Artificial solid electrolyte interfacial film performance evaluation method

Abstract

The invention relates to an artificial solid electrolyte interfacial film performance evaluation method. The method comprises the following steps: constructing an artificial solid electrolyte interface ASEI membrane based on crystal structure data, and determining the surface performance of the ASEI membrane; constructing a heterojunction structure of the ASEI film according to the surface performance, and carrying out lattice matching treatment on the heterojunction structure to obtain an ASEI film interface model; and performing performance evaluation calculation on the ASEI membrane interface model, and determining performance parameters of the ASEI membrane. By adopting the method, the accuracy of ASEI film performance evaluation can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of power equipment detection, and in particular to a method for evaluating the performance of an artificial solid electrolyte interface membrane. Background Art

[0002] Artificial solid electrolyte interphase (ASEI) films have garnered widespread attention in recent years as a key material for improving the interfacial stability and cycle life of lithium metal batteries. These films are typically constructed on the surface of lithium anodes via physical coating, chemical vapor deposition, or in-situ polymerization to inhibit dendrite growth, reduce interfacial impedance, and enhance electrolyte compatibility.

[0003] However, existing technologies for evaluating ASEI membrane performance suffer from insufficient accuracy. Therefore, a method for improving the accuracy of ASEI membrane performance evaluation is urgently needed. Summary of the Invention

[0004] Based on this, it is necessary to provide an artificial solid electrolyte interface membrane performance evaluation method that can improve the accuracy of ASEI membrane performance evaluation in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for evaluating the performance of an artificial solid electrolyte interface membrane. The method comprises:

[0006] Based on crystal structure data, artificial solid electrolyte interface (ASEI) membranes were constructed and their surface properties were determined.

[0007] The heterojunction structure of the ASEI film is constructed based on the surface properties, and the heterojunction structure is subjected to lattice matching to obtain the ASEI film interface model;

[0008] The performance evaluation calculation of the ASEI membrane interface model is performed to determine the performance parameters of the ASEI membrane.

[0009] In one embodiment, the performance parameters include structural stability, and the performance evaluation calculation of the ASEI membrane interface model to determine the performance parameters of the ASEI membrane includes:

[0010] Determine the internal binding energy of the ASEI film interface model;

[0011] The structural stability of the ASEI film is determined based on the internal binding energy and the preset energy threshold.

[0012] In one embodiment, the determining of the internal binding energy of the ASEI film interface model includes:

[0013] According to the crystal structure data of the ASEI film interface model, the total crystal energy of the ASEI film interface model, the number of atoms constituting the crystal structure data, and the isolated state energy corresponding to the atoms in the isolated state are determined respectively;

[0014] The total crystal energy, the number of atoms, and the isolated state energy are substituted into the internal binding energy equation to determine the internal binding energy of the ASEI film interface model.

[0015] In one embodiment, the performance parameters include electronic insulation, and a performance evaluation calculation is performed on the ASEI film interface model to determine the performance parameters of the ASEI film, including:

[0016] Determine the energy band diagram of the ASEI film interface model, and determine the band gap value of the ASEI film interface model according to the energy band diagram;

[0017] The electronic insulation of the ASEI film is determined by the size of the band gap value.

[0018] In one embodiment, the performance parameters include ion transport capacity, and a performance evaluation calculation is performed on the ASEI membrane interface model to determine the performance parameters of the ASEI membrane, including:

[0019] Determine the diffusion coefficient and ionic conductivity of the ASEI membrane interface model;

[0020] The ion transport capacity of the ASEI membrane is determined according to the size of the diffusion coefficient and the size of the ionic conductivity.

[0021] In one embodiment, the performance parameters include interfacial wettability, and a performance evaluation calculation is performed on the ASEI film interface model to determine the performance parameters of the ASEI film, including:

[0022] Determine the interface formation energy of the ASEI film interface model;

[0023] The interfacial wettability of the ASEI film is determined based on the interface formation energy and the preset wettability threshold.

[0024] In one embodiment, determining the interface formation energy of the ASEI film interface model includes:

[0025] According to the crystal structure data of the ASEI film interface model, the interface area, total energy, first interface energy and second interface energy of the ASEI film interface model are determined respectively;

[0026] The interface area, total energy, first interface energy and second interface energy are input into the interface formation energy relationship to determine the interface formation energy of the ASEI film interface model.

[0027] In one embodiment, the performance parameters include lithium dendrite suppression capability, and a performance evaluation calculation is performed on the ASEI film interface model to determine the performance parameters of the ASEI film, including:

[0028] Determine the interfacial energy of the ASEI film interface model;

[0029] The lithium dendrite inhibition capability of the ASEI film is determined based on the interfacial energy and the preset lithium dendrite inhibition threshold.

[0030] In one embodiment, the surface properties include surface energy, and determining the surface properties of the ASEI film includes:

[0031] Based on the crystal structure data of ASEI film, the surface bottom area, unit cell energy, number of surface atoms and total number of atoms in the unit cell of ASEI film were determined respectively;

[0032] The surface area, unit cell energy, number of surface atoms, and total number of atoms in the unit cell are input into the surface energy equation to determine the surface energy of the ASEI film.

[0033] In one embodiment, the surface properties include electron work function, and determining the surface properties of the ASEI film includes:

[0034] According to the crystal structure data of ASEI film, the crystal vacuum energy level and crystal Fermi level of ASEI film are determined respectively;

[0035] The difference between the crystal vacuum level and the crystal Fermi level is determined as the electron work function of the ASEI film.

[0036] In a second aspect, the present application also provides an artificial solid electrolyte interface membrane performance evaluation device. The device includes:

[0037] A determination module is used to construct an artificial solid electrolyte interface (ASEI) membrane based on crystal structure data and determine the surface properties of the ASEI membrane;

[0038] The matching module is used to construct the heterojunction structure of the ASEI film according to the surface properties and perform lattice matching on the heterojunction structure to obtain the ASEI film interface model;

[0039] The evaluation module is used to perform performance evaluation calculations on the ASEI membrane interface model and determine the performance parameters of the ASEI membrane.

[0040] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are performed:

[0041] Based on crystal structure data, artificial solid electrolyte interface (ASEI) membranes were constructed and their surface properties were determined.

[0042] The heterojunction structure of the ASEI film is constructed based on the surface properties, and the heterojunction structure is subjected to lattice matching to obtain the ASEI film interface model;

[0043] The performance evaluation calculation of the ASEI membrane interface model is performed to determine the performance parameters of the ASEI membrane.

[0044] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0045] Based on crystal structure data, artificial solid electrolyte interface (ASEI) membranes were constructed and their surface properties were determined.

