A high-throughput screening method and system for multinary thermoelectric materials

Abstract

The application discloses a high-throughput screening method of a multimer thermoelectric material. First, semiconductor materials are screened from public materials according to structural complexity, experimental synthesis literature and an electronic band gap; then, the sulfide cluster semiconductor materials are further screened according to the screening method; then, the sulfide cluster semiconductor materials are subjected to mechanical and dynamic stability determination by using first principle calculation, so that the materials stable at room temperature are determined; then, the second-order and third-order interatomic force constants of the stable materials are obtained by using the first principle calculation, and the materials have super-low lattice thermal conductivity by using the phonon Boltzmann transport equation; finally, the target multimer thermoelectric material meeting the requirements is found by calculating the electric transport parameters. The target material system can be quickly obtained by using the high-throughput screening method combined with the first principle calculation.

Description

Technical Field

[0001] The present invention relates to the technical field of energy conversion material screening, and in particular to a high-throughput screening method and system for polymer thermoelectric materials. Background Art

[0002] Faced with the demand for new renewable energy sources and the need to manage waste heat in industry and everyday life, thermoelectric materials that convert heat into electricity have garnered widespread attention. Thermoelectric devices offer advantages such as small size, quiet operation, long lifespan, and high reliability, making them widely used in fields such as medicine, military, and aerospace. These advantages include applications in micro-thermostats, automotive lidar, 5G communications, and body-temperature-generating watches. However, since their discovery, thermoelectric materials have typically had conversion efficiencies ranging from 5% to 20%. This low conversion efficiency has limited their practical applications. Therefore, improving the thermoelectric performance of these materials is crucial for the development of thermoelectric functional devices.

[0003] Thermoelectric figure of merit provides information about the relationship between the electrical and thermal properties of a material, and can also be used to evaluate the thermoelectric performance of a material. A good thermoelectric figure of merit requires a large Seebeck coefficient (S), high electrical conductivity ( ) and low thermal conductivity ( ). Therefore, the two main ways to improve thermoelectric conversion efficiency are to optimize electrical transport performance and reduce lattice thermal conductivity. Due to the mutual coupling of electrical conductivity and Seebeck coefficient, the optimization of electrical transport performance is more difficult. Lattice thermal conductivity can be independently regulated. Therefore, the search for thermoelectric materials with intrinsic low lattice thermal conductivity has become the focus of thermoelectric research. At the same time, such low thermal conductivity materials also play an important role in thermal barrier coating applications. Currently, there are methods based on structural descriptors to obtain material phonon transport properties, such as the single-atom localized vibration model, which can achieve rapid screening of low lattice thermal conductivity materials. However, this ignores the possibility that low thermal conductivity may be caused by the aggregation of similar atoms.

[0004] In recent years, the phonon transport and thermoelectric figure of merit of some chalcogenide-containing aggregates have been studied, such as monolayer CdTe2 and Pd2Se3, but they have the disadvantage of high thermal conductivity, which also leads to a thermoelectric figure of merit of only about 1; subsequently, it is found that the three-dimensional chalcogenide-containing aggregates Ba2X6(X = S, Se, Te), ASe(A = K, Rb) and ZnSe2 have ultra-low lattice thermal conductivity, and some of them show high thermoelectric performance; in general, in the 5G information era, such high-ZT chalcogenide-containing aggregate materials can significantly optimize the thermoelectric conversion efficiency, mainly reflected in the improvement of the heat dissipation and refrigeration power of microelectronic devices in the integrated circuit field and the development of high-efficiency waste heat power generation devices. At the same time, such low-thermal-conductivity chalcogenide-containing aggregate materials can also be applied in thermal barrier coating technology, which can improve the working temperature and service life of the hot end parts of the aero-engine. However, there are still some challenges in determining the best target material, and it is known that thermoelectric conversion devices are mainly composed of one P-type and one N-type material, and a variety of performance-friendly P-type materials have been found, such as SnSe, PbTe and most Heusler alloys; on the contrary, N-type thermoelectric materials with ZT>1 are relatively rare in the market and experimental research, so it is crucial to find a kind of N-type thermoelectric material with ZT>1 for building high-performance thermoelectric conversion devices. At present, the materials project gene database has provided 150,000 crystal structures, and how to quickly obtain the thermoelectric performance of the aggregate material is an important topic worth exploring.

[0005] It is impractical to synthesize and test the thermoelectric performance of 150,000 crystal structures by traditional experimental procedures, mainly because it often takes several days to synthesize and test the performance of only one material, and on the other hand, the gene database does not provide the thermoelectric performance data of the material, and the traditional high-throughput calculation method needs to calculate the basic thermoelectric parameters of 150,000 materials uniformly, although this method can obtain the thermoelectric performance of all materials, but due to the calculation of one material at least needs one day, the calculation cost of this scheme is still very high.

