided by the embodiment of the application is shown in the figure.

[0032] Figure 4 In this implementation, the EOS data of an alloy component in two crystal structures and two magnetic configurations and the curve obtained by fitting the EOS equation are shown in the figure.

[0033] Figure 5 In this implementation, a comparison chart of the calculated Curie temperature of 40 FCC crystal structure and BCC crystal structure alloys and the literature values is shown in the figure.

[0034] Figure 6 A schematic diagram of a Curie temperature calculation device of a multi-component magnetic alloy provided by the embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0035] In order to further understand the application, the preferred embodiments of the application will be described in conjunction with the embodiments below, but it should be understood that these descriptions are only for further illustrating the features and advantages of the application, and are not limitations on the claims of the application.

[0036] Term explanation:

[0037] EMTO: EMTO stands for Exact Muffin-Tin Orbitals, which is a method used for computational simulation of materials, particularly in handling alloy systems with high accuracy. This method is based on first-principles calculations and can predict physical properties of materials such as energy, crystal structure, etc.

[0038] pyMETO: pyMETO is a Python library or toolkit specifically developed for the EMTO program, acting as a bridge between users and the underlying EMTO executable program. It enables automation and parameterization of the computational workflow. Users can write Python scripts to call functions in pyMETO to generate input files for EMTO, submit computational tasks, parse output files, and extract key data such as energy, volume, etc.

[0039] Pymatgen: Pymatgen is an open-source Python library for crystal structure analysis and generation, element and compound property queries, phase diagram construction, chemical reaction analysis, and input / output file format conversion, etc.

[0040] Face-Centered Cubic (FCC): Atoms are located at the eight corners of a cube and the center of each face. Typical metals include aluminum, copper, nickel, gold, and gamma-iron.

[0041] Body-Centered Cubic (BCC): Atoms are located at the eight corners of a cube and the center of the cube. Typical metals include chromium, tungsten, alpha-iron, and molybdenum.

[0042] KGRN: KGRN refers to the KKRR self-consistent calculation (Korringa-Kohn-Rostoker Self-Consistent Calculation) when calling the EMTO computational program. This is an electronic structure calculation task based on the KKR method, which focuses on solving the electronic structure of materials through self-consistent iteration to ensure the self-consistency of the calculation results in physics and mathematics. Through the KKR method and self-consistent iteration, KGRN can provide high-precision electronic structure data for materials science research.

[0043] KFCD: KFCD stands for Full Charge Density Calculation, which is the full name of the calculation. This step is based on the KGRN calculation, and its main purpose is to calculate the total energy of the material through the full charge density method.

[0044] Example 1

[0045] Reference Figure 1 The present embodiment provides a method for calculating the Curie temperature of a multi-component magnetic alloy, comprising the following steps:

[0046] S1: define the alloy components to be calculated, and write the alloy component information in a preset format into a composition configuration file;

[0047] S2: based on the composition configuration file and the preset calculation parameters, automatically generate the normalized input files required by the EMTO calculation program and create a hierarchical input directory;

[0048] S3: traverse each alloy component in the composition configuration file, for each determined alloy component, combine the preset crystal structure type and magnetic configuration configuration, generate the input files of the corresponding KKR self-consistent calculation and total charge density calculation tasks; and write the generated input files into the hierarchical subdirectory;

[0049] S4: call the EMTO calculation program, based on the input files in the hierarchical subdirectory, batch execute the calculation tasks, including KKR self-consistent calculation and total charge density calculation;

[0050] S5: automatically extract the equation of state data through a parallel tool, and based on the extracted equation of state data, batch fitting is performed to predict the ferromagnetic (FM) state ground state total energy and paramagnetic (PM) state ground state total energy ;

[0051] S6: based on the fitted ferromagnetic state ground state total energy and paramagnetic state ground state total energy , the Curie temperature is directly calculated using the mean field theory formula;

[0052] S7: write the alloy components, crystal structure types, fitted ground state energies, and calculated Curie temperatures, etc. Key information, according to the preset standardized format, write into a JSON file and output.