[0046] The heterojunction structure of the ASEI film is constructed based on the surface properties, and the heterojunction structure is subjected to lattice matching to obtain the ASEI film interface model;

[0047] The performance evaluation calculation of the ASEI membrane interface model is performed to determine the performance parameters of the ASEI membrane.

[0048] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the following steps:

[0049] Based on crystal structure data, artificial solid electrolyte interface (ASEI) membranes were constructed and their surface properties were determined.

[0050] The heterojunction structure of the ASEI film is constructed based on the surface properties, and the heterojunction structure is subjected to lattice matching to obtain the ASEI film interface model;

[0051] The performance evaluation calculation of the ASEI membrane interface model is performed to determine the performance parameters of the ASEI membrane.

[0052] The above-mentioned artificial solid electrolyte interface membrane performance evaluation method first constructs an artificial solid electrolyte interface ASEI membrane based on crystal structure data. The crystal structure data contains information such as the precise arrangement and spatial position of atoms, which enables the constructed ASEI membrane model to truly restore the microstructure of the material. Next, the heterojunction structure of the ASEI membrane is constructed based on the surface properties, and then the heterojunction structure is lattice-matched. This treatment can eliminate the stress and defects caused by lattice differences at the interface, making the ASEI membrane interface model more stable and consistent with the actual material interface state. Finally, the performance evaluation calculation is performed on the ASEI membrane interface model constructed and processed as described above. At this time, the ASEI membrane interface model is highly close to the real material from the microstructure to the interface characteristics. The factors considered in the evaluation calculation process are consistent with the actual situation. Therefore, it can more comprehensively and accurately reflect the performance of the ASEI membrane in actual applications, thereby greatly improving the accuracy of the ASEI membrane performance evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a diagram of the internal structure of a computer device in one embodiment;

[0054] Figure 2 Schematic diagram of a process for evaluating the performance of an artificial solid electrolyte interface membrane in one embodiment;

[0055] Figure 3 A schematic flow chart of a method for evaluating the performance of an artificial solid electrolyte interface membrane in another embodiment;

[0056] Figure 4 A schematic flow chart of a method for evaluating the performance of an artificial solid electrolyte interface membrane in another embodiment;

[0057] Figure 5 A schematic flow chart of a method for evaluating the performance of an artificial solid electrolyte interface membrane in another embodiment;

[0058] Figure 6 A unit cell model of the crystal structure of LiF and LiX alloy in one embodiment;

[0059] Figure 7 The band structure of LiF and LiX alloy in one embodiment;

[0060] Figure 8 is the band structure of LiF-LiX;

[0061] Figure 9 A schematic flow chart of a method for evaluating the performance of an artificial solid electrolyte interface membrane in another embodiment;

[0062] Figure 10 A schematic flow chart of a method for evaluating the performance of an artificial solid electrolyte interface membrane in another embodiment;

[0063] Figure 11 A schematic flow chart of a method for evaluating the performance of an artificial solid electrolyte interface membrane in another embodiment;

[0064] Figure 12 A schematic flow chart of a method for evaluating the performance of an artificial solid electrolyte interface membrane in another embodiment;

[0065] Figure 13 A schematic flow chart of a method for evaluating the performance of an artificial solid electrolyte interface membrane in another embodiment;

[0066] Figure 14 A schematic flow chart of a method for evaluating the performance of an artificial solid electrolyte interface membrane in another embodiment;

[0067] Figure 15 1 is a structural block diagram of an artificial solid electrolyte interface membrane performance evaluation device in one embodiment. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0069] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 1 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store relevant data in the process of evaluating the performance of artificial solid electrolyte interface membranes. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for evaluating the performance of an artificial solid electrolyte interface membrane is implemented.

[0070] Those skilled in the art will understand that Figure 1The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0071] In one embodiment, Figure 2 As shown in the figure, a method for evaluating the performance of artificial solid electrolyte interface membrane is provided. Figure 1 The computer device in the example is used to illustrate the process, including the following steps:

[0072] S201, constructing an artificial solid electrolyte interface (ASEI) membrane based on crystal structure data, and determining the surface properties of the ASEI membrane.

[0073] A crystal is a solid substance formed by atoms, ions, or molecules arranged periodically according to certain rules. Crystal structure data describes the specific arrangement of atoms in a crystal, as well as the distances and angles between them.

[0074] The ASEI membrane is a solid electrolyte interface membrane formed between the electrode and the electrolyte.

[0075] The surface properties of ASEI membranes refer to the physical and chemical characteristics of the membrane surface. Common surface properties include surface energy, surface charge distribution, and surface roughness. Surface energy reflects the activity of surface atoms or molecules, influencing the membrane's interaction with other substances; surface charge distribution affects ion adsorption and transport; and surface roughness influences the contact area and wettability of the interface.

[0076] In the present embodiment, a computer device first acquires crystal structure data. Once this data is acquired, a material simulation software is used to construct an initial model of the ASEI film. During this construction process, the material simulation software constructs the ASEI film's microstructure in a virtual environment based on information such as the atomic arrangement and interactions within the crystal structure.

[0077] After constructing the ASEI film model, a computer uses the computational capabilities of materials simulation software to determine its surface properties. By calculating the energy state of surface atoms and the distribution of electron clouds, parameters such as surface energy and work function are derived. These parameters provide a direct reflection of the atomic activity and ease of electron escape on the ASEI film surface, thereby determining the ASEI film's surface stability and its ability to interact with other substances.

[0078] S202 , constructing a heterojunction structure of the ASEI film according to the surface properties, and performing lattice matching processing on the heterojunction structure to obtain an ASEI film interface model.

[0079] A heterojunction structure is formed by combining two or more different materials. When constructing the heterojunction structure of an ASEI membrane, materials with different properties are combined to fully leverage the strengths of each. For example, combining a material with high ionic conductivity with a material with good chemical stability results in an ASEI membrane with superior overall performance.

[0080] The atoms in a lattice crystal are arranged periodically to form a lattice. Different materials have different lattice parameters (such as lattice constant and unit cell shape). When constructing the heterojunction structure of an ASEI film, lattice matching is required to better bond the different materials at the interface and reduce interface defects and stress.

[0081] The ASEI membrane interface model is a model obtained after lattice matching and is used to simulate the interface between the ASEI membrane and other substances (such as electrodes and electrolytes). The ASEI membrane interface model integrates factors such as the ASEI membrane's structure, surface properties, and interactions with other substances.

[0082] In the examples of this application, a computer device combines components of different materials into an ASEI membrane model in a specific manner. Based on the material properties reflected by the surface properties, the computer device selects the appropriate material combination and uses software tools to rationally stitch the different material structures together to form a heterojunction structure, giving the ASEI membrane the combined advantages of multiple materials.

