Electrolyte material screening method, apparatus, and electronic device

Abstract

The application discloses an electrolyte material screening method and device and electronic equipment. The method comprises the following steps: receiving an electrolyte material screening instruction, wherein the electrolyte material screening instruction carries a target demand index, and the target demand index at least comprises a target stability index and a target conductivity index; in response to the electrolyte material screening instruction, determining a plurality of candidate stability indexes corresponding to a plurality of candidate materials respectively according to structural parameters corresponding to the plurality of candidate materials respectively; determining a plurality of initial materials from the plurality of candidate materials, wherein the candidate stability indexes of the plurality of initial materials are greater than the target stability index; determining initial conductivity indexes corresponding to the plurality of initial materials respectively according to band gap parameters corresponding to the plurality of initial materials respectively; and determining a target material from the plurality of initial materials according to the initial conductivity indexes corresponding to the plurality of initial materials respectively. The application solves the technical problem of low screening efficiency caused by the condition limitation of complex electrolyte structure.

Description

Technical Field

[0001] This invention relates to the field of data processing, and more specifically, to a method, apparatus, and electronic device for screening electrolyte materials. Background Technology

[0002] In related technologies, traditional screening methods, such as experimental synthesis and characterization, and first-principles calculations, are used to screen solid electrolyte materials, but due to limitations such as the complexity of electrolyte structures, there is a technical problem of low screening efficiency.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This invention provides an electrolyte material screening method, apparatus, and electronic device to at least solve the technical problem of low screening efficiency due to limitations such as the complex structure of electrolytes.

[0005] According to one aspect of the present invention, an electrolyte material screening method is provided, comprising: receiving an electrolyte material screening instruction, wherein the electrolyte material screening instruction carries a target demand index, the target demand index including at least a target stability index and a target conductivity index; responding to the electrolyte material screening instruction, determining candidate stability indices corresponding to the plurality of candidate materials based on structural parameters corresponding to the plurality of candidate materials respectively; determining a plurality of initial materials from the plurality of candidate materials whose candidate stability indices are greater than the target stability index; determining initial conductivity indices corresponding to the plurality of initial materials based on band gap parameters corresponding to the plurality of initial materials respectively; and determining a target material from the plurality of initial materials based on the initial conductivity indices corresponding to the plurality of initial materials, wherein the target material is an initial material whose initial conductivity index is greater than the target conductivity index.

[0006] Optionally, determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective structural parameters includes: determining the candidate chemical formula parameters corresponding to each of the multiple candidate materials based on their respective structural parameters; and determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective candidate chemical formula parameters.

[0007] Optionally, determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective structural parameters includes: determining the spatial structural parameters corresponding to each of the multiple candidate materials based on their respective structural parameters; and determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective spatial structural parameters.

[0008] Optionally, before determining the initial conductivity index corresponding to each of the plurality of initial materials based on the band gap parameters corresponding to each of the plurality of initial materials, the method includes: determining the characteristic parameters corresponding to each of the plurality of atomic positions corresponding to each of the plurality of initial materials, wherein the atomic positions are predetermined positions in the structure corresponding to the initial materials; and determining the band gap parameters corresponding to each of the plurality of initial materials based on the characteristic parameters corresponding to each of the plurality of initial materials.

[0009] Optionally, determining the target material based on the initial conductivity index corresponding to the plurality of initial materials includes: when the characteristic parameters include coordination bond parameters and element category parameters, determining the band gap parameters corresponding to the plurality of initial materials based on the coordination bond parameters and element category parameters corresponding to the plurality of initial materials.

[0010] Optionally, determining the bandgap parameter corresponding to each of the plurality of initial materials based on the characteristic parameters corresponding to each of the plurality of initial materials includes: determining the screening weights corresponding to each of the plurality of characteristic parameters; determining, from the plurality of characteristic parameters, a plurality of initial characteristic parameters whose corresponding screening weights are greater than a predetermined weight threshold; determining the correlation index between any two of the plurality of initial characteristic parameters to obtain a plurality of correlation indices; determining the target characteristic parameters corresponding to each of the plurality of initial materials based on the plurality of correlation indices and the plurality of characteristic parameters corresponding to each of the plurality of initial materials; and determining the bandgap parameter corresponding to each of the plurality of initial materials based on the target characteristic parameters corresponding to each of the plurality of initial materials.