[0053] Specifically,

[0054] In step S1, the chemical components of the alloy to be calculated are defined, and the chemical component information is written into a composition configuration file in a preset format; For example, the composition_file.txt file, the composition configuration file contains atomic fraction information of at least one alloy component.

[0055] In step S2, by calling the pyMETO program matched with the EMTO calculation program, the normalized input file required by the EMTO calculation is automatically generated based on the component configuration file and the preset calculation parameters, so as to ensure the accuracy and consistency of the calculation process. The pyMETO program serves as an automatic bridge connecting the component analysis and the EMTO calculation, receives and reads the component information in the component configuration file, and generates the formatted input file meeting the requirements of the EMTO according to the component information, which is a key link for realizing the process automation.

[0056] The preset main input parameters include:

[0057] (1) Atomic weight: the alloy component information in the component configuration file is parsed line by line by the pymatgen tool in the open source Python library for material analysis, and the atomic fraction of each element is normalized; according to the normalized atomic fraction, the atomic weight of the corresponding lattice point in the input file is set.

[0058] (2) Crystal structure type: including face-centered cubic structure FCC and body-centered cubic structure BCC, and more possible crystal structures, constituting a crystal structure list lattice_list;

[0059] (3) Magnetic configuration: including ferromagnetic state FM and paramagnetic state PM, constituting a magnetic configuration list magn_list;

[0060] (4) Wigner-Seitz radius scanning: a series of Wigner-Seitz radius (SWS) values are taken, constituting a Wigner-Seitz radius list sws_list, which is used for subsequent calculation of state equation, for example, 2.50 Bohr to 2.80 Bohr.

[0061] In the embodiment, the specific processing procedure includes:

[0062] S201: Read the component information of the alloy from the composition_file.txt file, and use the pymatgen tool to parse the alloy component information, and convert the original data into structured data form. pymatgen as a data analysis and preprocessing tool, by reading the composition_file.txt file and identifying the chemical elements and atomic fractions therein, then performing normalization processing, converts the human-readable component information into machine-processable structured data, and prepares for subsequent calculation.

[0063] Subsequently, the composition list composition_list is traversed, and the atomic fraction of each element is normalized as a weight to ensure the normalization of data, so that the composition of the alloy contained in the given composition_file.txt file and the composition of the alloy after normalization are included.

[0064] S202: sequentially traverse the lattice structure list lattice_list, the magnetic configuration list magn_list, and the Wigner-Seitz radius list sws_list, and set the corresponding input parameters. After the above step is completed, an input directory with a hierarchical structure is created according to the alloy composition name, the crystal structure name, and the magnetic configuration name, so as to facilitate the management and search of data. Finally, the input files are saved to the corresponding directory, and the path of the input files on the disk is recorded to the file. As shown in Figure 2 The structure of the working directory corresponding to a certain alloy composition includes information such as alloy composition, crystal structure identification, equation of state, and flow of electronic structure calculation. Each alloy composition follows the directory structure. Such a shallow directory structure helps to reduce IO pressure and improve program running speed.

[0065] In step S3, each alloy component in the composition configuration file is traversed, and for each component, the input files of the corresponding KKR self-consistent calculation KGRN and the total charge density calculation KFCD are generated in combination with the preset crystal structure type and magnetic configuration configuration, and the storage location of the input file is located to ensure that the subsequent calculation task can accurately access the required input resources. Then the generated input file is written into a hierarchical subdirectory named in the format of “component name / crystal structure name_magnetic configuration name”, realizing the ordered management of the calculation task.

[0066] The input file of KGRN is mainly used to define the control parameters of the self-consistent field KKR calculation, the lattice information, the numerical precision setting, and the atomic composition information. Its structure includes the following parts:

[0067] (1) File header and task information: task name, calculation mode and option control line, and external file path definition, etc.

[0068] (2) Calculation parameter area: control self-consistent iteration number, magnetic configuration, crystal structure type, angular momentum cutoff, convergence criterion, Wigner-Seitz radius, etc.