[0083] Because different materials have different lattice parameters, the computer minimizes these differences by adjusting the lattice orientation and expanding or shrinking the lattice cells, thereby improving their integration at the interface. This process requires repeated calculations and adjustments until the ideal lattice matching is achieved, resulting in a stable ASEI film interface model.

[0084] S203, performing performance evaluation calculation on the ASEI membrane interface model to determine the performance parameters of the ASEI membrane.

[0085] In the examples of this application, a computer system uses computational methods such as density functional theory and molecular dynamics simulation to analyze the ASEI membrane interface model from multiple perspectives. Through performance evaluation calculations, a series of performance parameters related to the ASEI membrane are obtained. These performance parameters are then organized and analyzed, and the different performance parameters are compared with the expected targets or the performance of existing materials to evaluate the performance of the ASEI membrane.

[0086] In some embodiments, the computer device can also determine whether the ASEI membrane meets the actual application requirements based on the analysis results. If it does not meet the requirements, it returns to the previous steps, adjusts the model parameters or replaces the materials, and re-simulates the calculation until the ASEI membrane performance parameters that meet the requirements are obtained.

[0087] In the above-mentioned artificial solid electrolyte interface membrane performance evaluation method, first, an artificial solid electrolyte interface ASEI membrane is constructed based on crystal structure data. The crystal structure data contains information such as the precise arrangement and spatial position of atoms, which enables the constructed ASEI membrane model to truly restore the microstructure of the material. Next, the heterojunction structure of the ASEI membrane is constructed based on the surface properties, and then the heterojunction structure is lattice-matched. This treatment can eliminate the stress and defects caused by lattice differences at the interface, making the ASEI membrane interface model more stable and consistent with the actual material interface state. Finally, the performance evaluation calculation is performed on the ASEI membrane interface model constructed and processed as described above. At this time, the ASEI membrane interface model is highly close to the real material from the microstructure to the interface characteristics. The factors considered in the evaluation calculation process are consistent with the actual situation. Therefore, it can more comprehensively and accurately reflect the performance of the ASEI membrane in actual applications, thereby greatly improving the accuracy of the ASEI membrane performance evaluation.

[0088] In one embodiment, the above performance parameters include structural stability, based on which, Figure 3 As shown in the above embodiment, "performing performance evaluation calculations on the ASEI film interface model to determine the performance parameters of the ASEI film" includes:

[0089] S301, determining the internal binding energy of the ASEI film interface model.

[0090] Internal binding energy refers to the energy required to completely separate the components (atoms, ions, etc.) in the ASEI membrane interface model to infinity. In the ASEI membrane interface model, internal binding energy reflects the strength of the interactions between atoms within the membrane. A greater binding energy indicates a tighter bond between atoms, requiring more energy to separate them, which translates to a more stable membrane structure.

[0091] The preset energy threshold is a numerical energy standard set before evaluating the structural stability of an ASEI membrane. This threshold is determined based on experience, theoretical calculations, or practical application requirements. It serves as a judgment boundary, with which the internal binding energy of the ASEI membrane is compared to determine the structural stability of the ASEI membrane. For example, if the internal binding energy is greater than the preset energy threshold, the ASEI membrane is considered to have good structural stability. Conversely, if it is less than the threshold, the membrane structure is relatively unstable and may be more susceptible to structural changes or damage in actual application.

[0092] In the embodiments of the present application, the computer device needs to select an appropriate calculation method based on the characteristics of the ASEI film and the required calculation accuracy, such as density functional theory or molecular dynamics methods, which are widely used in the field of materials calculation. The computer device uses the selected calculation method to individually calculate the energy of each isolated atom in the ASEI film interface model. This process requires accurate simulation of the energy conditions of the atoms in their isolated state, fully considering key factors such as the atomic internal electronic structure and nuclear charge distribution. After completing the calculation of the isolated atom energy, the computer calculates the total energy of the entire ASEI film interface model using the same calculation method and parameter settings. At this time, it is necessary to comprehensively consider the complex interactions between atoms in the model, including chemical bond interactions and weaker interactions such as van der Waals forces. Finally, a specific calculation method is used, namely, the total energy of the model minus the sum of the energies of all isolated atoms, to obtain the internal binding energy of the ASEI film interface model. The value of the internal binding energy reflects the energy changes when atoms combine to form the membrane structure. A negative value indicates that the process of atomic bonding is energetically favorable.

[0093] S302 , determining the structural stability of the ASEI film according to the internal binding energy and a preset energy threshold.

[0094] Structural stability refers to the ability of the ASEI membrane to maintain its original atomic structure and chemical composition without significant changes when subjected to external factors (such as temperature, pressure, electric field, and ion migration). A structurally stable ASEI membrane can continue to effectively perform its role as an electrolyte interface during the battery's charge and discharge cycles, such as preventing side reactions between the electrolyte and electrodes and promoting ion conduction. By evaluating the structural stability of the ASEI membrane, its service life and performance in actual battery applications can be predicted.

[0095] In the embodiments of the present application, a computer device predefines an energy threshold for determination based on the material properties of the ASEI membrane, the environmental conditions of actual application, and previous research experience. The computer device compares the calculated internal binding energy with the preset energy threshold. If the internal binding energy is less than the energy threshold, this indicates that the atoms within the membrane structure are tightly bound and the membrane structure is stable. Conversely, if the internal binding energy is greater than the energy threshold, the membrane structure is relatively unstable and may be more susceptible to external factors and structural changes in actual application scenarios.

[0096] The computer outputs the internal binding energy of the ASEI membrane interface model, a pre-set energy threshold, and a comparison-based determination of structural stability. These results require further analysis. If the membrane structure is determined to be unstable, further investigation into the underlying causes is necessary. The membrane's atomic composition can be analyzed to identify any inappropriate atomic ratios, while the membrane structure can also be examined to determine if defects are affecting its stability. This analysis provides a strong basis for subsequent structural optimization of the ASEI membrane, thereby enhancing its performance in practical applications.

[0097] In some embodiments, the internal binding energy may be Ecoh, and the preset energy threshold may be 0. When Ecoh is greater than 0, atoms absorb energy from the outside world when they assemble from a free state into a crystal, making the crystal unstable and prone to decomposition. Conversely, when Ecoh is less than 0, atoms release energy from the outside world when they assemble from a free state into a crystal, making the crystal stable. A larger value for |Ecoh| indicates a more stable crystal structure.

[0098] In one embodiment, Figure 4 As shown, the “determining the internal binding energy of the ASEI film interface model” in the above embodiment includes:

[0099] S401 , according to the crystal structure data of the ASEI film interface model, respectively determining the total crystal energy of the ASEI film interface model, the number of atoms constituting the crystal structure data, and the isolated state energy corresponding to the atoms in the isolated state.

