Analysis Method for Structural Performance of MOF Materials, Storage Medium and Electronic Device

Abstract

The present application relates to a method for analyzing the structural properties of MOFs materials, a storage medium, and an electronic device. The method includes: obtaining a first structure file of a target MOFs material model and creating a first input parameter file; using DFTB+ software to read the first structure file and the first input parameter file for geometric optimization to obtain a second structure file, its compound energy, and unit cell parameters; if the target MOFs material is a newly designed structure, calculating the formation energy based on theoretical chemical equations, elemental energies, and compound energies; if the target MOFs material is an existing structure, calculating the formation energy based on existing chemical equations and the energies of the reactants and products of the equation; creating a second input parameter file; using DFTB+ software to read the second structure file and the second input parameter file for density of states calculation and visualization to obtain a density of states map; and analyzing the target MOFs material based on the unit cell parameters, formation energy, and density of states map.

Description

Technical Field

[0001] This application relates to the technical field of material analysis. Specifically, it relates to a method for analyzing the structural properties of MOFs materials, a storage medium, and an electronic device. Background Art

[0002] Metal-organic frameworks (MOFs), also known as metal-organic skeletons, are a new type of porous material and have attracted much attention due to their wide application potential in fields such as gas adsorption, separation, and catalysis. The structure of MOFs consists of metal centers (secondary building units, SBUs) and organic ligands, and their pore size, topological structure, and functional characteristics can be precisely regulated by adjusting the types of metal centers and organic ligands. With the progress of MOFs synthesis and modification technologies, researchers can flexibly change their structures and chemical properties and further expand their application fields by means such as introducing functional groups, exchanging metals and ligands, and encapsulating nano-objects. Currently, more than 100,000 different MOFs have been successfully synthesized.

[0003] However, with the rapid increase in the types of MOFs materials, the number of MOFs that can be synthesized in the future may reach trillions, far exceeding the scope that traditional experimental methods can handle. It is unrealistic to rely solely on experimental synthesis and testing of all potential MOFs materials. Especially under limited time and resources, the efficiency of experimental screening faces severe challenges. The research and development of MOFs materials urgently need to rely on computational simulations. Simulations can use chemical calculation software developed by commercial companies such as Material studio, but these software have problems such as high fees. Summary of the Invention

[0004] The purpose of this application is to provide a method for analyzing the structural properties of MOFs materials, a storage medium, and an electronic device, aiming to analyze the structural properties of MOFs materials through simulation calculations to provide analysis data for MOFs material screening, improve the efficiency of screening MOFs materials, reduce the screening cost, and this process is implemented based on the free and open-source software DFTB+, reducing the cost of simulation calculations.

[0005] To achieve the above purpose, in the first aspect of this application, a method for analyzing the structural properties of MOFs materials is provided. The method includes:

[0006] Obtain the first structure file of the target MOFs material model and produce the first input parameter file for geometric optimization of the target MOFs material model;

[0007] Run the geometric optimization command in the DFTB+ software to read the first structure file and the first input parameter file and perform geometric optimization simulations to obtain the second structure file, the compound energy, and the unit cell parameters of the geometrically optimized target MOFs material model;

[0008] If the target MOF material has a newly designed structure, calculate the formation energy of the target MOF material based on the theoretical chemical equation for synthesizing the target MOF material from the elemental substances of the constituent elements of the target MOF material, the energy of the elemental substances, and the energy of the compound.

[0009] If the target MOF material has an existing structure, calculate the formation energy of the target MOF material based on the existing chemical equation for synthesizing the target MOF material and the energies of the reactants and products in this existing chemical equation, where the energy of the product includes the energy of the compound.

[0010] Create a second input parameter file for the target MOF material model for density of states calculation.

[0011] Run the density of states calculation command in the DFTB+ software to read the second structure file and the second input parameter file and perform the density of states calculation, and visualize the density of states calculation results to obtain the density of states diagram of the geometrically optimized target MOF material model.

[0012] Analyze the target MOF material based on the unit cell parameters, formation energy, and density of states diagram.

[0013] Optionally, the calculating the formation energy of the target MOF material based on the theoretical chemical equation for synthesizing the target MOF material from the elemental substances of the constituent elements of the target MOF material, the energy of the elemental substances, and the energy of the compound includes:

[0014] Determine the elemental substances of all constituent elements of the target MOF material based on the chemical formula of the target MOF material.

[0015] Determine the reaction equation for generating the target MOF material using all the elemental substances and balance it to obtain the theoretical chemical equation.

[0016] Calculate the energy of all the elemental substances.

[0017] Multiply the energy of the compound by the product of the stoichiometric coefficients of the target MOF material in the theoretical chemical equation, and subtract the product of the energy of each elemental substance and its stoichiometric coefficient in the theoretical chemical equation to obtain the formation energy.

[0018] Optionally, the calculating the formation energy of the target MOF material based on the existing chemical equation for synthesizing the target MOF material and the energies of the reactants and products in this existing chemical equation includes:

[0019] Obtain the existing chemical equation for synthesizing the target MOF material.

[0020] Calculate the energies of all reactants and all products other than the target MOF material in the existing chemical equation.

[0021] Multiply the energy of the compound by the stoichiometric number of the target MOF material in the existing chemical equation, add the product of the energy of each product other than the target MOF material and its stoichiometric number in the existing chemical equation, and subtract the product of the energy of each reactant and its stoichiometric number in the existing chemical equation to obtain the formation energy.

[0022] Optionally, calculating the energy of all the simple substances includes:

[0023] For each simple substance, obtain the third structure file of the simple substance and create a third input parameter file for geometric optimization of the simple substance;

[0024] Run the geometric optimization command in the DFTB+ software to read the third structure file and the third input parameter file and perform geometric optimization simulation to obtain the energy of each geometrically optimized simple substance.

[0025] Optionally, calculating the energy of all reactants and all products other than the target MOF material in the existing chemical equation includes:

[0026] For each reactant and each product other than the target MOF material in the existing chemical equation, obtain the fourth structure file of the reactant or product and create a fourth input parameter file for geometric optimization;

[0027] Run the geometric optimization command in the DFTB+ software to read the fourth structure file and the fourth input parameter file and perform geometric optimization simulation to obtain the energy of each reactant and each product after geometric optimization.