[0069] (3) Component setting area: define the symbol Symb of each element, the grid number IQ, the sub-lattice number IT, the atomic type number ITA, the atomic number NZ, the concentration, the initial magnetic moment SPLT, etc.

[0070] (4) Exchange-correlation functional setting and solution precision setting;

[0071] (5) Electron shell configuration information;

[0072] KFCD is the total electron density obtained based on the convergence of KGRN, and the density functional theory DFT total energy functional of the system is calculated to obtain the ground state total energy of the system. Therefore, the KFCD input file content includes file path association information, that is, connection with the file generated by KGRN, and setting of numerical integration and expansion parameters.

[0073] In step S4, the EMTO calculation program is called to perform the calculation task in batches based on the input files in the hierarchical subdirectory. The calculation task includes:

[0074] KKR self-consistent calculation: execute the KGRN program to obtain the self-consistent charge density of the system under different Wigner-Seitz radii;

[0075] Total charge density calculation: execute the KFCD program to calculate and obtain the total energy of the system based on the self-consistent charge density;

[0076] EMTO as the core calculation engine is responsible for performing high-precision quantum mechanical calculations to generate total energy data of alloy systems under different volumes and magnetic states. The specific process is:

[0077] S401: The system starts the KKR self-consistent calculation task by traversing the preset Wigner-Seitz radius list, and sequentially executes the KGRN and KFCD programs. Each radius value corresponds to an independent calculation process, that is, a sub-task calculation module is calculated. This step realizes the automatic calculation execution under multiple parameter conditions and provides a rich data basis for subsequent analysis.

[0078] Further, due to the large number of calculation tasks and the variety of parameter combinations of complex material systems, there are problems such as low efficiency, difficult management, and easy errors. To solve this problem, the calculation tasks are processed and executed automatically in batches in this embodiment, so as to efficiently obtain physical quantities such as total energy and atomic magnetic moment under multiple chemical systems and configurations. Including,

[0079] (1) Construct a single-system parallel running module to efficiently and parallelly process according to the predefined task list. Its function is realized through a batch_run_parallel module, and the specific steps are as follows:

[0080] Receive a working directory emto_workdir as input, and locate a task list file such as jobname.txt under this directory. The file lists all the task names of the independent systems or configurations to be calculated as the input source of the batch processing job.

[0081] The tasks in the task list are distributed to the computing nodes for parallel execution by a parallel task scheduling tool such as GNU Parallel. The maximum concurrency of parallel tasks can be dynamically configured by the parameter num_task to maximize the utilization of multi-core resources of the computing server and significantly shorten the total computing time. The default value of num_task is 40.

[0082] Pre-check and environment preparation operations are performed to ensure that each subtask can run in an independent and complete environment. This includes verifying that the working directory, task list file, and necessary auxiliary scripts exist and are valid; exporting key check and verification functions to ensure that each parallel task has independent error diagnosis and processing capabilities.

[0083] After all parallel subtasks are completed, log information is output to identify the end of the entire batch.

[0084] (2) Build a high-throughput computing module, including,

[0085] Receive a chemical system name identifier and read the components to be calculated line by line according to the corresponding component list file.

[0086] For each component, traverse the given crystal structure type and magnetic state to automatically generate the corresponding standardized directory hierarchy to be calculated.

[0087] After entering the specific directory, call the single-system parallel running module to perform parallel computation on all tasks for the component.

[0088] Due to the long-term and resource-consuming nature of high-throughput computation, stricter pre-checks are performed on the legality of the directory before the task is issued. If the generated directory hierarchy structure is missing or does not meet expectations, an error is reported and the task is terminated to avoid resource waste.

[0089] (3) Combine parallel execution and strict checking strategies to ensure computing efficiency while considering task reliability, control running and exceptions, including,

[0090] Through the high-throughput computing module, single-system parallel running module, and subtask computing module, a complete and automated link from high-throughput chemical system traversal to single-task computation and exception capture is realized. Lower-level single-task errors such as convergence failure are captured and recorded by the subtask computing module, while middle-level parallel task errors such as sub-process crashes, or upper-level parameter configuration errors are managed and reported by the single-system parallel running module and high-throughput computing module, respectively, forming a clear error responsibility boundary.