[0100] The total crystal energy refers to the total energy of all atoms in the ASEI film interface model in their current crystal structure. This energy includes the kinetic energy of the atoms and the interaction energy between them (such as chemical bond energy and energy generated by van der Waals forces). The total crystal energy reflects the energy state of the entire model, and its value is closely related to the type, number, arrangement, and interaction strength of the atoms.

[0101] The number of atoms constituting the crystal structure data is the number of each type of atoms contained in the crystal structure of the ASEI film interface model. Different types of atoms (such as lithium, fluorine, magnesium, etc., depending on the composition of the ASEI film) each have a certain number in the model.

[0102] The isolated-state energy of an atom is the energy possessed by a single atom in its isolated state, completely separated from and unaffected by other atoms. This energy is primarily determined by the atom's electronic structure and nuclear properties. Different types of atoms have different electronic configurations and nuclear charges, resulting in different isolated-state energies.

[0103] In an embodiment of the present application, the crystal structure data of the ASEI film interface model, including information such as atomic species, coordinates, and unit cell parameters, is input into a calculation program to obtain the total crystal energy, which reflects the comprehensive energy state of all atoms and interactions in the crystal.

[0104] The crystal structure data is then analyzed to identify the different types of atoms and count the number of each type. By analyzing the atomic coordinates and type information, the total number of atoms is summarized and the specific number of each type of atom is recorded, providing accurate data for subsequent calculations.

[0105] For each atom in the crystal, an isolated-state model is constructed, assuming it is in a gaseous, non-interacting state. Using a similar or modified method for calculating the total crystal energy, factors such as the atomic electronic structure and nuclear charge distribution are determined to calculate the isolated-state energy of each atom. For common atoms, data from literature or databases can be used; however, specialized calculations are required for unique atoms. Finally, a list of isolated-state energies corresponding to each atomic type is compiled.

[0106] S402 , substituting the total crystal energy, the number of atoms, and the isolated state energy into the internal binding energy equation to determine the internal binding energy of the ASEI film interface model.

[0107] In the embodiment of the present application, the obtained total crystal energy, number of atoms, and isolated state energy are substituted into the internal binding energy relationship to determine the internal binding energy of the ASEI film interface model.

[0108] In some embodiments, the internal binding energy relationship can be expressed as equation (1).

[0109] The internal binding energy Ecoh of the composite ASEI film crystal is calculated using DFT. The Ecoh calculation method is as follows:

[0110]

[0111] In formula (1), Etot represents the total energy of the crystal; x represents the number of A atoms in the crystal; y represents the number of B atoms in the crystal; Represents the isolated state energy of atoms A and B in isolated state.

[0112] In one embodiment, the above performance parameters include electronic insulation, on this basis, such as Figure 5 As shown in the above embodiment, "performing performance evaluation calculations on the ASEI film interface model to determine the performance parameters of the ASEI film" includes:

[0113] S501 , determining an energy band diagram of an ASEI film interface model, and determining a band gap value of the ASEI film interface model according to the energy band diagram.

[0114] The energy band diagram is a graphic used to describe the distribution of electron energy states in a crystal. In a crystal, due to the interaction between atoms, the energy of electrons is no longer continuous, but forms a series of energy bands.

[0115] The different energy bands in a band diagram represent electronic states with different energy ranges. Typically, the lower energy bands are filled with electrons and are called the valence bands. The higher energy bands are generally empty and are called the conduction bands. Between the valence and conduction bands lies an energy region where no allowed electronic states exist; this region is known as the band gap.

[0116] The band gap is the energy difference between the top of the valence band and the bottom of the conduction band. The size of the band gap reflects the minimum energy required for an electron to transition from the valence band to the conduction band. For semiconductors, the band gap ranges from 0.1 to 3 eV; for insulators, the band gap is typically greater than 3 eV; and for metals, where the valence and conduction bands overlap, the band gap is zero.

[0117] In the embodiment of the present application, first, in order to determine the energy band diagram of the ASEI film interface model, it is necessary to select a first-principles calculation method based on density functional theory based on the model characteristics and accuracy requirements, such as with the help of computing software such as VASP and CASTEP. The crystal structure data of the ASEI film interface model, including atomic species, coordinates, unit cell parameters, etc., are accurately input into the computing software to construct a crystal model. Next, the parameters of the calculation method are set, covering key parameters such as plane wave cutoff energy, k-point grid density, exchange-correlation functional, etc. These parameters directly affect the calculation results and efficiency. After completing the settings, run the calculation program to obtain information such as the energy eigenvalue and wave function of the electronic structure, and finally use the drawing software or the built-in function of the computing software to draw the energy band diagram based on the k-point and electron energy information.

[0118] Based on the energy band diagram, determine the locations of the valence band top and conduction band bottom. The valence band is a low-energy band filled with electrons, while the conduction band is a high-energy band generally unoccupied. Read the energy values ​​corresponding to the valence band top and conduction band bottom. The difference between the two energies is the band gap. Some calculation software also allows you to directly obtain this value through output files or specific commands.

[0119] S502, determining the electronic insulation of the ASEI film according to the size of the band gap value.

[0120] Electronic insulation refers to a material's ability to prevent electrons from conducting an electric current. A material's electronic insulation is closely related to its band gap. When a material has a large band gap, electrons have difficulty transitioning from the valence band to the conduction band. Without external excitation, there are few free electrons in the conduction band, and electrons in the valence band are bound to atoms and unable to move freely. Consequently, the material exhibits excellent electronic insulation, meaning that current is difficult to flow through it. Such materials are often referred to as insulators. If a material's band gap is small, at room temperature or lower, some electrons may transition to the conduction band through thermal excitation, resulting in a certain degree of conductivity. These materials are referred to as semiconductors. Metallic materials without a band gap (zero band gap) have a large number of free electrons in their conduction band, resulting in excellent conductivity but poor electronic insulation. Therefore, determining the band gap of an ASEI film can be used to assess its electronic insulation. A large band gap indicates good electronic insulation; a small or zero band gap indicates poor or no electronic insulation.

[0121] In the examples of this application, the resulting band gap values ​​are compared with the band gap ranges of common materials. Generally, materials with band gaps greater than 3eV are considered insulators, exhibiting good electronic insulation. Band gaps between 0.1 and 3eV are semiconductors, exhibiting relatively weak electronic insulation but capable of conducting electricity under certain conditions. Band gaps near zero are metals, exhibiting good conductivity but poor electronic insulation. By comparison, a larger band gap value for an ASEI film indicates excellent electronic insulation, making it difficult for electrons to transition from the valence band to the conduction band, resulting in poor conductivity. A smaller band gap value indicates poor electronic insulation, allowing electrons to be easily excited to the conduction band, exhibiting some conductivity.