[0011] Optionally, determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective structural parameters includes: determining the element radii corresponding to each of the multiple elements included in the multiple candidate materials; determining the tolerance factor corresponding to each of the multiple candidate materials based on the element radii corresponding to the multiple elements respectively, wherein the corresponding tolerance factor characterizes the structural compactness of the corresponding candidate material; and determining the candidate stability index corresponding to each of the multiple candidate materials based on the tolerance factors corresponding to the multiple candidate materials.

[0012] According to one aspect of the present invention, an electrolyte material screening device is provided, comprising: a receiving module for receiving an electrolyte material screening instruction, wherein the electrolyte material screening instruction carries a target demand index, the target demand index including at least a target stability index and a target conductivity index; a response module for responding to the electrolyte material screening instruction and determining a candidate stability index corresponding to a plurality of candidate materials based on structural parameters corresponding to a plurality of candidate materials respectively; a first determining module for determining a plurality of initial materials from the plurality of candidate materials whose candidate stability index is greater than the target stability index; a second determining module for determining an initial conductivity index corresponding to the plurality of initial materials based on band gap parameters corresponding to the plurality of initial materials respectively; and a third determining module for determining a target material from the plurality of initial materials based on the initial conductivity index corresponding to the plurality of initial materials respectively, wherein the target material is an initial material whose initial conductivity index is greater than the target conductivity index.

[0013] According to one aspect of the present invention, an electronic device is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the electrolyte material screening method described in any of the preceding claims.

[0014] According to one aspect of the present invention, a computer-readable storage medium is provided, wherein when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the electrolyte material screening method described in any of the preceding claims.

[0015] In this embodiment of the invention, an electrolyte material screening instruction is received, wherein the electrolyte material screening instruction carries a target demand index, the target demand index including at least a target stability index and a target conductivity index; in response to the electrolyte material screening instruction, a candidate stability index corresponding to each of the candidate materials is determined based on the structural parameters corresponding to each of the candidate materials; from the candidate materials, a plurality of initial materials with a candidate stability index greater than the target stability index are determined; based on the band gap parameters corresponding to each of the initial materials, an initial conductivity index corresponding to each of the initial materials is determined; based on the initial conductivity index corresponding to each of the initial materials, a target material is determined from the plurality of initial materials, wherein the target material is an initial material with an initial conductivity index greater than the target conductivity index. By receiving electrolyte material screening instructions carrying target demand indices, subsequent screening can be conducted in a targeted manner using these indices as the standard. Based on the structural parameters of multiple candidate materials, candidate stability indices are determined, effectively achieving a quantitative assessment of the structural stability of electrolyte materials. Through preliminary screening, identifying initial materials with candidate stability indices greater than the target stability index ensures that electrolyte materials for subsequent conductivity performance evaluation meet application requirements in terms of structural stability, thus avoiding further testing of structurally unstable materials and reducing screening costs. Furthermore, by determining initial conductivity indices corresponding to the bandgap parameters of multiple initial materials, a quantitative assessment of the conductivity performance of electrolyte materials is effectively achieved. By screening target materials with initial conductivity indices greater than the target conductivity index, rapid screening of electrolyte materials meeting the target conductivity requirements is realized, thereby solving the technical problem of low screening efficiency due to limitations such as complex electrolyte structures. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0017] Figure 1 This is a flowchart of an electrolyte material screening method according to an embodiment of the present invention;

[0018] Figure 2 This is a flowchart of an electrolyte material screening method in an optional embodiment of the present invention;

[0019] Figure 3 This is a structural block diagram of an electrolyte material screening device according to an embodiment of the present invention. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0021] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] First, some nouns or terms that appear in the description of the embodiments of this application shall be interpreted as follows:

[0023] XGBoost: XGBoost (eXtreme Gradient Boosting) is an ensemble learning algorithm based on gradient boosting. The core of XGBoost lies in building multiple decision tree models and combining them to improve prediction accuracy. It optimizes by minimizing an objective function that includes a regularization term for the model's prediction error and model complexity. XGBoost also supports custom loss functions, making it applicable to various machine learning tasks such as classification and regression.

[0024] Materials Project API: The Materials Project API is an interface that provides data for the fields of materials science and engineering. Materials Project is an open-source database and toolset, and this API allows users to programmatically access a large amount of data in Materials Project, including information such as material structure, properties, phase diagrams, and synthesis pathways.