[0091] In summary, in the high-throughput computing scenario of complex systems, the efficient batch running of KGRN and KFCD programs is achieved through task list driving and parallel scheduling, and strict input checking and error control mechanisms are provided, thereby ensuring the automation, robustness and scalability of the calculation.

[0092] S402: In order to ensure the smooth execution of the computing task, the system starts a background monitoring process while performing KKR self-consistent calculation. This process tracks the calculation state and progress in real time, can timely discover and report abnormal conditions such as calculation interruption, resource exhaustion, etc., and trigger the corresponding processing mechanism.

[0093] In this embodiment, the background running state monitoring and exception capture of the KGRN program are taken as examples, which are described as follows:

[0094] The monitoring process specifically includes the following four stages:

[0095] The first stage: calculation task process and output file initialization checking stage, which aims to confirm that the KGRN process has been successfully started and entered into a stable calculation state, avoiding monitoring idling or misjudgment.

[0096] The second stage: real-time process survival monitoring, after successfully passing the initialization verification, it enters the continuous monitoring stage of the survival state of the KGRN process. For example, a fixed detection period is used to detect whether the corresponding process is alive, and when the process ends, its exit state is recorded and the success is returned.

[0097] The third stage: error mode identification and exception capture, during the process survival period, the output file is parsed in real time to actively identify specific abnormal patterns that may occur in the calculation process, which lead to invalid loops or error states of the task.

[0098] A set of error strings related to the internal logic of the KGRN program and their corresponding trigger thresholds are predefined. These patterns represent common convergence failures or logic errors in KGRN calculation. They include iteration convergence failure trigger threshold, self-consistent field cycle failure trigger threshold and Fermi level solution failure trigger threshold. If any condition is met, it is considered that the calculation is abnormal, and a timestamped error log is output and the corresponding process is forcibly terminated.

[0099] The fourth stage: error handling and log mechanism, all checking results are identified and attached with standardized timestamps, which facilitates task tracking and debugging. When an exception is detected, the function is immediately aborted and an error code is returned for the upper layer call logic to perform fault tolerance or resubmit the calculation.

[0100] In summary, through the combination of file existence detection, process survival monitoring and error log pattern matching, real-time background monitoring of the KGRN subroutine running process is realized, and the process is automatically captured and terminated when an exception is found, thereby improving the robustness and automation level of the calculation process.

[0101] S403: After all the calculation tasks are completed, the entire process is automatically ended. If it is detected that there are still unfinished tasks, the system will return to the self-consistent calculation step S401 to continue executing the remaining calculation tasks until all tasks are completed. This loop control mechanism ensures the integrity and automation level of task execution.

[0102] In step S5, the state equation data is automatically extracted, and the BASH script is used in combination with the Parallel parallel tool to efficiently and in parallel extract the state equation data from the output file generated in step S4. The state equation data is specifically the total energy of the system corresponding to different Wigner-Seitz radii. The extracted EOS data is written into a data file in a predetermined format.

[0103] The parallel computing library of Python language, such as joblib or multiprocessing, is used to batch fit the extracted EOS state equation data to predict the ground state energy in the ferromagnetic state and the paramagnetic state. The state equation is a mathematical model describing the relationship between the energy E of the material and the volume V, which is used to fit a series of (volume, total energy) data points obtained in S5 calculation.

[0104] Through fitting, the ground state energy of the system can be accurately determined as a key input parameter for subsequent calculation of the Curie temperature. In this embodiment, the parallelization method significantly improves the data processing efficiency. After fitting is completed, the results are automatically written into a designated file.

[0105] The state equation fitting model includes at least the following two types of Morse state equation and Birch-Murnaghan state equation:

[0106] (1) Morse state equation

[0107]

[0108] wherein, E is the total energy of the system, with the unit of Ry; R is the Wigner-Seitz radius, with the unit of Bohr, , , and are parameters to be fitted.