[0122] In a specific embodiment, Figure 6-8 As shown, Figure 6 is the unit cell model of the LiF and LiX alloy crystal structure, Figure 7 is the band structure of LiF and LiX alloy, Figure 8 The band structure of LiF-LiX, wherein X can be F, Mg, Ga and Zn.

[0123] Band structure calculations generate an energy band diagram, from which the band gap is determined. The larger the band gap, the more difficult it is for electrons to be excited from the valence band to the conduction band, resulting in lower conductivity and better insulation. When the valence band contains unfilled orbitals (orbitals not fully occupied by electrons), or when the valence band is full but the band gap is zero, the structure is a conductor, exhibiting good electronic conductivity. When the band gap is non-zero, the structure is a semiconductor or an insulator.

[0124] The electronic band structure of LiF, an alloy composed of lithium and other elements LiX alloy is as follows Figure 7As shown in the figure, LiF has a large band gap (8.83 eV) and excellent electronic insulation. However, LiX alloy has no band gap near the Fermi level (close to 0 eV).

[0125] The electronic band structure of LiF-LiX is as follows Figure 8 As shown in the figure, the lithium fluoride-lithium magnesium LiF-LiMg and lithium fluoride-lithium gallium LiF-LiGa composite ASEI films have small band gaps of 0.02eV and 0.04eV, respectively, indicating that they can maintain semiconductor properties. In addition, lithium fluoride-lithium zinc LiF-LiZn has no band gap near the Fermi level, indicating that its electronic insulation is inferior to LiF-LiMg and LiF-LiGa.

[0126] In one embodiment, the above performance parameters include ion transport capacity, based on which, Figure 9 As shown in the above embodiment, "performing performance evaluation calculations on the ASEI film interface model to determine the performance parameters of the ASEI film" includes:

[0127] S601, determining the diffusion coefficient and ionic conductivity of the ASEI membrane interface model.

[0128] The diffusion coefficient is a physical quantity that describes the diffusion rate of particles in a substance. In the ASEI membrane interface model, it represents the ability of ions to diffuse within the membrane. A larger diffusion coefficient indicates faster ion diffusion within the membrane, allowing ions to move more quickly from areas of high concentration to areas of low concentration. This means that ion migration within the membrane is relatively easy and the membrane presents less resistance to ion diffusion. For example, in the electrolyte membrane of a lithium-ion battery, a larger diffusion coefficient for lithium ions allows them to move more quickly through the membrane during charge and discharge, improving battery efficiency and performance. The diffusion coefficient is affected by many factors, including temperature, membrane structure and composition, and ion size and charge. Generally speaking, increasing temperature increases the diffusion coefficient because it increases the thermal kinetic energy of ions, making it easier for them to overcome diffusion resistance. The membrane's pore structure and chemical composition also significantly influence the diffusion coefficient. For example, membranes with more open, porous structures typically have larger diffusion coefficients, facilitating ion diffusion.

[0129] Ionic conductivity describes the ability of ions to conduct electric current in a material. For the ASEI membrane interface model, it reflects the membrane's contribution to ionic conduction. Higher ionic conductivity indicates a material's greater ability to allow ions to pass through and conduct current. Taking solid-state batteries as an example, electrolyte membranes with high ionic conductivity enable rapid lithium ion transfer between the positive and negative electrodes, enabling efficient charging and discharging of the battery, and improving its energy and power density. Ionic conductivity is also influenced by a variety of factors. In addition to factors similar to the diffusion coefficient, such as temperature, membrane structure, and composition, it is also related to ion concentration. Higher ion concentrations increase ionic conductivity because more ions are involved in the conduction process. Furthermore, interactions between ions and the membrane material can affect ionic conductivity. Excessive interactions can hinder ion movement, thereby reducing ionic conductivity.

[0130] In the examples of this application, the crystal structure data of the ASEI membrane interface model was input into the software to construct a complete simulation system, and initial conditions consistent with the actual application scenario were set, including parameters such as temperature, pressure, and ion concentration. The simulation program was then run to track the ion motion trajectory over a certain period of time, recording the ion position information at different times. Subsequently, based on the simulated ion position information, the diffusion coefficient was calculated using the Einstein relation or the mean square displacement method, and the value was obtained by linearly fitting the mean square displacement-time curve.

[0131] After determining the diffusion coefficient, the computer first determines the ion mobility number through experimental measurement or theoretical calculation to determine the current contribution of the ions in the conductive process. The calculated diffusion coefficient is then combined with the Nernst-Einstein equation, taking into account parameters such as ion concentration, ion charge, and temperature. After the calculation is complete, the resulting ionic conductivity is compared with experimental data or theoretical calculations in the literature. If there is a significant deviation, the simulation method and parameter settings are reviewed and adjusted before recalculation to ensure the results are reasonable.

[0132] In a specific embodiment, the calculation method of ionic conductivity σ is shown in formula (2).

[0133]

[0134] In formula (2), e represents the charge number; k B represents the Boltzmann constant; T represents the calculation temperature, T = 298.15K; ρ represents the number of Li+ per unit volume; D represents the diffusion coefficient.

[0135] S602, determining the ion transport capacity of the ASEI membrane according to the size of the diffusion coefficient and the size of the ionic conductivity.

[0136] Ion transport capacity describes the overall ion transport performance of an ASEI membrane. It depends on the diffusion and conductivity of ions within the membrane. Diffusion coefficient and ionic conductivity are two important metrics for measuring ion transport capacity. The diffusion coefficient primarily reflects the diffusion rate of ions within the membrane, while ionic conductivity focuses on the ability of ions to conduct current under the influence of an electric field. Generally speaking, the larger the diffusion coefficient and ionic conductivity, the stronger the ion transport capacity. For example, a large diffusion coefficient allows ions to diffuse rapidly within the membrane, reaching the electrode surface to participate in electrochemical reactions. Simultaneously, high ionic conductivity ensures that ions can efficiently conduct current under the influence of an electric field, thereby enabling normal battery charging and discharging. Therefore, by evaluating the diffusion coefficient and ionic conductivity, the ion transport capacity of ASEI membranes can be quantified and compared, providing a basis for the design and optimization of membrane materials with excellent ion transport properties. In addition to factors related to the diffusion coefficient and ionic conductivity, membrane thickness, surface properties, and externally applied electric fields and pressure also affect ion transport capacity. Thinner membranes generally facilitate ion transport because the ions have to travel a shorter path across the membrane. Membrane surface properties that promote ion adsorption and desorption can also enhance ion transport. An externally applied electric field can accelerate ion migration, while changes in pressure can alter the membrane's pore structure, affecting ion transport pathways.