[0025] F-score: F-score is one of the commonly used evaluation metrics in classification problems. It takes into account both precision and recall. In classification problems, F-score can evaluate the performance of the model and, together with other evaluation metrics (such as accuracy, AUC, etc.), comprehensively consider the quality of the model.

[0026] Example 1

[0027] According to an embodiment of the present invention, an embodiment of an electrolyte material screening method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0028] Figure 1 This is a flowchart of an electrolyte material screening method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0029] S102, receive an electrolyte material screening instruction, wherein the electrolyte material screening instruction carries a target demand index, and the target demand index includes at least: a target stability index and a target conductivity index;

[0030] In step S102 of this application, an electrolyte material screening instruction is received.

[0031] This includes an electrolyte material screening instruction, which is used to initiate the screening of electrolyte materials. This instruction carries target requirement indices for selecting specific target materials. For example, it could screen for solid-state electrolyte materials with high ionic conductivity and good chemical stability, suitable for lithium-ion batteries, or novel garnet-structured solid-state electrolyte materials with a band gap above 4 eV and a tolerance factor between 0.9 and 1.1.

[0032] This includes a target demand index, which is pre-set based on the required electrolyte material. This index characterizes the performance of the target material, reflecting its suitability and performance requirements in a specific application scenario. It can include the physical and chemical properties of the electrolyte material. The target demand index may include a target stability index and a target conductivity index.

[0033] This involves a target stability index, which is pre-defined based on the desired electrolyte material and is used to quantify the stability of the electrolyte material's structure and chemical properties under specific environmental or conditions. For example, in the screening of solid-state battery electrolyte materials, the target stability index can be a chemical formula parameter, crystal structure parameter (e.g., space structure parameter, or space group), etc.

[0034] This involves a target conductivity index, which is a pre-defined index based on the required electrolyte material and is used to quantify the conductivity of the electrolyte material. For example, the target conductivity index can be a set ionic conductivity threshold or a band gap value.

[0035] By receiving electrolyte material screening instructions carrying target demand indices, and these target demand indices include at least the target stability index and the target conductivity index, it is helpful to use the target demand index as the screening standard for electrolyte materials in a targeted manner. This ensures that the electrolyte materials selected can meet the application requirements, improves the targeting and accuracy of the screening, and thus improves the efficiency of subsequent screening for target materials.

[0036] Furthermore, the setting of target demand indices is not limited to target stability and target conductivity indices; it can also include other key performance indicators, such as electrochemical window, ion transference number, and thermal stability. Comprehensive consideration of these indices allows for a more complete evaluation of the material's overall performance, ensuring that the selected materials exhibit excellent electrochemical performance and long-term stability in practical applications.

[0037] S104, in response to the electrolyte material screening instruction, determines the candidate stability index corresponding to each of the candidate materials based on the structural parameters corresponding to each of the candidate materials;

[0038] In step S104 of this application, an electrolyte material screening instruction is responded to, and the candidate stability index corresponding to each of the candidate materials is determined based on the structural parameters corresponding to each of the candidate materials.

[0039] This involves candidate materials, which are pre-selected electrolyte materials used for screening based on the target demand index.

[0040] This involves structural parameters, which are used to characterize the structural stability of the material being considered. For example, in solid electrolyte materials, these structural parameters may include chemical formula parameters and spatial structure parameters (such as space groups).

[0041] This involves a candidate stability index, which is a parameter determined based on the structural parameters of the candidate material and used to quantify the structural stability of the candidate material.

[0042] In response to the electrolyte material screening instructions, and based on the structural parameters of multiple candidate materials, the candidate stability index was determined for each candidate material. This effectively achieved a quantitative assessment of the structural stability of electrolyte materials, which helps to avoid further testing of structurally unstable materials and saves screening and analysis resources. As a result, structurally stable solid electrolyte materials can be screened efficiently, ensuring that the screened materials meet the application requirements of solid-state battery electrolytes in terms of structure, and providing a foundation for further screening.

[0043] S106, From a pool of candidate materials, identify several initial materials whose candidate stability index is greater than the target stability index;

[0044] In step S106 of this application, several initial materials with a candidate stability index greater than the target stability index were identified.

[0045] This involves initial materials, which are electrolyte materials obtained from candidate materials through stability screening, with the candidate stability index being greater than the target temperature index.