[0028] Optionally, creating the first input parameter file for geometric optimization of the target MOF material model includes:

[0029] Create a first initial file in hsd format;

[0030] Write the Geometry module in the first initial file and set the object of geometric optimization to the first structure file in this module;

[0031] Write the Driver module in the first initial file and set the calculation type to geometric optimization in this module, set to enable full lattice optimization and use a rational function optimizer, set the maximum number of optimization steps to any step between 100 and 200 steps, and set the convergence criterion to GradElem of the gradient element less than 1e-4;

[0032] Write the Hamiltonian module in the first initial file, and in this module, set to turn on the self-consistent charge calculation, with the convergence value and the maximum number of iterations of this calculation being 1e-6 and 2000 times respectively. Set the Slater-Koster parameters to use the 3OB parameter set. Set the maximum angular momentum quantum number of each element of the target MOFs material model. Set the k-point sampling in the Brillouin zone to use the Monkhorst-Pack method and only select the Γ point as the k-point sampling point;

[0033] Write the Analysis module in the first initial file, and in this module, set the calculation properties;

[0034] Write the ParserOptions module in the first initial file, and in this module, set the parser version, and finally obtain the first input parameter file for the geometric optimization of the target MOFs material model.

[0035] Optionally, the second input parameter file for the density of states calculation of the target MOFs material model includes:

[0036] Create a new second initial file in hsd format;

[0037] Write the Geometry module in the second initial file, and in this module, set the object of the density of states calculation to the second structure file;

[0038] Write the Hamiltonian module in the second initial file, and in this module, set to turn on the self-consistent charge calculation with the convergence value being 1e-5. Set the maximum angular momentum quantum number of each element of the target MOFs material model. Set the k-point sampling density in the Brillouin zone to an 8×8×8 grid;

[0039] Write the Analysis module in the second initial file, and in this module, set the projection region for the density of states calculation of each element of the target MOFs material model;

[0040] Write the ParserOptions module in the second initial file, and in this module, set the parser version, and finally obtain the second input parameter file for the density of states calculation of the target MOFs material model.

[0041] Optionally, the analysis of the target MOFs material based on the unit cell parameters, formation energy, and density of states diagram includes:

[0042] Analyze the unit cell shape and size of the target MOFs material based on the unit cell parameters;

[0043] When the target MOFs material is a newly designed structure, if the formation energy is greater than 0, determine that the target MOFs material cannot be formed by spontaneous reaction;

[0044] When the target MOF material is an existing structure, determine one or more existing chemical equations with the minimum formation energy for experimental verification;

[0045] Perform total density of states analysis and partial density of states analysis on the target MOF material based on the density of states diagram.

[0046] In a second aspect of the present application, there is provided a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method described in any one of the first aspects above are implemented.

[0047] In a third aspect of the present application, there is provided an electronic device, including:

[0048] A memory, on which a computer program is stored;

[0049] A processor, configured to execute the computer program in the memory to implement the steps of the method described in any one of the first aspects above.

[0050] Through the above technical solutions, for the target MOF material model to be analyzed, obtain its first structure file and create its first input parameter file, and perform geometric optimization simulation by reading the first structure file and the first input parameter file through DFTB+ to perform geometric optimization on the target MOF material model, so as to obtain the compound energy and unit cell parameters. For different situations of the target MOF material, if it is a newly designed structure, calculate the formation energy based on the theoretical chemical equation for the synthesis of elemental components, elemental energy, and compound energy; if it is an existing structure, calculate the formation energy based on the existing chemical equation, reactant, and product energy. Finally, create a second input parameter file, and use DFTB+ to read this file and the second structure file of the geometrically optimized target MOF material model to perform density of states calculation and visualization to obtain the density of states diagram. After the operation is completed, the target MOF material can be analyzed based on the calculated unit cell parameters, formation energy, and density of states diagram. In this way, the simulation calculation and analysis of MOF materials are realized based on the open-source and free software DFTB+, which can provide more data support for screening MOF materials, improve the screening efficiency, and reduce the time and cost of screening.

[0051] Other features and advantages of the present application will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The drawings are used to provide a further understanding of the present application and constitute a part of the specification. They are used together with the following specific implementation to explain the present application, but do not constitute a limitation to the present application. In the drawings:

[0053] Figure 1It is a flowchart of a method for analyzing the structural properties of MOFs materials shown according to an exemplary embodiment.

[0054] Figure 2 It is a structural model diagram of geometrically optimized Mg-MOF-74 shown according to an exemplary embodiment.

[0055] Figure 3 It is a density of states diagram of Mg-MOF-74 shown according to an exemplary embodiment.

[0056] Figure 4 It is a block diagram of an electronic device shown according to an exemplary embodiment. Detailed implementation manners

[0057] The following will detail the specific implementation manners of the present application in conjunction with the accompanying drawings. It should be understood that the specific implementation manners described herein are only for the purpose of illustrating and explaining the present application, and are not used to limit the present application.

[0058] Metal-organic framework materials (MOFs) have shown broad application prospects in many fields such as air and water capture, carbon capture (carbon dioxide capture), adsorption and separation of volatile organic compounds (VOCs), etc. due to their highly adjustable pore structures, large specific surface areas, and excellent adsorption properties, and have important industrial and environmental practical values. However, the number of reported MOFs compounds is huge currently (for example, more than 100,000 MOFs are included in the Cambridge Structural Database CSD). If only relying on traditional experimental methods for performance analysis and screening, there are many inconveniences:

[0059] 1. Time and cost limitations of experimental screening:

[0060] Although MOFs materials have broad application prospects in many fields, the huge and increasing number of MOFs materials makes it infeasible to rely on traditional experiments to synthesize and test one by one. Under limited time and resources, simply relying on experimental screening methods cannot cover all potential MOFs materials, resulting in low efficiency and high cost in the screening process.

[0061] 2. High complexity of structure and performance:

[0062] The structure and performance of MOFs materials are affected by the complex interactions of multiple factors such as metal centers, ligands, pore structures, and functional groups, and it is difficult to comprehensively evaluate them by traditional experimental means. With the continuous progress of synthesis technologies, the variety of MOFs materials increases, making the systematic research on their performance more difficult.

[0063] 3. Lack of efficient screening and optimization tools:

[0064] Currently, there is a lack of efficient screening and optimization tools in the research and development process of MOFs. Traditional experimental methods not only require a large number of experiments and time, but also need to be repeatedly debugged and improved, increasing the investment of time and cost. In addition, existing research methods are difficult to efficiently process a large library of MOFs materials, limiting the potential of MOFs materials in applications.