[0137] In the embodiments of the present application, the computer device compares the calculated diffusion coefficient and ionic conductivity with a pre-set standard or reference value. The larger the two values, the stronger the ion transport capacity is generally. Taking the two values ​​into consideration, a comprehensive evaluation of the ion transport capacity of the ASEI membrane is performed. If both the diffusion coefficient and the ionic conductivity are high, it indicates that the membrane has good ion transport capacity and can meet practical applications; if one value is low, the problems with the membrane structure, composition or simulation conditions are analyzed in depth and optimized and improved. Finally, the computer device outputs the specific values ​​of the diffusion coefficient and ionic conductivity, as well as the comprehensive evaluation results of the ion transport capacity of the ASEI membrane, providing a basis for subsequent research and application.

[0138] In one embodiment, the above performance parameters include interface wettability, based on which, e.g. Figure 10 As shown in the above embodiment, "performing performance evaluation calculations on the ASEI film interface model to determine the performance parameters of the ASEI film" includes:

[0139] S701, determining the interface formation energy of the ASEI film interface model.

[0140] The interface formation energy refers to the energy absorbed or released when forming the ASEI film interface. It reflects the difficulty of forming the interface and the stability of the interface.

[0141] In the embodiments of the present application, a computer device uses quantum mechanics calculation methods such as density functional theory or molecular dynamics simulation methods to calculate three key energy values: the energy of the ASEI film system alone, which reflects the energy of the ASEI film itself; the energy of the contact material system alone, which reflects the energy state of the contact material itself; and the energy of the complete interface system formed by the ASEI film and the contact material, which includes the energy generated by the interaction between atoms at the interface. Finally, a series of calculations are performed to determine the interface formation energy, the magnitude of which reflects the difficulty of forming the interface and the stability of the interface. If the energy decreases when the interface is formed, it means that the interface is easy to form and relatively stable; conversely, if external energy is required to form the interface, then the interface is relatively unstable.

[0142] S702 , determining the interface wettability of the ASEI film according to the interface formation energy and a preset wettability threshold.

[0143] Wettability refers to the ability or affinity of a liquid to spread on a solid surface. The preset wettability threshold is a pre-set standard value used to determine the wettability of the ASEI membrane interface. This threshold is typically determined based on the specific research objectives, material properties, and experience from relevant experimental or theoretical research.

[0144] Interfacial wettability is the interaction property between the ASEI membrane interface and liquids (such as electrolytes). If the interfacial wettability is good, the liquid can spread well on the ASEI membrane surface, which is conducive to ion transport and chemical reactions at the interface. Conversely, if the wettability is poor, the liquid may form droplets on the membrane surface, which is not conducive to ion transport and interfacial reactions, and may affect the performance of related devices such as batteries.

[0145] In the embodiments of the present application, the calculated interface formation energy is compared with a preset wettability threshold. If the interface formation energy is less than or equal to the preset wettability threshold, it indicates that it is relatively easy to form the interface. In this case, it can be determined that the ASEI film has good interfacial wettability, that is, the liquid (such as the electrolyte) can spread well on the surface of the ASEI film, which is very beneficial for the transmission of ions and chemical reactions at the interface. However, if the interface formation energy is greater than the preset wettability threshold, it means that more energy is required to form the interface, and the interface is relatively difficult to form. In this case, it can be determined that the interfacial wettability of the ASEI film is poor, which will have an adverse effect on the performance of related devices such as batteries.

[0146] In a specific embodiment, Wb represents the interface formation energy, 0 represents a preset wettability threshold, and Wb<0 represents that the interface can be formed and exists stably. The larger |Wb| is, the better the wettability is.

[0147] In one embodiment, Figure 11 As shown, the “determining the interface formation energy of the ASEI film interface model” in the above embodiment includes:

[0148] S801 , determining the interface area, total energy, first interface energy, and second interface energy of the ASEI film interface model according to crystal structure data of the ASEI film interface model.

[0149] S802 , inputting the interface area, total energy, first interface energy, and second interface energy into an interface formation energy equation to determine the interface formation energy of the ASEI film interface model.

[0150] The interface formation energy represents the energy change that occurs when forming the interface between the ASEI film and the contact material. It is a key parameter for measuring interface stability and the thermodynamic properties of the formation process. A negative interface formation energy indicates that interface formation is a spontaneous, energy-reducing process, making the interface relatively easy to form and relatively stable. Conversely, a positive interface formation energy indicates that external energy is required for interface formation, making it relatively difficult to form and potentially less stable.

[0151] In the examples of the present application, DFT is used to calculate the interface formation energy and evaluate the wettability of the interface. The calculation method of the interface formation energy Wb is shown in formula (3).

[0152]

[0153] In formula (3), E A / B Represents the total energy of the interface system composed of two surfaces A and B; represent the first interface energy and the second interface energy respectively; S represents the interface area.

[0154] In one embodiment, the above performance parameters include lithium dendrite suppression capability, such as Figure 12 As shown in the above embodiment, "performing performance evaluation calculations on the ASEI film interface model to determine the performance parameters of the ASEI film" includes:

[0155] S901, determining the interface energy of the ASEI film interface model.

[0156] S902 , determining the lithium dendrite suppression capability of the ASEI film according to the interface energy and a preset lithium dendrite suppression threshold.

[0157] In the ASEI membrane interface model, interfacial energy refers to the additional energy at the interface due to the different arrangement of atoms or molecules at the interface compared to the bulk phase. This energy reflects the stability and activity of the interface, and its magnitude is closely related to factors such as the interface's structure, chemical composition, and surrounding environment. Generally speaking, the lower the interfacial energy, the more stable the interface and the less susceptible it is to various physical and chemical changes.

[0158] The preset lithium dendrite suppression threshold is a reference value derived from extensive experimental research, theoretical analysis, and practical application experience. It serves as a criterion for evaluating the ASEI film's ability to suppress lithium dendrites, measuring the required interfacial energy level to effectively inhibit lithium dendrite growth. This threshold is not fixed and varies depending on different battery systems, experimental conditions, and research objectives.

[0159] Lithium dendrites are branch-like crystals formed when lithium metal deposits unevenly on the electrode surface during the charge and discharge process of lithium batteries. The growth of lithium dendrites can cause numerous problems, such as piercing the battery separator, causing a short circuit between the positive and negative electrodes, and reducing the battery's cycle performance and safety. In severe cases, they can even cause safety incidents such as battery combustion and explosion.

[0160] Dendrite inhibition refers to the ability of an ASEI membrane to prevent or slow the growth of lithium dendrites on the surface of a battery electrode. This is a key indicator for evaluating the performance of ASEI membranes in lithium batteries. ASEI membranes with excellent dendrite inhibition can effectively regulate the deposition of lithium ions, ensuring uniform deposition on the electrode surface. This inhibits the formation and growth of lithium dendrites, improving battery safety and cycle life.