[0046] Through preliminary screening, multiple initial materials are identified from a pool of candidate materials, and the stability index of these initial materials is greater than the target stability index. This ensures that the electrolyte materials for subsequent conductivity performance evaluation meet the application requirements in terms of structural stability, thereby avoiding unnecessary screening of structurally unstable electrolyte materials, reducing screening costs, and improving screening efficiency and accuracy.

[0047] S108, Based on the band gap parameters corresponding to the multiple initial materials, determine the initial conductivity index corresponding to the multiple initial materials respectively;

[0048] In step S108 provided in this application, initial conductivity indices corresponding to the plurality of initial materials are determined.

[0049] This involves the bandgap parameter, which quantifies the energy difference between the top of the valence band and the bottom of the conduction band in the band structure of an electrolyte material. It reflects the transition energy levels of electrons within the electrolyte material, thus affecting its conductivity. For example, in the screening of solid-state electrolyte materials, a bandgap parameter of 2.5 eV indicates that the energy required for an electron to transition from the valence band to the conduction band is 2.5 eV.

[0050] This includes the initial conductivity index, which is determined based on the band gap parameter of the electrolyte material and is used to quantify the conductivity performance of the electrolyte material.

[0051] By determining the initial conductivity index corresponding to each of the multiple initial materials based on their respective band gap parameters, the conductivity performance of the electrolyte material can be clearly defined. This effectively achieves a quantitative assessment of the conductivity performance of the electrolyte material, which helps to subsequently conduct targeted screening based on the initial conductivity index, improving screening efficiency and accuracy, and ensuring that the conductivity of the screened electrolyte material meets the target requirements.

[0052] S110, based on the initial conductivity index corresponding to each of the multiple initial materials, determine the target material from the multiple initial materials, wherein the target material is the initial material whose initial conductivity index is greater than the target conductivity index.

[0053] In step S110 of this application, the target material was identified.

[0054] This involves a target material, which is an electrolyte material selected from the initial materials whose structural stability and conductivity meet the target requirements. Specifically, the candidate stability index of the target material is greater than the target stability index, and its initial conductivity index is greater than the target conductivity index.

[0055] By screening multiple initial materials to select target materials with an initial conductivity index greater than the target conductivity index, it is ensured that the obtained electrolyte material not only has a stable structure but also high conductivity. Furthermore, screening based on the initial conductivity index can quickly locate electrolyte materials that meet the target conductivity requirements, making the screening process more accurate and efficient. This helps to solve the technical problem of low screening efficiency due to limitations such as the complexity of electrolyte structures.

[0056] Through the above steps S102-S110, an electrolyte material screening instruction is received, wherein the electrolyte material screening instruction carries a target demand index, which includes at least a target stability index and a target conductivity index; in response to the electrolyte material screening instruction, based on the structural parameters corresponding to the multiple candidate materials, a candidate stability index corresponding to each of the multiple candidate materials is determined; from the multiple candidate materials, multiple initial materials with a candidate stability index greater than the target stability index are determined; based on the band gap parameters corresponding to the multiple initial materials, an initial conductivity index corresponding to each of the multiple initial materials is determined; based on the initial conductivity index corresponding to each of the multiple initial materials, a target material is determined from the multiple initial materials, wherein the target material is an initial material with an initial conductivity index greater than the target conductivity index. By receiving electrolyte material screening instructions carrying target demand indices, subsequent screening can be conducted in a targeted manner using these indices as the standard. Based on the structural parameters of multiple candidate materials, candidate stability indices are determined, effectively achieving a quantitative assessment of the structural stability of electrolyte materials. Through preliminary screening, identifying initial materials with candidate stability indices greater than the target stability index ensures that electrolyte materials for subsequent conductivity performance evaluation meet application requirements in terms of structural stability, thus avoiding further testing of structurally unstable materials and reducing screening costs. Furthermore, by determining initial conductivity indices corresponding to the bandgap parameters of multiple initial materials, a quantitative assessment of the conductivity performance of electrolyte materials is effectively achieved. By screening target materials with initial conductivity indices greater than the target conductivity index, rapid screening of electrolyte materials meeting the target conductivity requirements is realized, thereby solving the technical problem of low screening efficiency due to limitations such as complex electrolyte structures.