[0109] (2) Birch-Murnaghan state equation

[0110]

[0111] where, is the total energy of the system, is the volume, is the total energy of the ground state, is the volume of the ground state, is the bulk modulus, is the first derivative of the bulk modulus with respect to pressure.

[0112] Referring to Figure 3 , the flow of the state equation (EOS, Equation of State) fitting calculation is as follows:

[0113] 1) Data input: read the EOS data from the file, corresponding to the values between energy E and volume V;

[0114] 2) Initial parameter estimation: fit the parabola to quickly obtain the initial parameters;

[0115] 3) Minimum value judgment: check whether the parabola has a minimum value, which corresponds to the physical meaning of whether the system has a stable ground state, and if not, an error is reported, which corresponds to data abnormalities and cannot describe a stable crystal;

[0116] 4) Initial parameter calculation: if there is a minimum value, calculate the key initial parameters of the EOS, including the total energy of the ground state , the volume of the ground state , the bulk modulus , and the first derivative of the elastic modulus with respect to pressure ;

[0117] 5) Accurate fitting: call the numerical fitting tool to fit the specified EOS model;

[0118] 6) Convergence judgment: check whether the fitting is converged, and if not, an error is reported;

[0119] 7) Result calculation and output: after convergence, calculate the ground state properties and fitting goodness, save the results and draw the graph; the ground state properties include the energy, volume, and bulk modulus of the equilibrium state, and the fitting goodness includes , which is used to measure the quality of the fitting, and the process ends.

[0120] Referring to Figure 4 , the EOS data of an alloy composition provided in this embodiment under two crystal structures of FCC and BCC and two magnetic configurations of FM and PM, and the curve obtained by fitting the EOS equation are shown, wherein the ground state energy Wigner-Seitz radius w0 and the corresponding goodness of fit .

[0121] In step S6, the total ground state energy of the ferromagnetic state and the total ground state energy of the paramagnetic state are obtained based on the fitting in step S5, and the content of the ferromagnetic element is calculated The Curie temperature is directly calculated using the mean field theory formula, which does not compromise the accuracy of the calculation and can save the time of performing a self-consistent calculation once.

[0122] wherein, according to different determination methods of the ferromagnetic element, the content of the ferromagnetic element is directly calculated according to the periodic table of elements, and the typical ferromagnetic elements of iron, cobalt and nickel are determined as the magnetic elements; or according to the calculation results, the elements with non-zero atomic local magnetic moment are determined as the magnetic elements.

[0123] The formula of the mean field theory is as follows:

[0124]

[0125] wherein, k B is the Boltzmann constant, is the content of the ferromagnetic element. This method directly estimates the distance temperature through the energy difference, avoiding the performance of a large number of finite temperature self-consistent calculations, while ensuring the calculation accuracy and significantly saving the calculation time.

[0126] In step S7, the alloy composition, crystal structure type, fitted ground state energy and calculated Curie temperature and other key information are written into the output JSON file in a predetermined standardized format, facilitating subsequent data analysis and visualization. The names and meanings of the stored fields are shown in Table 1.

[0127] Table 1: Name and meaning of key in alloy dataset JSON file

[0128]

[0129] To further verify the feasibility and reliability of the method, the Curie temperature calculation results of 40 FCC crystal structure and BCC crystal structure alloys are compared with the literature data, and the results are shown in Table 2. Further Figure 5 The comparison of the calculated values and the literature values of the Curie temperature of the 40 FCC crystal structure and BCC crystal structure alloys in this implementation can be more intuitively observed. The results show that the calculated data is in good agreement with the literature data, which fully proves the accuracy and stability of the method proposed in the present application in the prediction of the Curie temperature.

[0130] Table 2: Calculated and literature values of Curie temperature for 40 alloys with different crystal structures (FCC and BCC)

[0131]

[0132] Example 2

[0133] Referring to Figure 6 The embodiment provides a Curie temperature calculation device for multi-component magnetic alloys, and the device comprises,

[0134] An alloy component definition module is configured to define alloy components to be calculated and write alloy component information in a preset format into a component configuration file.

[0135] A hierarchical input directory construction module is configured to automatically generate a normalized input file required by an EMTO calculation program and create a hierarchical input directory based on the component configuration file and preset calculation parameters.