[0065] Therefore, with the rapid increase in the types of MOFs materials and the high complexity of their structural properties, traditional experimental analysis methods are difficult to meet the requirements of rapid and efficient screening and optimization. To accelerate the research and development process of MOFs materials, new methods based on computational simulation need to be introduced to analyze the structural properties of MOFs materials, providing a basis for the screening of MOFs materials, thereby reducing the experimental workload, lowering costs, and improving the research and development efficiency.

[0066] DFTB+ (Density Functional Tight Binding Plus) is a fast quantum mechanics calculation software based on the tight-binding density functional theory (DFTB), suitable for electronic structure calculations and molecular dynamics simulations of systems such as molecules, clusters, crystals, surfaces, and nanomaterials. As an approximation method based on the density functional theory DFT, DFTB+ greatly improves the calculation efficiency by using pre-computed DFT parameter files, especially suitable for large-scale molecular dynamics simulations.

[0067] Figure 1 is a flowchart of a method for analyzing the structural properties of a MOFs material shown according to an exemplary embodiment. Refer to Figure 1 This method includes:

[0068] S101, obtain the first structure file of the target MOFs material model and create the first input parameter file for the geometric optimization of the target MOFs material model.

[0069] S102, run the geometric optimization command in the DFTB+ software to read the first structure file and the first input parameter file and perform geometric optimization simulation to obtain the second structure file, the compound energy, and the unit cell parameters of the geometrically optimized target MOFs material model.

[0070] S103, if the target MOFs material is a newly designed structure, calculate the formation energy of the target MOFs material based on the theoretical chemical equation for synthesizing the target MOFs material from the elemental substances of the constituent elements of the target MOFs material, the energy of the elemental substances, and the compound energy.

[0071] S104. If the target MOF material has an existing structure, calculate the formation energy of the target MOF material based on the existing chemical equation for synthesizing the target MOF material and the energies of the reactants and products of the existing chemical equation, where the energy of the products includes the energy of the compound.

[0072] S105. Produce a second input parameter file for the target MOF material model for density of states calculation.

[0073] S106. Run the density of states calculation command in the DFTB+ software to read the second structure file and the second input parameter file and perform the density of states calculation, and visualize the density of states calculation results to obtain the density of states diagram of the geometrically optimized target MOF material model.

[0074] S107. Analyze the target MOF material based on the unit cell parameters, formation energy, and density of states diagram.

[0075] In step S101, the target MOF material model can be a computer modeling model of the MOF material to be analyzed, which is reflected by the first structure file. The first structure file can be obtained by constructing the target MOF material model in chemical calculation software. In addition, it is also possible to download the structural data of the existing target MOF material model from a database and obtain the first structure file through preprocessing. For example, it is possible to download the cif format crystal structure data file of the corresponding target MOF material from the Cambridge Crystallographic Data Centre (CCDC), remove the solvent coordinated with metal ions to generate a reasonable input structure for calculation, and then convert the cif format crystal structure data file after removing solvation into the gen format recognizable by the DFTB+ software to obtain the first structure file. For example, when the target MOF material is Mg-MOF-74, the cif file with the CCDC number 1863524 of this material can be downloaded from the CCDC, and after removing the solvent coordinated with metal ions, it can be converted into the gen format using a self-written script, and this gen format file can be used as the first structure file.

[0076] The input parameter file includes the first input parameter file, the second input parameter file, the third input parameter file, and the fourth input parameter file, which can be an hsd format input parameter file, and records multiple parameter settings for simulation calculation.

[0077] In step S101, produce the first input parameter file as a preparation file for geometric optimization of the target MOF material model in the DFTB+ software, and write the calculation parameter settings required for geometric optimization in the first input parameter file.

[0078] Optionally, in step S101, a first input parameter file for geometric optimization of the target MOFs material model is created, including:

[0079] S1011, create a first initial file in hsd format.

[0080] S1012, write the Geometry module in the first initial file, and set the object of geometric optimization to the first structure file in this module.

[0081] S1013, write the Driver module in the first initial file, and in this module, set the calculation type to geometric optimization, set to enable full lattice optimization and use a rational function optimizer, set the maximum number of optimization steps to any step between 100 and 200 steps, and set the convergence criterion to that the gradient element GradElem is less than 1e-4.

[0082] S1014, write the Hamiltonian module in the first initial file, and in this module, set to enable self-consistent charge calculation, and the convergence value and maximum number of iterations of this calculation are 1e-6 and 2000 times respectively, set the Slater-Koster parameters to use the 3OB parameter set, set the maximum angular momentum quantum number of each element of the target MOFs material model, and set the k-point sampling in the Brillouin zone to use the Monkhorst-Pack method and only select the Γ point as the k-point sampling point.

[0083] S1015, write the Analysis module in the first initial file, and set the calculation attributes in this module.

[0084] S1016, write the ParserOptions module in the first initial file, and set the parser version in this module, and finally obtain the first input parameter file for geometric optimization of the target MOFs material model.

[0085] In step S1011, a blank first initial file in hsd format can be created first, and then the corresponding parameter settings are written. After step S1011 is executed, steps S1012 to S1016 are executed. Steps S1012 to S1016 are all to write the corresponding modules in the first initial file. The execution order of this application is not limited. After all modules are written, the first input parameter file can be obtained.

[0086] In step S1012, write the Geometry module into the first initial file. Through this module, set the object of the geometric optimization simulation calculation as the first structure file. For example, the file name of the first structure file in gen format can be directly introduced to specify that the geometric optimization object is the first structure file, or the structure parameters in the first structure file can be copied into the Geometry module to complete the setting of the geometric optimization object.

[0087] In step S1013, write the Driver module into the first initial file. Through this module, specify that the simulation calculation performed on the first structure file is geometric optimization, and optimize the ground state structure of the target MOFs material model by the full geometric optimization method to obtain a structure with fully relaxed atomic positions and lattice parameters without applying any symmetry constraints.

[0088] To improve the calculation accuracy, in the module, turn on the lattice optimization through the code "LatticeOpt = Yes", and set the use of the rational function optimizer (Rational Optimizer) for full lattice optimization through the code "Optimizer = Rational{}", which can effectively handle complex systems containing a large number of atoms. By setting the maximum number of optimization steps between 100 and 200 steps in the module, for example, 150 steps, and setting the convergence criterion as the gradient element GradElem less than 1e-4, the setting of the geometric optimization termination condition is achieved. In addition, other contents can also be set in the module. For example, the file name of the file output after the geometric optimization calculation can be set, etc. This application does not make specific restrictions on this.