[0057] As an optional embodiment, the candidate stability index is determined based on the structural parameters corresponding to the candidate materials, including: determining the candidate chemical formula parameters corresponding to the candidate materials based on the structural parameters corresponding to the candidate materials; and determining the candidate stability index corresponding to the candidate materials based on the candidate chemical formula parameters corresponding to the candidate materials.

[0058] This embodiment describes the specific steps for determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective structural parameters.

[0059] This involves the selection of candidate chemical formula parameters, which are used to represent the material composition of electrolyte materials. These parameters include the chemical formula, element types, and the atomic ratio of each element. These candidate chemical formula parameters can reflect the structural stability of electrolyte materials from the perspective of chemical composition.

[0060] In the steps involved in this embodiment, firstly, the candidate chemical formula parameters corresponding to the candidate materials are determined by the structural parameters corresponding to the candidate materials respectively. Then, the candidate stability index corresponding to the candidate materials is determined based on the candidate chemical formula parameters corresponding to the candidate materials respectively.

[0061] By identifying the structural parameters corresponding to multiple candidate materials, the corresponding chemical formula parameters for each candidate material are determined. This effectively clarifies the structural stability characteristics of the electrolyte material in terms of its chemical composition. Consequently, based on the corresponding chemical formula parameters, the corresponding stability indices for each candidate material can be accurately determined. This allows for efficient and accurate screening based on the stability indices corresponding to the chemical formula parameters, ensuring that the subsequently screened electrolyte materials meet the target requirements in terms of chemical composition while improving the efficiency of electrolyte screening.

[0062] As an optional embodiment, the candidate stability index corresponding to each of the candidate materials is determined based on the structural parameters corresponding to each of the candidate materials, including: determining the spatial structural parameters corresponding to each of the candidate materials based on the structural parameters corresponding to each of the candidate materials; and determining the candidate stability index corresponding to each of the candidate materials based on the spatial structural parameters corresponding to each of the candidate materials.

[0063] This embodiment describes the specific steps for determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective structural parameters.

[0064] This involves spatial structure parameters, which are used to characterize the spatial structure of electrolyte materials. These parameters reflect the spatial structural characteristics of the electrolyte material, and thus its stability. For example, these parameters may include space groups, which reflect the symmetry and arrangement of crystals, and consequently, the stability of the corresponding electrolyte material.

[0065] In the steps involved in this embodiment, firstly, the spatial structural parameters corresponding to the multiple candidate materials are determined based on the structural parameters corresponding to the multiple candidate materials. Then, based on the spatial structural parameters corresponding to these candidate materials, the candidate stability index corresponding to the multiple candidate materials is determined.

[0066] By determining the spatial structural parameters corresponding to multiple candidate materials, the structural stability characteristics of the electrolyte material in terms of spatial structure were effectively clarified. Based on these spatial structural parameters, the candidate stability indices for each candidate material were accurately determined. This allows the stability of the electrolyte material to be accurately reflected by the candidate stability indices corresponding to the spatial structural parameters, providing a basis for subsequent electrolyte material screening. This ensures that the selected electrolyte materials meet the target requirements in terms of spatial structure, while improving the efficiency of electrolyte screening.

[0067] As an optional embodiment, before determining the initial conductivity index corresponding to each of the multiple initial materials based on the multiple band gap parameters corresponding to each of the multiple initial materials, the method includes: determining the characteristic parameters corresponding to each of the multiple atomic positions corresponding to each of the multiple initial materials, wherein the atomic positions are predetermined positions in the structure corresponding to the initial materials; and determining the band gap parameters corresponding to each of the multiple initial materials based on the characteristic parameters corresponding to each of the multiple initial materials.

[0068] In this embodiment, specific steps are described before determining the initial conductivity index corresponding to each of the multiple initial materials based on the multiple band gap parameters corresponding to the multiple initial materials.

[0069] This involves atomic positions, which are the specific locations of the atoms of each element in the structure of the electrolyte material. For example, for an A3B2C3X12 type material, the atomic positions can be divided into A-sites, B-sites, C-sites, and X-sites. The types and arrangements of atoms at these positions have a direct impact on the electrochemical performance and structural stability of the electrolyte material.

[0070] This involves characteristic parameters, which are used to characterize the properties of electrolyte materials. These parameters can include chemical and physical characteristics, reflecting the physical and chemical properties of the electrolyte material. For example, in the screening of solid electrolyte materials, these characteristic parameters may include the atomic number of the element at the corresponding position, polarizability, covalent bond length, van der Waals radius, first ionization energy, number of valence electrons, and electronegativity. By obtaining these characteristic parameters, the correlation between the constituent elements of the electrolyte material and their corresponding properties can be determined.