[0161] In the examples of this application, the interfacial energy of the ASEI film interface model was determined to evaluate its ability to inhibit lithium dendrite growth. Li nucleation and subsequent Li dendrite growth require overcoming the interfacial energy. The interfacial energy γ is the internal energy increment per unit interface and is calculated as shown in Equation (4).

[0162]

[0163] In formula (4), represents the total energy of the interface system; represents the unit cell energy of ASEI membrane; represents the unit cell energy of ASEI film and Li metal; N ASEI represents the number of unit cells of ASEI membrane; N Li represents the unit cell number of Li metal.

[0164] γ>0 means that the growth of lithium dendrites can be suppressed. The larger the γ is, the stronger the ability to suppress the growth of lithium dendrites is.

[0165] In one embodiment, the surface properties include surface energy, such as Figure 13 As shown in the above embodiment, “determining the surface properties of the ASEI film” includes:

[0166] S1001, determining the surface bottom area, unit cell energy, number of surface atoms, and total number of atoms in the unit cell of the ASEI film based on the crystal structure data of the ASEI film.

[0167] S1002 , inputting the surface bottom area, the unit cell energy, the number of surface atoms, and the total number of atoms in the unit cell into a surface energy equation to determine the surface energy of the ASEI film.

[0168] The unit cell is the smallest repeating unit in a crystal that fully reflects the periodicity and symmetry of the crystal structure. The unit cell energy refers to the energy possessed by a single unit cell, encompassing the kinetic energy and potential energy of the atoms within the unit cell, as well as the interaction energy between atoms. The unit cell energy is a fundamental parameter describing the energy state of a crystal and is crucial for understanding its stability, thermodynamic properties, and various physical processes.

[0169] The surface atom count refers to the number of atoms located on the surface of an ASEI film. Surface atoms possess unique physical and chemical properties due to their environment, which differs from that of bulk atoms. The surface atom count is a key parameter in calculating surface energy, reflecting the number of active sites on the surface and the degree of interaction between the surface and its external environment.

[0170] The total number of atoms in a unit cell refers to the total number of atoms contained within a single unit cell. This parameter reflects the chemical composition and structural complexity of a crystal and is important for calculating various physical properties of the crystal, such as density and specific heat. When calculating surface energy, the total number of atoms in a unit cell can be used for normalization to obtain comparable surface energy values.

[0171] Surface energy refers to the higher energy of a surface compared to the bulk phase due to the unsaturated force field of surface atoms. Surface energy reflects the activity and stability of a surface, and its magnitude is closely related to factors such as the crystal structure, the type and arrangement of surface atoms. Surface energy is a key parameter for measuring the surface properties of ASEI films, significantly influencing their interactions with other substances, such as wetting, adsorption, and chemical reactions.

[0172] In the embodiment of the present application, the theoretical model of the LiF-LiX (X = Mg, Ga, Zn) composite ASEI film is constructed using the CASTEP module in the Materials Studio software, and the calculation formula of the surface energy Esurf is shown in (5).

[0173]

[0174] In formula (5), A represents the bottom area of ​​the surface, Eslab represents the energy of the surface, Ebulk represents the energy of the unit cell, Nslab represents the number of atoms in the surface, and Nbulk represents the total number of atoms in the unit cell.

[0175] In one embodiment, the surface properties include electron work function, such as Figure 14 As shown in the above embodiment, “determining the surface properties of the ASEI film” includes:

[0176] S1101 , determining the crystal vacuum energy level and the crystal Fermi energy level of the ASEI film according to the crystal structure data of the ASEI film.

[0177] S1102 , determining the difference between the crystal vacuum energy level and the crystal Fermi level as the electron work function of the ASEI film.

[0178] The crystal vacuum level refers to the energy state of electrons in the vacuum outside the crystal. At absolute zero, electrons are in their lowest energy state. The energy level corresponding to the minimum energy required to move an electron from the interior of the crystal to the vacuum at infinity is the crystal vacuum level. It serves as a reference energy level, measuring the relative energy level of electrons in the crystal to the external vacuum environment.

[0179] The Fermi level is the chemical potential of electrons in a crystal, that is, the highest energy level that electrons can occupy at absolute zero. The probability of electrons occupying energy levels below this level is 1, while the probability of electrons occupying energy levels above this level is 0. The Fermi level reflects the distribution and energy state of electrons in a crystal and plays a key role in understanding the electrical and optical properties of crystals.

[0180] The electron work function refers to the minimum energy required to move an electron from the interior of a crystal to the vacuum outside the crystal surface. It is equal to the difference between the crystal's vacuum energy level and the crystal's Fermi level and is a key physical quantity that describes the ease with which electrons escape from the crystal surface. The electron work function influences electron transfer and interface properties when the crystal comes into contact with other materials, and is of great significance in fields such as semiconductor devices, optoelectronic materials, and batteries. For example, in batteries, the electron work function of the ASEI film affects the efficiency of charge transfer between it and the electrode, thereby affecting the battery's charge and discharge performance.

[0181] In the embodiment of the present application, the calculation formula of the electron work function W is shown in (6).

[0182] W=E vacuum -E fermi (6)

[0183] In formula (6), E vacuumRepresents the vacuum energy level of the crystal; E fermi represents the Fermi level.

[0184] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0185] Based on the same inventive concept, the present application also provides an artificial solid electrolyte interface membrane performance evaluation device for implementing the artificial solid electrolyte interface membrane performance evaluation method mentioned above. The implementation solution provided by this device is similar to the implementation solution described in the above method. Therefore, the specific limitations of one or more artificial solid electrolyte interface membrane performance evaluation device embodiments provided below can be found in the above-mentioned limitations of the artificial solid electrolyte interface membrane performance evaluation method, and will not be repeated here.

[0186] In one embodiment, Figure 15 As shown, an artificial solid electrolyte interface membrane performance evaluation device is provided, including: a determination module 1201, a matching module 1202 and an evaluation module 1203, wherein:

[0187] Determination module 1201, for constructing an artificial solid electrolyte interface (ASEI) membrane based on crystal structure data and determining surface properties of the ASEI membrane;

[0188] Matching module 1202, for constructing a heterojunction structure of the ASEI film according to the surface properties, and performing lattice matching processing on the heterojunction structure to obtain an ASEI film interface model;

[0189] The evaluation module 1203 is used to perform performance evaluation calculations on the ASEI film interface model to determine the performance parameters of the ASEI film.

[0190] In one embodiment, the performance parameter includes structural stability. The evaluation module 1203 is specifically configured to determine the internal binding energy of the ASEI film interface model; and determine the structural stability of the ASEI film based on the internal binding energy and a preset energy threshold.