[0089] In step S1014, write the Hamiltonian module into the first initial file. Through this module, write the parameter settings for the DFTB operation. Specifically, the self-consistent charge operation can be turned on in this module through the code "Scc=Yes" to obtain an accurate electronic structure, and set the convergence value of the self-consistent charge calculation as 1e-6, indicating that the calculation stops when the charge density converges to 1e-6, and set the maximum number of iterations of the self-consistent charge calculation as 2000, indicating that at most 2000 self-consistent iterative calculations are performed.

[0090] The Slater-Koster parameters are model parameters that describe the transition of electrons between atoms, and they play a crucial role in the calculation and simulation of electronic structures. The Slater-Koster parameter file set contains multiple files recording the Slater-Koster parameters, and each Slater-Koster parameter file can correspond to a pair of elements of a set of molecular structures. Since the geometric optimization operation of the DFTB+ software requires the use of Slater-Koster parameters, for MOF materials, the 3OB parameter set can be set in the Hamiltonian module, which provides a good balance between computational efficiency and accuracy.

[0091] In the Hamiltonian module, it is also possible to set the maximum angular momentum quantum number for the constituent elements of the target MOF material, that is, to define the orbital type used for each element. Taking the aforementioned Mg-MOF-74 as an example, it can be set that the magnesium element (Mg) uses the p orbital, the hydrogen element (H) uses the s orbital, the carbon element (C) uses the p orbital, and the oxygen element (O) uses the p orbital, which can be achieved through the MaxAngularMomentum sub-module of the Hamiltonian module. Since the primitive unit of MOF materials generally has many elements and the structure is relatively complex, for example, the total number of atoms in Mg-MOF-74 is 162, so the k-point sampling in the Brillouin zone can be set to use the Monkhorst-Pack method in the Hamiltonian module, and only the Γ point is selected as the k-point sampling point. The Monkhorst-Pack method is a commonly used k-point grid generation method for calculating supercells. By generating a uniform k-point grid to sample the Brillouin zone, the computational accuracy can be improved. The relatively large periodic unit of MOF materials makes sampling at the Γ point sufficient to accurately describe its electronic structure, and in this way, the computational efficiency can also be improved. Specifically, it can be achieved in the KPointsAndWeights sub-module of the Hamiltonian module.

[0092] In step S1015, the Analysis module can be written in the first initial file. The Analysis module can be used to configure and control how to analyze the calculation results and calculation properties. For example, "CalculateForces = Yes" can be written to set the calculation properties. This module provides users with a variety of options to extract important information from the simulation results and further process and analyze the calculation data. Through this module, users can select which calculation properties need to be analyzed or extracted and generate relevant result outputs.

[0093] In step S1016, the ParserOptions module can be written into the first initial file. For example, the parser version can be set by the command "ParserVersion = 14". After all the above settings are written into the first initial file, the first input parameter file for geometric optimization of the target MOFs material model is finally obtained.

[0094] After step S101 is executed, step S102 can be entered. In step S102, the geometric optimization command can be run in the DFTB+ software. The DFTB+ software running command reads the first structure file and the first input parameter file, and performs geometric optimization simulation calculations on the target MOFs material model in the first structure file based on the settings in the first input parameter file. After the calculation is completed, a second structure file is obtained, and the second structure file contains the geometrically optimized target MOFs material model. In addition, after the calculation is completed, the compound energy and unit cell parameters of the target MOFs material model can also be obtained. The unit cell parameters include the edge length and angle of the unit cell. For example, for Mg-MOF-74, the calculated compound energy is -8688.13 eV, and the unit cell parameters can be seen in Table 1. The geometrically optimized model can be seen in Figure 2 。

[0095] Table 1 Unit cell parameter table of Mg-MOF-74

[0096]

[0097] After step S102 is executed, step S103 or step S104 is entered. If the target MOFs material is a newly designed structure and there is no current experimental synthesis route, step S103 can be entered. Optionally, in step S103, the formation energy of the target MOFs material is calculated based on the theoretical chemical equation for synthesizing the target MOFs material from the elemental substances of the composition elements of the target MOFs material, the energy of the elemental substances, and the compound energy, including:

[0098] S1031, determining all the elemental substances of the composition elements of the target MOFs material based on the chemical formula of the target MOFs material.

[0099] S1032, determining the reaction formula for generating the target MOFs material using all the elemental substances and balancing it to obtain the theoretical chemical equation.

[0100] S1033, calculating the energy of all the elemental substances.

[0101] S1034, multiplying the product of the compound energy and the stoichiometric coefficient of the target MOFs material in the theoretical chemical equation, and subtracting the product of the energy of each elemental substance and its stoichiometric coefficient in the theoretical chemical equation to obtain the formation energy.

[0102] In step S1031, first determine the simple substances of the constituent elements according to the chemical formula of the target MOFs material. Continuing with the previous example, assume that Mg-MOF-74 is the newly designed structure with the chemical formula C 72 H 18 O 54 Mg 18 , it can be determined that the simple substances of its constituent elements are C, H2, O2, and Mg respectively.

[0103] After step S1031 is completed, step S1032 can be executed. In step S1032, determine the reaction formula for generating the target MOFs material using all the simple substances and balance it to obtain the theoretical chemical equation, that is, the reaction formula for theoretically generating the target MOFs material using simple substances. Through this theoretical chemical equation, the stoichiometric coefficients of the reactants and products can be determined, that is, the coefficients in front of the substances participating in the reaction in the chemical reaction equation, to provide data for subsequent calculations. Continuing with the previous example, the theoretical chemical equation for generating Mg-MOF-74 using C, H2, O2, and Mg can be:

[0104] 18Mg + 27O2 + 72C + 9H2 → C 72 H 18 O 54 Mg 18 (1)

[0105] After step S1032 is completed, step S1033 can be executed. In step S1033, calculate the energies of all simple substances. In step S1033, calculating the energies of all simple substances can include:

[0106] S10331. For each simple substance, obtain the third structure file of the simple substance and create the third input parameter file for geometric optimization of the simple substance.

[0107] S10332. Run the geometric optimization command in the DFTB+ software to read the third structure file and the third input parameter file and perform geometric optimization simulation to obtain the energy of each geometrically optimized simple substance.

[0108] In step S10331, for each simple substance, first obtain the third structure file of the simple substance and create the third input parameter file for geometric optimization. The specific execution process can refer to step S101.