[0006] Therefore, we urgently need an effective screening method to find potential chalcogenide-containing aggregate thermoelectric materials. SUMMARY

[0007] The purpose of the present application is to provide a high-throughput screening method for aggregate thermoelectric materials.

[0008] To solve the above technical problems, the present application provides a high-throughput screening method for aggregate thermoelectric materials, comprising:

[0009] Step S1: According to the target database, a preset number of screening information is extracted, which at least includes the synthesis conditions of inorganic compounds, the number of atoms, and the basic information of the electronic energy band;

[0010] Step S2: Using a semiconductor screening method, the semiconductor material is screened from the preset number of screening information;

[0011] Step S3: Using a sulfur group atom-containing polymer screening method, the sulfur group atom-containing polymer material is screened from the semiconductor material;

[0012] Step S4: According to the sulfur group atom-containing polymer material, the stability is judged and the polymer material judged to be stable is obtained;

[0013] Step S5: According to the stable polymer material, the lattice thermal conductivity is tested and the electrical transport parameters of the polymer material are calculated, and then the thermoelectric performance is evaluated using the thermoelectric merit value, and the target polymer thermoelectric material meeting the preset requirements is obtained.

[0014] In one aspect, in step S2, the method comprises the following steps:

[0015] Step S21: According to the preset number of screening information, the first screening condition is used to screen the semiconductor material that has been synthesized in the experiment;

[0016] Step S22: According to the preset number of screening information, the second screening condition is used to screen the semiconductor material with the number of atoms in the initial unit cell in the first preset interval;

[0017] Step S22: According to the preset number of screening information, the third screening condition is used to screen the semiconductor material with the electronic band gap in the second preset interval, so as to obtain the semiconductor material.

[0018] In one aspect, in step S3, the method comprises the following steps:

[0019] Step S31: Using a first-principles calculation software to optimize the semiconductor material, obtaining the spatial structure information data of the semiconductor material, and then constructing the force field information data and the preset grid density data for each spatial structure contained in the semiconductor material;

[0020] Step S32: In the spatial structure information data of the semiconductor material, the projection augmented plane wave is used to process the electronic wave function and the PBE-GGA exchange correlation functional is used to calculate the electronic structure;

[0021] Step S33: According to the spatial structure information data of each atom in the semiconductor material, the polymer material containing sulfur-sulfur, selenium-selenium, or tellurium-tellurium bond length between the preset multiple of the distance between two atoms in the sulfur, selenium, or tellurium element is calculated, so as to screen the polymer material containing at least two sulfur, selenium, or tellurium atom numbers.

[0022] In one aspect, in step S33, according to the spatial structure information data of each atom in the semiconductor material, the material containing sulfur, selenium or tellurium, and the bond length being between 1.05-1.1 times of the distance between two atoms in the sulfur, selenium or tellurium element is screened as the polymer material.

[0023] In one aspect, in step S4, the method comprises the following steps:

[0024] Step S41: judging the mechanical stability of the material according to the screened polymer material containing at least two sulfur, selenium or tellurium atoms.

[0025] Step S42: judging the dynamic stability of the material according to the screened polymer material containing at least two sulfur, selenium or tellurium atoms, so as to screen the stable polymer material.

[0026] In one aspect, in step S41, the method comprises the following steps:

[0027] Step S411: calculating the elastic constant of the polymer material by using the density functional perturbation theory;

[0028] Step S412: judging whether the elastic constant satisfies the formula:

[0029]

[0030]

[0031]

[0032]

[0033] If yes, it is judged that the polymer material has mechanical stability, and the dynamic stability of the material is judged; if no, it is judged that the polymer material does not have mechanical stability and the polymer material without mechanical stability is screened out.

[0034] In one aspect, in step S42, the method comprises the following steps:

[0035] Step S421: calculating the phonon spectrum of the polymer material with mechanical stability by using the finite displacement method;

[0036] Step S422: judging whether the phonon dispersion curve of the phonon spectrum has imaginary frequency, if yes, it is judged that the polymer material does not have dynamic stability and the polymer material without dynamic stability is screened out; if no, it is judged that the polymer material has dynamic stability and the polymer material with dynamic stability is screened out.

[0037] In one aspect, in step S5, the method further comprises the following steps:

[0038] Step S51: calculating the phonon spectrum of the stable polymer material by using the finite displacement method, and then calculating the second-order atomic interaction force constant according to the phonon spectrum;

[0039] Step S52: obtaining the third-order atomic interaction force constant of the stable polymer material by using the finite displacement method;

[0040] Step S53: solving the phonon Boltzmann transport equation according to the second-order atomic interaction force constant and the third-order atomic interaction force constant to obtain the lattice thermal conductivity of the stable polymer material.