[0191] In one embodiment, the evaluation module 1203 is specifically configured to determine the total crystal energy of the ASEI film interface model, the number of atoms constituting the crystal structure data, and the isolated-state energy corresponding to the atoms in an isolated state based on the crystal structure data of the ASEI film interface model; and substitute the total crystal energy, the number of atoms, and the isolated-state energy into the internal binding energy equation to determine the internal binding energy of the ASEI film interface model.

[0192] In one embodiment, the performance parameter includes electronic insulation. The evaluation module 1203 is specifically configured to determine an energy band diagram of the ASEI film interface model, determine a band gap value of the ASEI film interface model based on the energy band diagram, and determine the electronic insulation of the ASEI film based on the size of the band gap value.

[0193] In one embodiment, the performance parameter includes ion transport capability. The evaluation module 1203 is specifically configured to determine the diffusion coefficient and ionic conductivity of the ASEI membrane interface model; and the ion transport capability of the ASEI membrane is determined based on the diffusion coefficient and the ionic conductivity.

[0194] In one embodiment, the performance parameter includes interface wettability. The evaluation module 1203 is specifically configured to determine the interface formation energy of the ASEI film interface model; and determine the interface wettability of the ASEI film based on the interface formation energy and a preset wettability threshold.

[0195] In one embodiment, the evaluation module 1203 is specifically configured to determine the interface area, total energy, first interface energy, and second interface energy of the ASEI film interface model based on the crystal structure data of the ASEI film interface model; and input the interface area, total energy, first interface energy, and second interface energy into an interface formation energy equation to determine the interface formation energy of the ASEI film interface model.

[0196] In one embodiment, the performance parameter includes lithium dendrite suppression capability. The evaluation module 1203 is specifically used to determine the interface energy of the ASEI film interface model; and determine the lithium dendrite suppression capability of the ASEI film based on the interface energy and a preset lithium dendrite suppression threshold.

[0197] In one embodiment, the surface properties include surface energy. The determination module 1201 is specifically configured to determine the surface bottom area, unit cell energy, number of surface atoms, and total number of atoms in the unit cell of the ASEI film based on the crystal structure data of the ASEI film; and input the surface bottom area, unit cell energy, number of surface atoms, and total number of atoms in the unit cell into a surface energy equation to determine the surface energy of the ASEI film.

[0198] In one embodiment, the surface properties include an electron work function. The determination module 1201 is specifically configured to determine the crystal vacuum energy level and the crystal Fermi energy level of the ASEI film based on the crystal structure data of the ASEI film, and determine the difference between the crystal vacuum energy level and the crystal Fermi energy level as the electron work function of the ASEI film.

[0199] Each module in the aforementioned artificial solid electrolyte interface membrane performance evaluation device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0200] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0201] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0202] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0203] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0204] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0205] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for evaluating the performance of an artificial solid electrolyte interface membrane, characterized in that: The method comprises: constructing an artificial solid electrolyte interface (ASEI) membrane based on crystal structure data and determining the surface properties of the ASEI membrane; constructing a heterojunction structure of the ASEI film according to the surface properties, and performing lattice matching processing on the heterojunction structure to obtain an ASEI film interface model; A performance evaluation calculation is performed on the ASEI film interface model to determine the performance parameters of the ASEI film.

2. The method according to claim 1, characterized in that The performance parameters include structural stability. The performance evaluation calculation of the ASEI membrane interface model is performed to determine the performance parameters of the ASEI membrane, including: determining the internal binding energy of the ASEI film interface model; The structural stability of the ASEI film is determined according to the internal binding energy and a preset energy threshold.

3. The method according to claim 2, characterized in that Determining the internal binding energy of the ASEI film interface model includes: Determining, based on the crystal structure data of the ASEI film interface model, the total crystal energy of the ASEI film interface model, the number of atoms constituting the crystal structure data, and the isolated state energy corresponding to the atoms in an isolated state; The total crystal energy, the number of atoms, and the isolated state energy are substituted into an internal binding energy equation to determine the internal binding energy of the ASEI film interface model.

4. The method according to claim 1, wherein The performance parameters include electronic insulation. The performance evaluation calculation of the ASEI film interface model is performed to determine the performance parameters of the ASEI film, including: Determining an energy band diagram of the ASEI film interface model, and determining a band gap value of the ASEI film interface model according to the energy band diagram; The electronic insulation of the ASEI film is determined according to the size of the band gap value.

5. The method according to claim 1, wherein The performance parameters include ion transport capacity, and the performance evaluation calculation of the ASEI membrane interface model is performed to determine the performance parameters of the ASEI membrane, including: Determining the diffusion coefficient and ionic conductivity of the ASEI membrane interface model; The ion transport capacity of the ASEI membrane is determined according to the size of the diffusion coefficient and the size of the ionic conductivity.

6. The method according to claim 1, characterized in that The performance parameters include interface wettability. The performance evaluation calculation of the ASEI film interface model is performed to determine the performance parameters of the ASEI film, including: Determining the interface formation energy of the ASEI film interface model; The interfacial wettability of the ASEI film is determined according to the interface formation energy and a preset wettability threshold.

7. The method according to claim 6, characterized in that Determining the interface formation energy of the ASEI film interface model includes: determining the interface area, total energy, first interface energy, and second interface energy of the ASEI film interface model according to the crystal structure data of the ASEI film interface model; The interface area, total energy, first interface energy and second interface energy are input into an interface formation energy relationship to determine the interface formation energy of the ASEI film interface model.

8. The method according to claim 1, characterized in that The performance parameters include lithium dendrite suppression capability, and the performance evaluation calculation of the ASEI film interface model is performed to determine the performance parameters of the ASEI film, including: Determining the interfacial energy of the ASEI film interface model; The lithium dendrite suppression capability of the ASEI film is determined according to the interface energy and a preset lithium dendrite suppression threshold.

9. The method according to any one of claims 1 to 8, characterized in that The surface properties include surface energy, and determining the surface properties of the ASEI film includes: Determining the surface bottom area, unit cell energy, number of surface atoms, and total number of atoms in a unit cell of the ASEI film according to the crystal structure data of the ASEI film; The surface bottom area, unit cell energy, number of surface atoms and total number of atoms in the unit cell are input into a surface energy relationship to determine the surface energy of the ASEI film.

10. The method according to any one of claims 1 to 8, characterized in that The surface properties include electron work function, and determining the surface properties of the ASEI film includes: determining the crystal vacuum energy level and the crystal Fermi energy level of the ASEI film according to the crystal structure data of the ASEI film; The difference between the crystal vacuum level and the crystal Fermi level is determined as the electron work function of the ASEI film.

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