[0109] For example, the model of a simple substance can be constructed by chemical modeling software and converted into the gen format to obtain the third structure file, or the existing model structure file can be directly downloaded from the database to achieve acquisition. Since the third input parameter file is also used for geometric optimization, reference can be made to the description of the production process of the first input parameter file in step S101. By creating a new hsd format file and writing multiple settings, the third input parameter file can be obtained. The module settings can also refer to the first input parameter file, using the same module, and still using a rational function optimizer, using the 3OB parameter set, etc. The k-point sampling in the Brillouin zone can still use the Monkhorst-Pack method, and only the Γ point is selected as the k-point sampling point. The difference is that for the third input parameter file of each simple substance, the orbital type setting for the constituent elements only includes the elements of the simple substance.

[0110] After step S10331 is executed, step S10332 can be entered. In step S10332, by running the command for geometric optimization in the DFTB+ software, the software reads the third structure file and the third input parameter file of each simple substance, and performs geometric optimization simulation calculations on the simple substance model of the third structure file based on the settings of the third input parameter file. After the calculation is completed, the energy of the geometrically optimized simple substance model can be obtained. For example, for Mg-MOF-74, the energy of the simple substance after the calculation is completed can be seen in Table 2. Of course, in other possible implementation manners, other methods can also be used to calculate the energy of the simple substance, and the present application does not make specific limitations on this.

[0111] Table 2 Total energy of Mg-MOF-74 and energies of C, O2, H2 and Mg

[0112]

[0113] After step S1033 is executed, step S1034 is entered. In step S1034, based on the theoretical chemical equation, the energy of the product is subtracted from the energy of the reactant to obtain the formation energy, that is, the product of the compound energy of the target MOFs material and the stoichiometric coefficient of the target MOFs material in the theoretical chemical equation is subtracted from the product of the first energy of each simple substance in the theoretical chemical equation. The first energy product is the product of the energy of the simple substance and the stoichiometric coefficient of the simple substance in the theoretical chemical equation.

[0114] Continuing with the previous example, for Mg-MOF-74, referring to Table 2 and the theoretical chemical equation (1), its formation energy can be calculated by the formula E = -8688.13 - (-38.06)×72 - (-18.3)×9 - (-9.4)×18 - (-175.5)×27.

[0115] If the target MOF material has an existing structure, that is, there is currently a synthetic path that can be experimentally synthesized, then the execution can proceed to step S104. Optionally, in step S104, if the target MOF material has an existing structure, calculate the formation energy of the target MOF material based on the existing chemical equation for synthesizing the target MOF material and the energies of the reactants and products of this existing chemical equation, including:

[0116] S1041. Obtain the existing chemical equation for synthesizing the target MOF material.

[0117] S1042. Calculate the energies of all reactants and all products except the target MOF material in the existing chemical equation.

[0118] S1043. Multiply the energy of the compound by the stoichiometric coefficient of the target MOF material in the existing chemical equation, add the product of the energy of each product except the target MOF material and its stoichiometric coefficient in the existing chemical equation, and subtract the product of the energy of each reactant and its stoichiometric coefficient in the existing chemical equation to obtain the formation energy.

[0119] In step S1041, obtain the existing chemical equation for synthesizing the target MOF material, that is, the actually achievable synthetic path. Taking Mg-MOF-74 as an example, select the following existing chemical equation for it:

[0120] 18MgO + 9C8H6O6 → C 72 H 18 O 54 Mg 18 + 18H2O (2)

[0121] After step S1041 is completed, proceed to execute step S1042. In step S1042, calculate the energies of all reactants and products in the existing chemical equation, except that the energy of the compound of the target MOF material has been calculated. Optionally, in step S1042, calculate the energies of all reactants and all products except the target MOF material in the existing chemical equation, including:

[0122] S10421. For each reactant and each product except the target MOF material in the existing chemical equation, obtain the fourth structure file of this reactant or product, and create a fourth input parameter file for geometric optimization.

[0123] S10422. Run the geometric optimization command in the DFTB+ software to read the fourth structure file and the fourth input parameter file and perform geometric optimization simulation to obtain the energies of each optimized reactant and each optimized product.

[0124] In step S10421, for each reactant in the existing chemical equation and each product other than the target MOF material, the fourth structure file can be obtained by constructing a model or downloading from an existing database, and the fourth input parameter file for its geometry optimization can be made. Specifically, reference can be made to the description of step S10331, with the difference being that for the fourth input parameter file of each reactant or product, the orbital type setting for the constituent elements only includes the constituent elements of that reactant or product.

[0125] After step S10421 is completed, step S10422 is executed. In step S10422, by running the command for geometry optimization in the DFTB+ software, the software reads the fourth structure file and the fourth input parameter file of each reactant or product, and performs a geometry optimization simulation calculation on the model of the fourth structure file based on the settings of the fourth input parameter file. After the calculation is completed, the energies of the reactants and products after geometry optimization can be obtained. For example, for the existing chemical equation (2), the calculation of the energies of the reactants and products can be seen in Table 3. Of course, in other possible implementation manners, other methods can also be used to calculate the energies of the reactants and products, and the present application does not make specific limitations thereto.

[0126] Table 3 Energy table of Mg-MOF-74 total energy and the energies of C8H6O6, MgO, and H2O

[0127]

[0128] After step S1042 is completed, step S1043 is executed. In step S1043, the product of the compound energy of the target MOF material multiplied by its stoichiometric number in the existing chemical equation is added to the sum of the products of the energies of each product, and then the sum of the products of the energies of each reactant is subtracted from this sum to obtain the formation energy. The product of the energy of the product is the product of the energy of the product and its stoichiometric number in the existing chemical equation, and the product of the energy of the reactant is the product of the energy of the reactant and its stoichiometric number in the existing chemical equation.

[0129] Continuing with the aforementioned example, for Mg-MOF-74, referring to Table 3 and the existing chemical equation (2), its formation energy can be calculated by the formula E = -8688.13 + (-110.45)×18 - (-99.3)×18 - (-975.17)×9.

[0130] After obtaining the formation energy, step S105 can be entered. In step S105, a second input parameter file is made for the density of states calculation of the target MOFs material model. Optionally, in step S105, making the second input parameter file for the density of states calculation of the target MOFs material model includes:

[0131] S1051, create a second initial file in hsd format.

[0132] S1052, write the Geometry module in the second initial file, and in this module, set the object for density of states calculation to the second structure file.

[0133] S1053, write the Hamiltonian module in the second initial file, and in this module, set to turn on the self-consistent charge calculation with a convergence value of 1e-5 for this calculation, set the maximum angular momentum quantum number for each element of the target MOFs material model, and set the k-point sampling density in the Brillouin zone to a grid of 8×8×8.