[0136] A calculation task input file generation module is configured to traverse each alloy component in the component configuration file, generate a corresponding KKR self-consistent calculation and full charge density calculation KFCD input file in combination with a preset crystal structure type and magnetic configuration for each determined alloy component, and write the generated input file into a hierarchical subdirectory.

[0137] An energy calculation module is configured to call the EMTO calculation program, perform a batch of calculation tasks based on the input file in the hierarchical subdirectory, and the calculation tasks include sequentially performed KKR self-consistent calculation tasks and full charge density calculation tasks.

[0138] An equation of state fitting module is configured to automatically extract equation of state data through a parallel tool based on the output results of the calculation tasks, and perform a batch of fitting based on the extracted equation of state data to predict ferromagnetic state ground state total energy and paramagnetic state ground state total energy ; the equation of state data is total energy of a system corresponding to different Wigner-Seitz radii.

[0139] A Curie temperature calculation module is configured to directly calculate the Curie temperature by using an average field theory formula based on the ferromagnetic state ground state total energy and paramagnetic state ground state total energy obtained through fitting.

[0140] Example 3

[0141] The embodiment provides a non-transitory computer readable storage medium, wherein the storage medium stores a computer program, and the computer program is loaded and executed by a processor to realize the Curie temperature calculation method of the multi-component magnetic alloy as described in the embodiment 1.

[0142] Embodiment 4

[0143] The embodiment provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, and the processor realizes the Curie temperature calculation method of the multi-component magnetic alloy as described in the embodiment 1 when executing the computer program.

[0144] The above description of the embodiments is only used to help understand the method of the present application and its core idea. It should be noted that, for those skilled in the art, without departing from the principle of the present application, some improvements and modifications can be made to the present application, and these improvements and modifications also fall within the protection scope of the claims of the present application.

[0145] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0146] It should be noted that some of the example embodiments are described as a process or method depicted as a flowchart. Although the flowchart describes the steps of the process as sequential, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps can be re-arranged. The process can be terminated when its operations are completed, but can also have additional steps not included in the figure. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

Claims

1. A method for calculating the Curie temperature of a multi-component magnetic alloy, characterized in that, include, Define the alloy composition to be calculated, and write the alloy composition information into the composition configuration file in a preset format; Based on the component configuration file and preset calculation parameters, the standardized input files required by the EMTO calculation program are automatically generated and a hierarchical input directory is created. Iterate through each alloy component in the composition configuration file. For each specific alloy component, combine the preset crystal structure type and magnetic configuration to generate corresponding KKR self-consistent calculation and KFCD total charge density calculation input files, and write the generated input files into a hierarchical subdirectory. The EMTO calculation program is invoked to perform calculation tasks in batches based on the input files in the hierarchical subdirectory. The calculation tasks include KKR self-consistent calculation tasks and total charge density calculation tasks executed sequentially. Based on the output of the computational task, state equation data is automatically extracted using parallel tools; and batch fitting is performed based on the extracted state equation data to predict the total energy of the ferromagnetic ground state. Total energy of the ground state in paramagnetic state The state equation data represents the total energy of the system corresponding to different Wigner-Seitz radii. The total energy of the ferromagnetic ground state obtained based on fitting Total energy of the ground state in paramagnetic state The Curie temperature is calculated directly using the mean-field theory formula.

2. The method for calculating the Curie temperature of a multi-component magnetic alloy according to claim 1, characterized in that, It also includes writing the key information of the alloy composition, crystal structure type, fitted ground state energy and / or calculated Curie temperature into a JSON file and outputting it according to a preset standardized format.

3. The method for calculating the Curie temperature of a multi-component magnetic alloy according to claim 1, characterized in that, The preset calculation parameters include atomic weights based on the normalized atomic fractions of each element, crystal structure types including face-centered cubic (FCC) and body-centered cubic (BCC) structures, magnetic configurations including ferromagnetic (FM) and paramagnetic (PM) states, and / or a series of predetermined Wigner-Seitz radius values.