[0041] In one aspect, in step S5, the method further comprises the following steps:

[0042] Step S54: calculating the elastic constant of the stable polymer material by using the density functional perturbation theory;

[0043] Step S55: solving the electrical conductivity, the Seebeck coefficient, and the carrier thermal conductivity using the basic electrical transport parameters of the stable polymer material;

[0044] Step S56: using the thermoelectric figure of merit to evaluate the thermoelectric performance of the stable polymer material, and obtaining a target polymer thermoelectric material that meets the preset requirements; wherein is the electrical conductivity, S is the Seebeck coefficient, is the temperature at which the material works, is the lattice thermal conductivity, is the electronic thermal conductivity.

[0045] The application also provides a high-throughput screening system for polymer thermoelectric materials for performing the high-throughput screening method, comprising:

[0046] A data extraction module is configured to extract a preset number of screening information from a target database, wherein the screening information at least includes the synthesis conditions of inorganic compounds, the number of atoms, and the basic information of the electronic energy band;

[0047] A first screening module is configured to screen out semiconductor materials from the preset number of screening information by using a semiconductor screening method;

[0048] A second screening module is configured to screen out chalcogen atom-containing polymer materials from the semiconductor materials by using a chalcogen atom-containing polymer screening method;

[0049] A characteristic judgment module is configured to perform stability judgment on the chalcogen atom-containing polymer materials and obtain stable polymer materials that are judged to be stable;

[0050] A material evaluation module is configured to perform a lattice thermal conductivity test on the stable polymer material and calculate an electrical transport parameter of the polymer material, and then evaluate the thermoelectric performance using a thermoelectric merit figure, so as to obtain a target polymer thermoelectric material meeting a preset requirement.

[0051] The high-throughput screening method of the present application has the following advantages:

[0052] The present application provides a unique polymer screening method to effectively obtain a super-low thermal conductivity and high-performance thermoelectric material, which enriches thermoelectric materials, greatly reduces the calculation cost, shortens the development cycle of new n-type thermoelectric materials, and provides a theoretical basis for constructing high-performance p-n type thermoelectric materials and promoting commercial thermoelectric devices. These high-ZT polymer thermoelectric materials can improve power generation efficiency, especially in industrial production, automobile engines and power plants, etc. These large amounts of waste heat can be directly recycled, thereby improving energy utilization efficiency and reducing dependence on fossil fuels; at the same time, high-ZT polymer thermoelectric materials can achieve precise temperature control in electronic components and precision instruments. Therefore, screening high-performance polymer thermoelectric materials has important practical significance in environmental protection, energy saving and improving energy utilization efficiency. In addition, the present application uses a polymer model and a high-throughput calculation screening method based on first principles to quickly obtain candidate materials, which is efficient and accurate, does not involve complex experimental processes in the entire process, has a simple operation process, is easy to implement, and is suitable for popularization to other semiconductor materials. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor based on the provided drawings.

[0054] Figure 1 is a flowchart of the high-throughput screening method of the polymer thermoelectric material provided by the embodiments of the present application.

[0055] Figure 2 is a flowchart of the semiconductor material screening method provided by the embodiments of the present application.

[0056] Figure 3 is a flowchart of the chalcogen atom-containing polymer material screening method provided by the embodiments of the present application.

[0057] Figure 4 is a flowchart of the stability judgment method provided by the embodiments of the present application.

[0058] Figure 5This is a flow chart of a method for determining the mechanical stability of a material provided by an embodiment of the present invention.

[0059] Figure 6 It is a flow chart of a method for determining the dynamic stability of a material provided by an embodiment of the present invention.

[0060] Figure 7 4 is a flow chart of a method for calculating lattice thermal conductivity provided by an embodiment of the present invention.

[0061] Figure 8 It is a schematic diagram of the generation of the lattice thermal conductivity material provided by an embodiment of the present invention.

[0062] Figure 9 This is a flow chart of a method for calculating thermoelectric performance provided by an embodiment of the present invention.

[0063] Figure 10 Schematic diagram of the relationship between carrier concentration, temperature and ZT in the polymer material provided by an embodiment of the present invention.

[0064] Figure 11 This is a schematic diagram of module connections of a high-throughput screening system for polymer thermoelectric materials provided by an embodiment of the present invention.

[0065] Description of the accompanying drawings:

[0066] 100. Data extraction module, 101. First screening module, 102. Second screening module, 103. Property judgment module, 104. Material evaluation module. DETAILED DESCRIPTION

[0067] The following describes embodiments of the present invention in detail, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and are not to be construed as limiting the present invention.

[0068] Thermoelectric figure of merit ( ) provides information about the parameters between the electrical and thermal properties of the material, and can also be used to evaluate the thermoelectric properties of the material. A good ZT value requires a large Seebeck coefficient (S), high electrical conductivity ( ) and low thermal conductivity ( ).