[0134] S1054, write the Analysis module in the second initial file, and in this module, set the projection region for the density of states calculation of each element of the target MOFs material model.

[0135] S1055, write the ParserOptions module in the second initial file, and in this module, set the parser version, and finally obtain the second input parameter file for the density of states calculation of the target MOFs material model.

[0136] In step S1051, create a second initial file in hsd format, the initial content of which can be empty, and then corresponding parameter settings can be written. After step S1051 is executed, steps S1052 to S1055 are entered. Steps S1052 to S1055 are all to write corresponding module settings in the second initial file. The present application does not limit the execution order thereof. After all modules are written, the second input parameter file can be obtained.

[0137] In step S1052, write the Geometry module in the second initial file. Through this module, set the object for density of states calculation to the second structure file. For example, the file name of the second structure file in gen format can be directly introduced to specify that the object for density of states calculation is the second structure file, or the structure parameters in the second structure file can be copied to the Geometry module to complete the setting of the object for density of states calculation.

[0138] In step S1053, writing the Hamiltonian module into the second initial file allows enabling the self-consistent charge calculation in this module and setting the convergence value of this calculation to 1e-5. In this way, the charge density will be automatically updated in each calculation until the change in the charge density in each calculation is less than this value, at which point the self-consistent calculation is considered to have converged. In a possible implementation, this module may include two sub-modules, MaxAngularMomentum and KPointsAndWeights. Through the MaxAngularMomentum sub-module, the maximum angular momentum quantum number of each constituent element of the target MOFs material can be set, which is achieved by defining the orbital type adopted for each element. Continuing with the previous example, for Mg-MOF-74, it can be set that the magnesium element (Mg) adopts the p orbital, the hydrogen element (H) adopts the s orbital, the carbon element (C) adopts the p orbital, and the oxygen element (O) adopts the p orbital. Additionally, the 8×8×8 grid with a higher k-point density can be set as the k-point sampling density of the Brillouin zone through the KPointsAndWeights sub-module. For example, the KPointsAndWeights sub-module can be set as follows:

[0139] KPointsAndWeights = SupercellFolding{ 8 0 0 0 8 0 0 0 8 0.5 0.5 0.5

[0144] }

[0145] In step S1054, the Analysis module can be continuously written into the second initial file to create a projection region for each element (such as Mg, H, C, O of Mg-MOF-74), and the density of states calculation for different elements is performed within this region. Specifically, the ProjectStates sub-module can be set in this module, and multiple Region sub-sub-modules are written in this sub-module to create projection regions for each element.

[0146] In step S1055, the ParserOptions module can be continuously written into the second initial file. For example, the parser version can be set through the command "ParserVersion = 12". After all the above settings are written into the second initial file, the second input parameter file for the density of states calculation of the target MOFs material model is finally obtained.

[0147] After step S105 is completed, step S106 can be executed. In step S106, a density of states calculation command can be run in the DFTB+ software. The DFTB+ software running command reads the second structure file and the second input parameter file, and performs a density of states calculation on the target MOFs material model of the second structure file based on the settings of the second input parameter file. After the calculation is completed, the density of states calculation results can be visualized to obtain a density of states graph. For example, a density of states graph can be plotted using a visualization tool such as python. See Figure 3 , taking Mg-MOF-74 as an example, the density of states graph can show the total density of states (TDOS) and the partial density of states (PDOS) of the Mg-MOF-74 equilibrium structure. The total density of states is used to represent the distribution of all electron states of the target MOFs material such as Mg-MOF-74 in the energy space, and the partial density of states is used to represent the contribution of elements of specific atomic orbitals to the total density of states.

[0148] The density of states, or the density of electronic states (DOS), describes the distribution of electronic states in the energy space. The density of states can give information such as the interaction between local partial wave orbitals, the energy level shift and energy level dispersion of electronic states, and can be directly used to analyze doping effects, etc. In the calculation, the density of states can intuitively give the electron energy spectrum obtained according to the k vector along the high-symmetry direction in the Brillouin zone, giving us all kinds of information we want. Therefore, its status is very important. The density of states (DOS) can represent the ratio of the number of electrons at the corresponding energy. Having a peak at a certain energy level means that there are more electrons distributed here. The abscissa of the density of states graph is energy, and the ordinate represents the relative quantity, which is a relative value. It is very helpful for revealing the interaction between atomic orbitals and the information of the energy level shift of electrons.

[0149] After step S106 is completed, step S107 can be executed. In step S107, the target MOFs material can be analyzed in terms of its material structure characteristics, stability, and electronic behavior, etc. based on the unit cell parameters, formation energy, and density of states graph obtained from the previous steps. Optionally, in step S107, analyzing the target MOFs material based on the unit cell parameters, formation energy, and density of states graph includes:

[0150] S1071, analyzing the shape and size of the unit cell of the target MOFs material based on the unit cell parameters.

[0151] S1072, when the target MOFs material is a newly designed structure, if the formation energy is greater than 0, it is determined that the target MOFs material cannot be formed by a spontaneous reaction.

[0152] S1073. When the target MOF material has an existing structure, determine one or more existing chemical equations with the minimum formation energy for experimental verification.

[0153] S1074. Perform a total density of states analysis and a partial density of states analysis on the target MOF material based on the density of states diagram.

[0154] In step S1071, the unit cell parameters (including the edge lengths a, b, c of the unit cell and the angles α, β, γ of the unit cell) are the basic geometric parameters characterizing the crystal structure. Through them, not only can the shape, size, and volume of the unit cell be accurately determined, but also the seven crystal systems (such as cubic, hexagonal, orthorhombic, etc.) to which the crystal belongs can be judged based on their numerical relationships, and further the space group symmetry can be deduced. These parameters provide the core basis for material structure analysis and can be further used for calculations such as atomic packing density.

[0155] After step S1071 is completed, step S1072 or step S1073 can be executed. If the target MOF material is a newly designed structure, step S1072 can be entered. In step S1072, analyze the stability of the MOF material with the newly designed structure according to the formation energy. If its formation energy is greater than 0, it means its stability is poor and it cannot be formed through a spontaneous reaction, and additional driving forces (such as high temperature, high pressure, or a catalyst) are needed, which makes its synthesis more complex and consumes more. In some cases, MOF structures with similar performance but lower formation energy may be screened, and further research on MOF materials with a formation energy greater than 0 may be abandoned. If the formation energy is less than 0, the stability of the target MOF material is good. If its performance in other aspects also meets the requirements, it can be included in further research, such as research in the experimental stage.