4. The method for calculating the Curie temperature of a multi-component magnetic alloy according to claim 1, characterized in that, The KKR self-consistent calculation input file includes control parameters, lattice information, numerical precision, and atomic composition information for defining the self-consistent field KKR calculation. The KGRN task is used to obtain the self-consistent charge density under different Wigner-Seitz radii.

5. The method for calculating the Curie temperature of a multi-component magnetic alloy according to claim 1, characterized in that, The EMTO calculation program is invoked to perform batch calculation tasks based on the input files in the hierarchical subdirectory. These tasks include sequentially executed KKR self-consistent calculation tasks and total charge density calculation tasks. Traverse the preset list of Wigner-Seitz radii, start the KKR self-consistent calculation task, and execute the KGRN and KFCD task execution programs in sequence. Each radius value corresponds to an independent calculation process. While performing KKR self-consistent computation, start the background monitoring process; Track computation status and progress in real time, and detect and report anomalies; The process will automatically end after all computational tasks have been completed. If any incomplete tasks are detected, the system will return to the self-consistent computation step and continue executing the remaining computation tasks until all tasks are completed.

6. The method for calculating the Curie temperature of a multi-component magnetic alloy according to claim 1, characterized in that, The batch fitting based on the extracted state equation data includes... The data were fitted using state equation fitting models, including the Morse state equation and the Birch-Murnaghan state equation. Morse's equation of state is: in, It is the total energy of the system, expressed in Ry; It is the Wigner-Seitz radius, in Bohr; , , and These are the parameters to be fitted; The Birch-Murnaghan equation of state is: in, It is the total energy of the system. It is volume. It is the total energy of the ground state. It is the volume of the ground state. It is the bulk elastic modulus, It is the first derivative of the bulk elastic modulus with respect to pressure.

7. The method for calculating the Curie temperature of a multi-component magnetic alloy according to claim 1, characterized in that, The mean-field theory formula is as follows: Where, k B denoted as Boltzmann constant, and c represents the content of ferromagnetic elements. The content of ferromagnetic elements is calculated directly based on the periodic table, identifying typical ferromagnetic elements such as iron, cobalt, and nickel as magnetic elements; or based on the calculation results, elements with non-zero local magnetic moments are identified as magnetic elements and their content is calculated.

8. A Curie temperature calculation device for a multi-component magnetic alloy, characterized in that, The device includes, The alloy composition definition module is used to define the alloy composition to be calculated and write the alloy composition information into the composition configuration file in a preset format. The hierarchical input directory construction module is used to automatically generate the standardized input files required by the EMTO calculation program and create a hierarchical input directory based on the component configuration file and preset calculation parameters. The calculation task input file generation module is used to traverse each alloy component in the composition configuration file. For each determined alloy component, it generates corresponding KKR self-consistent calculation and KFCD total charge density calculation input files by combining the preset crystal structure type and magnetic configuration, and writes the generated input files into a hierarchical subdirectory. The energy calculation module is used to call the EMTO calculation program and perform calculation tasks in batches based on the input files in the hierarchical subdirectory. The calculation tasks include KKR self-consistent calculation tasks and total charge density calculation tasks executed sequentially. The state equation fitting module is used to automatically extract state equation data based on the output of computational tasks using parallel tools; and to perform batch fitting based on the extracted state equation data to predict the total energy of the ferromagnetic ground state. Total energy of the ground state in paramagnetic state The state equation data represents the total energy of the system corresponding to different Wigner-Seitz radii. The Curie temperature calculation module is used to calculate the total energy of the ferromagnetic ground state based on the fitted data. Total energy of the ground state in paramagnetic state The Curie temperature is calculated directly using the mean-field theory formula.

9. A non-transitory computer-readable storage medium, characterized in that, The storage medium stores a computer program, which is loaded and executed by a processor to implement the Curie temperature calculation method for multi-component magnetic alloys as described in any one of claims 1-7.

10. An electronic device, comprising: A processor, a memory, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements the method for calculating the Curie temperature of a multi-component magnetic alloy as described in any one of claims 1-7.

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