[0071] In the steps involved in this embodiment, before determining the initial conductivity index corresponding to the multiple initial materials, the characteristic parameters corresponding to the multiple atomic positions corresponding to the multiple initial materials are first determined, and then the band gap parameters corresponding to the multiple initial materials are determined according to the characteristic parameters corresponding to the multiple initial materials.

[0072] By determining the characteristic parameters corresponding to multiple atomic positions of multiple initial materials, a comprehensive and accurate characterization of electrolyte materials can be achieved. This enables accurate prediction of the band gap parameters corresponding to multiple initial materials, thereby ensuring that the screened electrolyte materials can meet the target requirements and improving the accuracy and efficiency of electrolyte screening.

[0073] As an optional embodiment, the target material is determined based on the initial conductivity index corresponding to the multiple initial materials, including: when the characteristic parameters include coordination bond parameters and element category parameters, the band gap parameters corresponding to the multiple initial materials are determined based on the coordination bond parameters and element category parameters corresponding to the multiple initial materials.

[0074] In this embodiment, the specific steps for determining the target material based on the initial conductivity index corresponding to multiple initial materials are described.

[0075] This involves coordinate bond parameters, which characterize the properties of coordinate bonds formed between element atoms and surrounding atoms in electrolyte materials. In solid electrolyte materials, different element atoms occupy different positions, such as the A, B, C, and X positions in a garnet-type structure. The coordinate bond characteristics between the element atom at each position and its surrounding atoms are different. Coordinate bond parameters include, but are not limited to, coordination number, bond length, bond angle, and bond energy.

[0076] This involves element category parameters, which are used to characterize the element categories in electrolyte materials. Different element categories have different properties, which in turn affect the performance of electrolyte materials.

[0077] In the steps involved in this embodiment, when the characteristic parameters include coordination bond parameters and element category parameters, the band gap parameters corresponding to the multiple initial materials are determined according to the coordination bond parameters and element category parameters corresponding to the multiple initial materials respectively.

[0078] Through the above steps, with characteristic parameters including coordination bond parameters and element category parameters, a comprehensive evaluation of the coordination number, bond length, bond angle, bond energy, and element category of electrolyte materials is achieved. This helps to accurately predict the corresponding band gap parameters of electrolyte materials, thereby improving the accuracy of band gap parameter prediction. Furthermore, predicting band gap parameters using characteristic parameters including coordination bond parameters and element category parameters can avoid subsequent verification of electrolyte materials with poor performance, thus reducing R&D costs and minimizing resource waste.

[0079] As an optional embodiment, determining the bandgap parameters corresponding to the multiple initial materials based on the characteristic parameters corresponding to the multiple initial materials includes: determining the screening weights corresponding to the multiple characteristic parameters; determining multiple initial characteristic parameters from the multiple characteristic parameters whose corresponding screening weights are greater than a predetermined weight threshold; determining the correlation index between any two initial characteristic parameters among the multiple initial characteristic parameters to obtain multiple correlation indices; determining the target characteristic parameters corresponding to the multiple initial materials based on the multiple correlation indices and the corresponding multiple characteristic parameters; and determining the bandgap parameters corresponding to the multiple initial materials based on the target characteristic parameters corresponding to the multiple initial materials.

[0080] This embodiment describes the specific steps for determining the initial conductivity index corresponding to each of the multiple initial materials based on the multiple characteristic parameters corresponding to each of the multiple initial materials.

[0081] This involves selection weights, which represent the relative importance or contribution of feature parameters to the predicted bandgap parameters. These selection weights can be determined using a feature selection model, such as the XGBoost model.

[0082] This involves a predetermined weight threshold, which is a pre-set value used to describe the importance of features in predicting the bandgap parameter. This predetermined weight threshold is used to distinguish which feature pairs have a significant impact on the predicted bandgap parameter and which feature pairs have negligible influence.

[0083] This involves initial feature parameters, which are feature parameters whose screening weight is greater than a predetermined weight threshold.

[0084] This involves correlation indices, which are used to describe the correlation between two feature parameters. For example, the correlation coefficient can be used to represent the correlation index between two feature parameters. By determining the correlation index, it is possible to identify which feature parameters exhibit redundancy or multicollinearity.