[0156] If the target MOF material has an existing structure, step S1073 can be entered. In step S1073, there may be one or more synthesis paths for the target MOF material. When there are multiple synthesis paths, the formation energies corresponding to multiple synthesis paths can be calculated according to the previous steps, and then select one or more existing chemical equations corresponding to the synthesis paths with the minimum formation energy and further verify and analyze them in experiments. If there is only one synthesis path, the existing chemical equation corresponding to this synthesis path can be directly used for experimental verification and analysis.

[0157] After step S1072 or step S1073 is completed, step S1074 can be entered. In step S1074, a total density of states analysis and a partial density of states analysis can be performed according to the density of states diagram. See Figure 3 , whose abscissa is energy and ordinate is the density of states DOS. Taking Mg-MOF-74 as an example, its total density of states (TDOS) can be seen in Figure 3For the fluctuation curve data corresponding to DOS in the middle, the partial density of states (PDOS) can be Figure 3 characterized by the fluctuation curve regions of the respective orbitals of the C, H, Mg, and O elements corresponding thereto in the middle, showing the specific contributions of different atomic orbitals to the total density of states.

[0158] See Figure 3 , in Mg-MOF-74, there is no obvious DOS crossing the Fermi level, indicating that Mg-MOF-74 is a semiconductor. The PDOS of Mg-MOF-74 can characterize the distribution of various electronic states in the valence band. The p-states and s-states of Mg, O, and C atoms mainly contribute to the valence band (VB). At the same time, there are three internal gaps in Mg-MOF-74: upper (0 - 6 eV), (8 - 12 eV), and lower (-6 - -12 eV). Studies have shown that Mg atoms make important contributions to the electronic states above the higher gap (>8 eV), O atoms make great contributions below the lower internal gap (<-6 eV), and near the Fermi level (E = 0 eV), considering the valence band, C atoms dominate the contribution to the electronic states.

[0159] Through the above technical solution, for the target MOFs material model to be analyzed, obtain its first structure file and make its first input parameter file, and perform geometric optimization simulation by reading the first structure file and the first input parameter file through DFTB+ to optimize the geometry of the target MOFs material model and obtain the compound energy and unit cell parameters. For different situations of the target MOFs material, if it is a newly designed structure, calculate the formation energy based on the theoretical chemical equation, elemental energy, and compound energy of the synthesis of the constituent elements; if it is an existing structure, calculate the formation energy based on the existing chemical equation, reactant, and product energies. Finally, make the second input parameter file, and use DFTB+ to read this file and the second structure file of the geometrically optimized target MOFs material model to perform density of states calculation and visualize to obtain the density of states diagram. After the operation is completed, the target MOFs material can be analyzed based on the calculated unit cell parameters, formation energy, and density of states diagram. Thus, the simulation calculation and analysis of MOFs materials are realized based on the open-source and free software DFTB+, which can provide more data support for screening MOFs materials, improve the screening efficiency, and reduce the time and cost of screening.

[0160] Molecular simulation technology provides atomic-level thermodynamic and kinetic data for the study of MOF materials, which are difficult to obtain through experiments. Through simulation, researchers can obtain more accurate structural, energy, and performance information in highly symmetric and complex systems, thus making up for the limitations of experimental research. In addition, molecular simulation has significant advantages in large-scale material screening. It can complete a large number of computational screenings in a short time, greatly improving the research efficiency and reducing costs. Compared with traditional experimental screening methods, molecular simulation can not only verify experimental phenomena but also provide a theoretical basis for the phenomena, providing support for the performance optimization of MOFs and the design of new materials. The results of molecular simulation can be a powerful supplement to experimental data. By comparing with experimental results, it can verify experimental phenomena and provide a theoretical basis for experimental results. Especially when it is difficult to obtain some complex data through experiments, DFTB+ can provide a feasible computational approach to help explain the experimentally observed phenomena.

[0161] Computational simulation, especially DFTB+, provides powerful technical support for the structural optimization and performance regulation of MOF materials. The high crystallinity and symmetry of MOFs enable the accurate characterization of atomic positions, reducing computational uncertainty and thus improving the accuracy of simulation. With the help of advanced computational hardware and software, simulation methods can optimize structures and properties based on low-resolution experimental data and obtain more reliable parameters. This not only enhances the understanding of MOF materials but also provides a solid theoretical support for their applications in the fields of energy storage, catalysis, adsorption, etc. Since DFTB+ is an approximation method based on density functional theory, it can significantly reduce the computational cost while maintaining a relatively high computational accuracy. This advantage is particularly important for the screening and study of a large number of different MOF structures, enabling efficient computational exploration without sacrificing accuracy.

[0162] Figure 4 is a block diagram of an electronic device shown according to an exemplary embodiment. As Figure 4 shown, the electronic device 700 may include: a processor 701, a memory 702. The electronic device 700 may further include one or more of a multimedia component 703, an input / output (I / O) interface 704, and a communication component 705.

[0163] Among them, the processor 701 is used to control the overall operation of the electronic device 700 to complete all or part of the steps in the above-mentioned MOFs material structure performance analysis method. The memory 702 is used to store various types of data to support the operation of the electronic device 700. These data may include, for example, instructions for any application or method operating on the electronic device 700, as well as application-related data, such as contact data, sent and received messages, pictures, audio, video, and so on. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disc. The multimedia component 703 may include a screen and an audio component. The screen may be a touch screen, for example, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 702 or sent through the communication component 705. The audio component further includes at least one speaker for outputting audio signals. The I / O interface 704 provides an interface between the processor 701 and other interface modules, and the other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them is not limited herein. Therefore, the corresponding communication component 705 may include: a Wi-Fi module, a Bluetooth module, an NFC module, and so on.

[0164] In an exemplary embodiment, the electronic device 700 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above-mentioned MOFs material structure performance analysis method.

[0165] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When the program instructions are executed by a processor, the steps of the above-mentioned MOFs material structure performance analysis method are implemented. For example, the computer-readable storage medium may be the above-mentioned memory 702 including program instructions, and the above-mentioned program instructions may be executed by the processor 701 of the electronic device 700 to complete the above-mentioned MOFs material structure performance analysis method.

[0166] The preferred embodiments of the present application have been described in detail above in conjunction with the accompanying drawings. However, the present application is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present application, various simple modifications can be made to the technical solutions of the present application, and these simple modifications all belong to the protection scope of the present application.