[0069] The materials project gene database has published the basic information of materials, mainly including the electronic band gap, the number of atoms, and whether it has been synthesized by experiment; for this purpose, the first step of screening can be carried out using these three conditions, which directly excludes more than 140,000 materials that do not need to be calculated, saving computing resources and shortening the development cycle of new materials; in addition, the existence of ions with large mass and weak chemical bonds in semiconductor materials can lead to low thermal conductivity (1 Wm -1 K -1 ) and improve the thermoelectric performance of ZT>1; since two sulfur (selenium or tellurium) atoms are aggregated together in a covalent bond, they can be regarded as a kind of large mass atom, so in this application, a kind of sulfur (selenium or tellurium) atom multimer model is defined and high-throughput screening is used to obtain such materials, and then for the screened multimer materials, first-principles calculations are used to obtain thermoelectric performance and determine N-type thermoelectric materials with ZT>1.

[0070] Thus, referring to Figure 1 , in some embodiments, a high-throughput screening method of a multimer thermoelectric material is involved, including the following steps:

[0071] Step S1: According to the target database, extract a preset number of screening information, which at least includes the synthesis conditions of inorganic compounds, the number of atoms and the basic information of the electronic energy band.

[0072] Specifically, in step S1, the synthesis conditions, the number of atoms and the basic information of the electronic energy band of a preset number of inorganic compounds that can be directly queried from the public materials project database platform are extracted (the preset number is determined by the number of organic compounds allowed by the materials project database platform to be directly queried, in this application, referring to the current 150,000 organic compounds).

[0073] Step S2: Using a semiconductor screening method, screen out semiconductor materials from the preset number of screening information.

[0074] Specifically, the materials project gene database currently only provides basic physical information such as the number of atoms, whether it has been synthesized by experiment, the electronic band gap, and the crystal structure. It does not have the thermoelectric performance parameters of each material. Therefore, these basic physical information is used to screen semiconductor materials, that is, semiconductor materials with experimentally synthesized and low crystal structure complexity are obtained from the materials project database.

[0075] For example, in the materials project database, the three screening conditions of theoretical, num_sites and band_gap are selected, and reference is made toFigure 2 As shown, i.e.:

[0076] In step S21, theoretical=True is selected, which indicates that the experimentally synthesized material is selected, and the experimentally synthesized material guarantees the energy stability of the thermoelectric material.

[0077] In step S22, num_sites=[2~20] is selected, which indicates that the number of atoms in the initial unit cell is in the range of 2~20, which belongs to a low complexity structure. Screening a low complexity structure not only facilitates the exploration of material performance and physical origin, but also reduces the calculation cost of first-principle simulation; as the number of atoms increases, the calculation time also increases. Therefore, the number of atoms in the range of 2~20 is selected in the present application, which controls the calculation time of optimizing a material within a few minutes.

[0078] In step S23, since the existing research has found that the thermoelectric materials with ZT>1 all belong to semiconductor materials, band_gap=[0.1~3] is selected, which indicates that the electron band gap is 0.1~3eV, which is a semiconductor material.

[0079] Therefore, after meeting the three screening conditions at the same time, more than 5000 experimentally synthesized semiconductor materials with low crystal structure complexity are obtained from the materials project database at present. The main purpose of step S2 is to shorten the calculation cost of the next step.

[0080] Step S3: A sulfur-containing polyatomic cluster screening method is used to screen sulfur-containing polyatomic cluster materials from semiconductor materials.

[0081] Although the traditional high-throughput method can directly calculate the thermal conductivity, electrical transport parameters and thermoelectric performance of the 5000 materials, the calculation time and resources are huge, because the time period for complete calculation of the performance of a material is at least about one day; therefore, in step S3 of the present application, a polymeric model is exemplarily proposed to obtain a kind of sulfur-containing polyatomic cluster material, which is about 100 or less, which not only effectively saves the calculation resources but also can obtain the thermoelectric performance of this kind of polymeric cluster; reference Figure 3 As shown, from the semiconductor materials obtained in step S2, the screening process for obtaining sulfur-containing polyatomic cluster materials is as follows:

[0082] In step S31, the first principle VASP software is used to optimize the structure, and the POSCAR file of 5000 structures has been obtained in step S2 screening, which represents the spatial structure information of the material, and then the corresponding POTCAR file and KPOINTS file are constructed for each structure, which respectively represent the force field information and grid density, low precision grid density is used, the product of lattice length and K point is equal to 30, and the INCAR file represents the control file of the calculation process.