[0085] This involves target feature parameters, which are the feature parameters that are finally determined to predict the bandgap parameters after screening weights and related index analysis.

[0086] In the steps involved in this embodiment, firstly, the screening weights corresponding to multiple feature parameters are determined. Then, from the multiple feature parameters, multiple initial feature parameters whose corresponding screening weights are greater than a predetermined weight threshold are determined. Next, the correlation index between any two initial feature parameters is analyzed to obtain multiple correlation indices. Finally, based on the multiple correlation indices and the multiple feature parameters corresponding to them, the target feature parameters corresponding to the multiple initial materials are determined. Then, based on the target feature parameters corresponding to the multiple initial materials, the band gap parameters corresponding to the multiple initial materials are determined.

[0087] By setting predetermined weight thresholds, it is possible to quickly and accurately distinguish which feature parameters have a significant impact on the predicted bandgap parameter and which feature parameters have negligible influence. Initial feature parameters with corresponding screening weights greater than the predetermined weight thresholds can be selected. Furthermore, by determining the correlation index, it is possible to analyze which feature parameters have redundancy or multicollinearity, thereby determining the target feature parameters for predicting the bandgap parameter. This helps to focus on the most relevant and effective feature parameters when predicting the bandgap parameter, improving the accuracy of the prediction and reducing unnecessary waste of computational resources.

[0088] As an optional embodiment, based on the structural parameters corresponding to the multiple candidate materials, the candidate stability index corresponding to each candidate material is determined, including: determining the element radii corresponding to the multiple elements included in the multiple candidate materials; determining the tolerance factor corresponding to each candidate material based on the element radii corresponding to the multiple elements included in the multiple candidate materials, wherein the corresponding tolerance factor characterizes the structural compactness of the corresponding candidate material; and determining the candidate stability index corresponding to each candidate material based on the tolerance factor corresponding to each candidate material.

[0089] This embodiment describes the specific steps for determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective structural parameters.

[0090] This involves elemental radii, which represent the size of an atom's radius within the crystal structure of an electrolyte material. In solid-state electrolytes, these radii not only affect the density of the crystal but also interact with the electrolyte's chemical properties (such as electronegativity and electron affinity), thus influencing its performance. For example, in garnet-type solid-state electrolytes, the radii of elements such as lithium (Li), lanthanum (La), and zirconium (Zr) directly affect the material's ionic conductivity.

[0091] This involves the tolerance factor, a quantitative indicator used to assess the structural stability of crystalline materials. This tolerance factor is typically used in specific types of crystal structures (such as perovskite and garnet structures) and is determined by comparing the proportions of different atomic radii within the material structure. Calculating the tolerance factor reveals the geometric compatibility of the crystal structure and the density of the atomic arrangement, thereby predicting the material's structural stability. For example, a tolerance factor between 0.9 and 1.1 indicates that the electrolyte material has a stable structure, relatively stable interatomic spacing and arrangement, and is not prone to structural phase transitions or degradation.

[0092] In the steps involved in this embodiment, firstly, the element radii corresponding to the multiple elements included in the multiple candidate materials are determined respectively. Then, according to the element radii corresponding to the multiple elements in each candidate material, the tolerance factors corresponding to the multiple candidate materials are determined respectively. The corresponding tolerance factors characterize the structural compactness of the corresponding candidate material. Finally, according to the tolerance factors corresponding to the multiple candidate materials, the candidate stability index corresponding to the multiple candidate materials is determined.

[0093] By determining the element radii corresponding to multiple elements through the above steps, a data foundation is provided for subsequent calculation of tolerance factors. Based on the element radii corresponding to multiple elements in each candidate material, the tolerance factors corresponding to multiple candidate materials are determined. This enables a quantitative assessment of the structural compactness and geometric stability of specific electrolyte materials such as perovskite and garnet, simplifies the assessment process of structural stability, and thus helps to quickly identify structurally stable electrolyte materials.

[0094] Based on the above embodiments and optional embodiments, an optional implementation method is provided, which is described in detail below.

[0095] In related technologies, traditional screening methods, such as experimental synthesis and characterization, and first-principles calculations, are used to screen solid electrolyte materials, but due to limitations such as the complexity of electrolyte structures, there is a technical problem of low screening efficiency.