[0167] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any suitable manner without conflict. To avoid unnecessary repetition, the present application does not separately describe various possible combination methods.

[0168] Furthermore, any combination can be made between the various different embodiments of the present application as long as it does not violate the idea of the present application, and it should also be regarded as the content recorded in the present application.

Claims

1. A method for analyzing the structural properties of MOFs materials, characterized in that, The method includes: Obtaining a first structure file of the target MOFs material model and creating a first input parameter file for the geometric optimization of the target MOFs material model; Running a geometric optimization command in the DFTB+ software to read the first structure file and the first input parameter file and perform geometric optimization simulation, obtaining a second structure file, the compound energy, and the unit cell parameters of the geometrically optimized target MOFs material model; If the target MOFs material is a newly designed structure, calculating the formation energy of the target MOFs material based on the theoretical chemical equation for synthesizing the target MOFs material from the constituent element simple substances of the target MOFs material, the energy of the simple substances, and the compound energy; If the target MOFs material is an existing structure, calculating the formation energy of the target MOFs material based on the existing chemical equation for synthesizing the target MOFs material, the energies of the reactants and products in the existing chemical equation, where the energy of the product includes the compound energy; Creating a second input parameter file for the density of states calculation of the target MOFs material model; Running a density of states calculation command in the DFTB+ software to read the second structure file and the second input parameter file and perform density of states calculation, and visualizing the density of states calculation results to obtain the density of states diagram of the geometrically optimized target MOFs material model; Analyzing the target MOFs material based on the unit cell parameters, the formation energy, and the density of states diagram.

2. The method according to claim 1, characterized in that, The calculating the formation energy of the target MOFs material based on the theoretical chemical equation for synthesizing the target MOFs material from the constituent element simple substances of the target MOFs material, the energy of the simple substances, and the compound energy includes: Determining the simple substances of all constituent elements of the target MOFs material based on the chemical formula of the target MOFs material; Determining the reaction equation for generating the target MOFs material using all the simple substances and balancing it to obtain the theoretical chemical equation; Calculating the energy of all the simple substances; Multiplying the compound energy by the product of the stoichiometric coefficients of the target MOFs material in the theoretical chemical equation, subtracting the product of the energy of each simple substance and the stoichiometric coefficient of the simple substance in the theoretical chemical equation, to obtain the formation energy.

3. The method according to claim 1, wherein The calculating the formation energy of the target MOFs material based on the existing chemical equation for synthesizing the target MOFs material, the energies of the reactants and products in the existing chemical equation includes: Obtaining the existing chemical equation for synthesizing the target MOFs material; Calculating the energies of all reactants and all products except the target MOFs material in the existing chemical equation; Multiplying the compound energy by the product of the stoichiometric coefficients of the target MOFs material in the existing chemical equation, adding the product of the energy of each product except the target MOFs material and the stoichiometric coefficient of the product in the existing chemical equation, and subtracting the product of the energy of each reactant and the stoichiometric coefficient of the reactant in the existing chemical equation, to obtain the formation energy.

4. The method according to claim 2, characterized in that, The calculating the energy of all the simple substances includes: For each simple substance, obtaining a third structure file of the simple substance and creating a third input parameter file for the geometric optimization of the simple substance; Run the geometry optimization command in the DFTB+ software to read the third structure file and the third input parameter file and perform a geometry optimization simulation to obtain the energy of each single substance after geometry optimization.

5. The method according to claim 3, characterized in that, Calculate the energies of all reactants and all products except the target MOF materials in the existing chemical equation, including: For each reactant and each product except the target MOF materials in the existing chemical equation, obtain the fourth structure file of the reactant or product and create a fourth input parameter file for geometry optimization; Run the geometry optimization command in the DFTB+ software to read the fourth structure file and the fourth input parameter file and perform a geometry optimization simulation to obtain the energies of each of the reactants and each of the products after geometry optimization.

6. The method according to claim 1, characterized in that, Create the first input parameter file for geometry optimization of the target MOF material model, including: Create a new first initial file in hsd format; Write the Geometry module in the first initial file and set the object of geometry optimization to the first structure file in this module; Write the Driver module in the first initial file and set the calculation type to geometry optimization, set to enable full lattice optimization and use a rational function optimizer, set the maximum number of optimization steps to any step between 100 and 200 steps, and set the convergence criterion to GradElem of the gradient element less than 1e-4; Write the Hamiltonian module in the first initial file and set to enable self-consistent charge calculation, and the convergence value and maximum number of iterations of this calculation are 1e-6 and 2000 times respectively, set the Slater-Koster parameters to use the 3OB parameter set, set the maximum angular momentum quantum number of each element of the target MOF material model, set the k-point sampling in the Brillouin zone to use the Monkhorst-Pack method and only select the Γ point as the k-point sampling point; Write the Analysis module in the first initial file and set the calculation properties in this module; Write the ParserOptions module in the first initial file and set the parser version in this module, and finally obtain the first input parameter file for geometry optimization of the target MOF material model.

7. The method according to claim 1, wherein Create the second input parameter file for density of states calculation of the target MOF material model, including: Create a new second initial file in hsd format; Write the Geometry module in the second initial file and set the object of density of states calculation to the second structure file in this module; Write the Hamiltonian module in the second initial file and set to enable self-consistent charge calculation and the convergence value of this calculation is 1e-5, set the maximum angular momentum quantum number of each element of the target MOF material model, and set the k-point sampling density in the Brillouin zone to a grid of 8×8×8; Write the Analysis module in the second initial file and set the projection region for density of states calculation of each element of the target MOF material model. Write the ParserOptions module in the second initial file, and set the parser version in this module, finally obtaining the second input parameter file for the density of states calculation of the target MOFs material model.

8. The method according to claim 1, wherein The analysis of the target MOFs material based on the unit cell parameters, formation energy, and density of states diagram includes: Analyze the unit cell shape and size of the target MOFs material based on the unit cell parameters; When the target MOFs material is a newly designed structure, if the formation energy is greater than 0, determine that the target MOFs material cannot be formed by a spontaneous reaction; When the target MOFs material is an existing structure, determine one or more existing chemical equations with the minimum formation energy for experimental verification; Perform total density of states analysis and partial density of states analysis on the target MOFs material based on the density of states diagram.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method described in any one of claims 1-8.

10. An electronic device, characterized in that, Including: A memory storing a computer program thereon; A processor for executing the computer program in the memory to implement the steps of the method described in any one of claims 1-8.

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