[0083] In step S32, the electronic wave function is processed in the POSCAR file using the projected augmented wave PAW, the electronic structure calculation adopts the PBE-GGA exchange correlation functional, the plane wave cutoff energy is set to 500 eV in the INCAR file, the force and energy convergence criteria of the crystal structure optimization are 10-4 eV / Å and 10-8 eV respectively, and whether the material contains two or more sulfur (selenium or tellurium) atom numbers is calculated in the process to determine the multimeric material, the sulfur single substance, the selenium single substance and the tellurium single substance, and the calculation results show that the sulfur-sulfur bond length of the sulfur single substance is about 2.1 Å, the selenium-selenium bond length of the selenium single substance is about 2.4 Å, and the tellurium-tellurium bond length of the tellurium single substance is about 2.8 Å; wherein, the electronic wave function is processed in the POSCAR file using the projected augmented wave PAW, the electronic structure calculation adopts the PBE-GGA exchange correlation functional, which is mainly run in the VASP software, and the existing technology which has been generally accepted by the simulation technology is adopted.

[0084] In step S33, whether the sulfur-sulfur (selenium-selenium or tellurium-tellurium) bond length in the 5000 materials is between 1.05-1.1 times the distance of two atoms in the sulfur (selenium or tellurium) single substance is calculated, if the condition is met, it means that the compound belongs to the multimeric material. It should be noted that the atomic aggregation range of 1.05-1.1 is set as the covalent bond length range of the sulfur (selenium or tellurium) atom in the present application, and the corresponding mathematical expression is (Dii < F (Ri+Ri) (i = S, Se, Te)), wherein Dii represents the distance between two sulfur (selenium or tellurium) atoms, Ri represents the covalent radius of the sulfur (selenium or tellurium) atom distance, and Ri+Ri represents the bond length of the sulfur (selenium or tellurium) single substance. The distance between two sulfur (selenium or tellurium) atoms and the judgment of the multimeric material are calculated by calculating the spatial structure information of each atom in the POSCAR file, and the crystal material meeting the multimeric model can be directly screened out. Through the multimeric model of the present application, only the structure optimization of 5000 compounds and the calculation of the thermoelectric performance of 100 multimers are needed, instead of directly calculating the thermoelectric performance of 5000 materials; through this step of screening, at least one order of magnitude of computing resources is saved.

[0085] Finally, 20 polyatomic materials are obtained in this step of screening process, including 10 sulfur atom polyatomic materials with chemical formula names of SrS2, BaS2, NaS, KS, RbS, Ba(PdS2)2, RbS, BaS3, Rb2S3, and K2S3; 5 selenium atom polyatomic materials with chemical formula names of MgSe2, RbCuPdSe5, KCuPdSe5, CuSe3Br, and AgSe3I; and 5 tellurium atom polyatomic materials with chemical formula names of Rb2Te3, Cs2Te5, K2Te3, RbTe, and RbTe.

[0086] Step S4: judging the stability of the sulfur atom-containing polyatomic materials and obtaining the polyatomic materials judged to be stable.

[0087] Specifically, in step S4, the stability of the 20 polyatomic materials screened in step S3 is judged; and the reference Figures 4-6 indicates that the exemplary

[0088] In step S41, the mechanical stability of the material is determined, and like step S3, the POSCAR file, POTCAR file, KPOINTS file, and INCAR file are required. In the INCAR file, NSW = 1, IBRION = 6, and ISIF = 3 are set. In the VASP software, the density functional perturbation theory is used to calculate the elastic constant (Cij) of the material. If the formula , , , is satisfied, it means that the material has mechanical stability, and then the polyatomic material without mechanical stability is screened out.

[0089] In step S42, the material dynamic stability is determined, and as in step S3, the POTCAR file, the KPOINTS file and the INCAR file are required, and the difference is that the POSCAR file is a supercell structure, the supercell is characterized by its a-axis, b-axis and c-axis close to equal length, and the total number of atoms is close to about 100; the k-point grid in the KPOINTS file is 3x3x3; the phonon spectrum is calculated by the finite displacement method in the Phonopy software, the Hellmann-Feynman force acting on each atom is calculated by introducing a small atomic displacement in the optimized structure, and the phonon dispersion curve is further calculated from the dynamic matrix, and in the INCAR file, NSW = 0 and IBRION = -1 are mainly set. If the phonon dispersion curve does not exist virtual frequency, that is, when the atomic vibration frequency is greater than 0, it represents that the material has dynamic stability, and then the polymeric material without dynamic stability is screened out and the polymeric material with dynamic stability is screened out, and 20 stable polymeric materials are obtained in the calculation process of this step.

[0090] Step S5: According to the stable polymeric material, the lattice thermal conductivity is tested and the electrical transport parameters of the polymeric material are calculated, and then the thermoelectric performance is evaluated using the thermoelectric merit value, and the target polymeric thermoelectric material meeting the preset requirements is obtained.

[0091] Specifically, in step S5, the lattice thermal conductivity of the 20 stable polymeric materials is tested, and the input parameters of the lattice thermal conductivity require the second-order atomic interaction force constant and the third-order atomic interaction force constant. Referring to Figure 7 as shown, exemplary:

[0092] In step S51, the second-order atomic interaction force constant has been obtained in the phonon dispersion curve calculation process in step S4.

[0093] In step S52, the third-order atomic interaction force constant needs to be determined, and as in step S3, the POTCAR file, the KPOINTS file and the INCAR file are required, and as in step S4, this step maintains the same supercell characteristics; when the number of atoms in the supercell is less than 100, the k-point grid of the third-order atomic interaction force constant is 2x2x2, and when the number of atoms in the supercell is greater than 100, the k-point grid of the third-order atomic interaction force constant is 1x1x1, and the cutoff radius of the nearest neighbor atom number in the third-order atomic interaction force constant is set to 8. The third-order atomic interaction force constant is obtained by the finite displacement method in the thirdorder.py software, and the INCAR file parameters of the second-order atomic interaction force constant remain the same.

[0094] In step S53, after obtaining the second-order and third-order atomic interaction force constants, the lattice thermal conductivity of the 20 stable materials is obtained by solving the phonon Boltzmann transport equation in the ShengBTE software, and the thermal conductivity is expressed as:

[0095]

[0096] for the phonon modes, representing the heat capacity, is the phonon group velocity, is the phonon lifetime. The q-point grid for evaluating the lattice thermal conductivity converges to 9x9x9. As shown in Figure 8 , 15 ultra-low lattice thermal conductivity materials (κ < 1 Wm -1 K -1 ) are obtained in this step calculation, among which 18 materials are lower than the thermal conductivity of 2.4 Wm -1 K -1 of the commercial material PbTe. This demonstrates the advantage of the multimer model of the present application in exploring low thermal conductivity.

[0097] In step S5, the electrical transport parameters of the 20 multimer materials are calculated and the thermoelectric performance is evaluated. As shown in Figure 9 , the exemplary:

[0098] In step S54, as in step S3, the POSCAR file, POTCAR file, KPOINTS file and INCAR file are required, and the first-principles calculation of the basic electrical transport parameters of the phonon frequency, elastic constant, deformation potential energy and wave function coefficient is carried out in the VASP software. As in step S4, the elastic constant of the material is calculated in the VASP software using the density functional perturbation theory, and the difference is that a high-precision grid density is used, and the product of the lattice edge length and the K point is equal to 50. In the calculation of the elastic constant, the INCAR file is set to IBRION = 6. In the calculation of the phonon frequency, the INCAR file is set to IBRION = 8. In the calculation of the electrical transport parameters, the INCAR file is set to NSW = 1.

[0099] In step S55, the basic electrical transport parameters are used to solve the electrical conductivity, Seebeck coefficient and carrier thermal conductivity in the AMSET software; the three electrical transport coefficients are calculated through the Onsager relationship, and the generalized transport coefficient is expressed as:

[0100]

[0101] and is the atomic coordinate, represents the atomic charge, is the spectral electrical conductivity, is the Fermi level at a specific concentration and temperature, represents the Fermi-Dirac distribution, is the energy band index. The conductivity is expressed as:

[0102]

[0103] The Seebeck coefficient is expressed as:

[0104]

[0105] represents the system temperature, and the carrier thermal conductivity is expressed as:

[0106]

[0107] The interpolation factor of the electrical transport grid density is set to 20, and 10 new polymer thermoelectric materials with ZT>1 are obtained from 20 polymers.

[0108] In step S56, the thermoelectric figure of merit is used By evaluating the thermoelectric properties of stable polymer materials, nine n-type thermoelectric materials were discovered, with chemical formulas of RbTe, BaS2, KCuPdSe5, RbCuPdSe5, Cs2Te5, CuSe3Br, AgSe3I, Rb2Te3, and K2Te3; and one p-type thermoelectric material, with chemical formula of RbTe. Figure 10 As shown, the relationship between carrier concentration, temperature and ZT in 10 polymer materials. Figure 10 The type (n-type or p-type) and chemical formula of the thermoelectric material are also shown. 18 cm -3 ~10 21 cm -3 The interval reaches the maximum value of ZT and ZT>1. The thermoelectric performance of these polymer materials is higher than 0.8 of the material PbTe, which indicates the advantages of the polymer model of this application in exploring high-performance thermoelectric materials.

[0109] Thus, steps S1-S3 of this application demonstrate the efficient acquisition of 20 chalcogen-containing polymer materials using the unique two-step screening method proposed in this application. Steps S4-S6 demonstrate the validity of this screening result using first-principles calculations, and the discovery of 15 ultra-low lattice thermal conductivity and 10 high-performance polymer thermoelectric materials, particularly 9 n-type thermoelectric materials, enriching the thermoelectric material pool. This two-step screening method and screening results provide a theoretical basis for constructing high-performance pn-type thermoelectric materials and promoting the commercialization of thermoelectric devices.

[0110] In some embodiments, reference Figure 11As shown, the application also relates to a high-throughput screening system for screening a plurality of thermoelectric materials, comprising:

[0111] A data extraction module 100 is configured to extract a preset number of screening information from a target database, wherein the screening information at least includes the synthesis conditions of inorganic compounds, the number of atoms, and the basic information of electronic energy bands;

[0112] A first screening module 101 is configured to screen semiconductor materials from the preset number of screening information by using a semiconductor screening method; and is further configured to screen the semiconductor materials that have been synthesized in experiments by using a first screening condition according to the preset number of screening information; screen the semiconductor materials with the number of atoms in the initial unit cell in a first preset interval by using a second screening condition according to the preset number of screening information; and screen the semiconductor materials with the electronic band gap in a second preset interval by using a third screening condition according to the preset number of screening information, so as to obtain the semiconductor materials.

[0113] A second screening module 102 is configured to screen the chalcogen atom-containing polymer materials from the semiconductor materials by using a chalcogen atom-containing polymer screening method; and is further configured to optimize the semiconductor materials by using a first-principle calculation software, to obtain the spatial structure information data of the semiconductor materials, and then to construct the force field information data and the preset grid density data for each spatial structure contained in the semiconductor materials; use the projected augmented wave to process the electronic wave function and use the PBE-GGA exchange correlation functional to calculate the electronic structure in the spatial structure information data of the semiconductor materials; calculate the polymer materials containing the sulfur-sulfur (selenium-selenium or tellurium-tellurium) bond length between the two atoms in the sulfur (selenium or tellurium) element in a preset multiple according to the spatial structure information data of each atom in the semiconductor materials, so as to screen the polymer materials containing at least two numbers of sulfur (selenium or tellurium) atoms.

[0114] A property judgment module 103 is configured to judge the stability according to the chalcogen atom-containing polymer materials, and to obtain the polymer materials judged to be stable; and is further configured to judge the material mechanical stability according to the screened polymer materials containing at least two numbers of sulfur (selenium or tellurium) atoms; judge the material kinetic stability according to the screened polymer materials containing at least two numbers of sulfur (selenium or tellurium) atoms, so as to screen the stable polymer materials.

[0115] The material evaluation module 104 is configured to perform lattice thermal conductivity test on the stable polymer material and calculate the electrical transport parameters of the polymer material, and then evaluate the thermoelectric performance using the thermoelectric figure of merit to obtain the target polymer thermoelectric material meeting the preset requirements; and is further configured to calculate the phonon spectrum of the stable polymer material using the finite displacement method, and then obtain the second-order atomic interaction force constant according to the phonon spectrum; obtain the third-order atomic interaction force constant of the stable polymer material using the finite displacement method; solve the phonon Boltzmann transport equation to obtain the lattice thermal conductivity of the stable polymer material according to the second-order atomic interaction force constant and the third-order atomic interaction force constant; calculate the elastic constant of the stable polymer material using the density functional perturbation theory; solve the electrical conductivity, the Seebeck coefficient and the carrier thermal conductivity using the basic electrical transport parameters of the stable polymer material; evaluate the thermoelectric performance of the stable polymer material using the thermoelectric figure of merit to obtain the target polymer thermoelectric material meeting the preset requirements.

[0116] In some embodiments, the present application also relates to a computer medium, wherein a computer program is stored on the computer medium, and the computer program is executed by a processor to realize the high-throughput screening method of the polymer thermoelectric material.

[0117] In some embodiments, the present application also relates to a computer comprising the computer medium.

[0118] In the description of the present application, the description of the terms "one embodiment", "some embodiments”, "an example”, "a specific example” or "some examples” means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the different embodiments or examples described in the present application and the features of the different embodiments or examples can be combined and combined by those skilled in the art without contradiction.

[0119] Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A method of high-throughput screening of multinary thermoelectric materials, comprising, The method comprises the following steps: Step S1: extracting a preset number of screening information according to a target database, the screening information at least comprising: synthesis conditions of inorganic compounds, basic information of atomic number and electronic energy band; Step S2: screening semiconductor materials from the preset number of screening information by using a semiconductor screening method; Step S3: screening sulfur group atom-containing polymer materials from the semiconductor materials by using a sulfur group atom-containing polymer screening method; Step S4: judging stability according to the sulfur group atom-containing polymer materials and obtaining polymer materials judged as stable; Step S5: performing lattice thermal conductivity test on the stable polymer materials, calculating the electrical transport parameters of the polymer materials, further evaluating the thermoelectric performance by using a thermoelectric figure of merit, and obtaining target polymer thermoelectric materials meeting preset requirements; In step S3, the method comprises the following steps: Step S31: optimizing the semiconductor materials by using first-principle calculation software to obtain spatial structure information data of the semiconductor materials, and further constructing force field information data and preset grid density data for each spatial structure contained in the semiconductor materials; Step S32: processing electronic wave functions by using projected augmented wave and calculating electronic structure by using PBE-GGA exchange correlation functional in the spatial structure information data of the semiconductor materials; Step S33: calculating polymer materials containing sulfur-sulfur, selenium-selenium or tellurium-tellurium bond length between 1.05 and 1.1 times of the distance between two atoms in sulfur, selenium or tellurium elements according to the spatial structure information data of each atom in the semiconductor materials, and screening polymer materials containing at least two numbers of sulfur, selenium or tellurium atoms.

2. The method of high-throughput screening of multinary thermoelectric materials of claim 1, wherein, In step S2, the method comprises the following steps: Step S21: screening semiconductor materials that have been synthesized according to the preset number of screening information by using a first screening condition; Step S22: screening semiconductor materials with the number of atoms in the initial unit cell in a first preset interval according to the preset number of screening information by using a second screening condition; Step S23: screening semiconductor materials with an electronic band gap in a second preset interval according to the preset number of screening information by using a third screening condition, thereby obtaining semiconductor materials.

3. The method of high-throughput screening of multinary thermoelectric materials of claim 1, wherein, In step S33, according to the spatial structure information data of each atom in the semiconductor materials, materials containing sulfur-sulfur, selenium-selenium or tellurium-tellurium bond length between 1.05 and 1.1 times of the distance between two atoms in sulfur, selenium or tellurium elements are regarded as polymer materials.

4. The method of high-throughput screening of multinary thermoelectric materials of claim 1, wherein, In step S4, the method comprises the following steps: Step S41: judging the mechanical stability of the screened polymer materials containing at least two numbers of sulfur, selenium or tellurium atoms; Step S42: judging the dynamic stability of the screened polymer materials containing at least two numbers of sulfur, selenium or tellurium atoms, thereby screening stable polymer materials.

5. The method of high-throughput screening of multinary thermoelectric materials of claim 4, wherein, In step S41, the method comprises the following steps: Step S411: calculating the elastic constant of the polymer material by using density functional perturbation theory; Step S412: judging whether the elastic constant whether the formula is satisfied: , If yes, it is judged that the polymer material has mechanical stability, and the material dynamics stability judgment is performed; if no, it is judged that the polymer material does not have mechanical stability, and the polymer material without mechanical stability is screened out.

6. The method of high-throughput screening of a multinary thermoelectric material of claim 4, wherein, In step S42, the method comprises the following steps: Step S421: calculating the phonon spectrum of the polymer material with mechanical stability by using the finite displacement method; Step S422: judging whether the phonon dispersion curve of the phonon spectrum exists virtual frequency, if yes, it is judged that the polymer material does not have dynamics stability, and the polymer material without dynamics stability is screened out; if no, it is judged that the polymer material has dynamics stability, and the polymer material with dynamics stability is screened out.

7. The method of high-throughput screening of multinary thermoelectric materials of claim 1 or 4, wherein, In step S5, the method comprises the following steps: Step S51: calculating the second-order atomic interaction force constant of the stable polymer material by using the finite displacement method; Step S52: obtaining the third-order atomic interaction force constant of the stable polymer material by using the finite displacement method; Step S53: solving the phonon Boltzmann transport equation to obtain the lattice thermal conductivity of the stable polymer material according to the second-order atomic interaction force constant and the third-order atomic interaction force constant.

8. The method of high-throughput screening of multinary thermoelectric materials of claim 7, wherein, In step S5, the method further comprises the following steps: Step S54: calculating the elastic constant of the stable polymer material by using the density functional perturbation theory; Step S55: solving the electrical conductivity, the Seebeck coefficient and the carrier thermal conductivity by using the basic electrical transport parameters of the stable polymer material; Step S56: using the thermoelectric figure of merit The thermoelectric performance of the stable multimeric material is evaluated to obtain a target multimeric thermoelectric material that meets preset requirements; wherein is the electrical conductivity, S is the Seebeck coefficient, is the temperature at which the material is operated, is the lattice thermal conductivity, is the electronic thermal conductivity.

9. A high-throughput screening system for polymeric thermoelectric materials for performing the high-throughput screening method according to any one of claims 1 to 8, characterized in that: It comprises: A data extraction module is configured to extract a preset number of screening information from a target database, wherein the screening information at least includes the synthesis conditions of inorganic compounds, the number of atoms, and the basic information of electronic energy bands; A first screening module is configured to screen out semiconductor materials from the preset number of screening information by using a semiconductor screening method; A second screening module is configured to screen out sulfur group atom-containing polymer materials from the semiconductor materials by using a sulfur group atom-containing polymer screening method; A characteristic judgment module is configured to perform stability judgment on the sulfur group atom-containing polymer materials and obtain stable polymer materials; A material evaluation module is configured to perform lattice thermal conductivity test on the stable polymer materials, calculate the electrical transport parameters of the polymer materials, further evaluate the thermoelectric performance by using the thermoelectric merit value, and obtain target polymer thermoelectric materials meeting the preset requirements.

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