[0096] There is currently no effective solution to the above problems.

[0097] In view of this, an optional embodiment of the present invention provides an electrolyte material screening method, which can also be called a garnet-type inorganic solid electrolyte material screening method for solid-state lithium batteries based on high-throughput screening technology. It can effectively solve the technical problem of not being able to efficiently and accurately extract invoice information when extracting invoice information.

[0098] Figure 2 This is a flowchart of an electrolyte material screening method in an optional embodiment of the present invention, such as... Figure 2As shown below, a detailed description will be provided.

[0099] S1: Collect data from open-source databases and build a database, including a set of materials to be tested and information such as the chemical formula, band gap, coordination environment, crystal structure, and space group of any of the materials to be tested;

[0100] S2: Chemical formula (same as the above-mentioned candidate chemical formula parameters) screening: A3B2C3X12 type material (same as the above-mentioned target stability index) is obtained from the set of materials to be tested, and the material set S1 is obtained;

[0101] For example, Python is used to connect to the Materials Project API port to collect information on materials with the chemical formula A3B2C3X12, as well as the chemical expression, band gap, coordination environment, crystal structure, space group, etc. of each material, and output to set S1.

[0102] S3: Crystal structure (same as the space structure parameters above) screening: From the material set S1, the structure with space group Ia(-3)d (same as the candidate stability index above) is obtained, and the material set S2 is obtained;

[0103] Through steps S2 and S3, the candidate chemical formula parameters and spatial structure parameters of multiple candidate materials are determined based on their respective structural parameters; and the candidate stability index of multiple candidate materials is determined based on their respective candidate chemical formula parameters and spatial structure parameters.

[0104] S4: Based on the characteristics of the garnet-type structure, the atomic sites of the material (same as the atomic positions mentioned above) are divided into four sites: A site, B site, C site and X site; the coordination information corresponding to each site is 8 coordination, 6 coordination, 4 coordination and 4 coordination, respectively. The element types of all materials in set S2 at the four sites are counted (same as the element category parameters mentioned above).

[0105] S5: Collect the S2 material set according to its chemical formula, and statistically analyze the corresponding characteristic parameters, including the atomic number, polarizability, covalent bond length, van der Waals radius, first ionization energy, number of valence electrons and electronegativity of the elements at the corresponding positions, and establish a database T1;

[0106] S6: For database T1, build an XGBoost classification model and classify the band gap E. gMaterials with a band gap less than 0.5 eV are labeled 0, and those greater than 0 are labeled 1 (same as the initial conductivity index). XGBoost is used for feature selection, and the importance of each feature is evaluated using F-score (same as the selection weight). Features with an F-score above 50 (same as the predetermined weight threshold) are selected (same as the initial feature parameters). The Pearson correlation between these 16 features is then calculated (same as the correlation index). Parameters are adjusted to ensure that the correlation between most features is within 0.2, indicating that these 16 features (same as the target feature parameters) are non-redundant, which helps improve the robustness of the subsequent model. The accuracy of the model is evaluated using ten-fold cross-validation, as detailed in Tables 1 and 2. Table 1 shows the parameters of the XGBoost classification model, and Table 2 shows the evaluation results of the XGBoost classification model.

[0107] S7: Filter the database T1 and retain material data with a band gap (same as the band gap parameter above) of 0.5 eV or higher. Establish an XGBoost regression model. The method is similar to step S6. Use MSE and R2 to evaluate the accuracy of the model. See Table 3 and Table 4 for details. Table 3 shows the parameters of the XGBoost regression model, and Table 4 shows the evaluation results of the XGBoost regression model.

[0108] Table 1

[0109] hyper-parameters XGB-C n_estinators 400 learning_rate 0.07 subsample 0.8 colsample_bytree 0.6 max_depth 2

[0110] Table 2

[0111]

[0112] Table 3

[0113] hyper-parameters XGB-C n_estinators 600 learning_rate 0.077 subsample 0.79 colsample_bytree 0.61 max_depth 6

[0114] Table 4

[0115]

[0116] S8: Receive electrolyte material screening instructions, wherein the electrolyte material screening instructions carry target demand indices, and the target demand indices include at least: target stability index and target conductivity index; in response to the electrolyte material screening instructions, determine the candidate stability indices corresponding to the multiple candidate materials based on the structural parameters corresponding to the multiple candidate materials respectively;

[0117] Specifically, in response to the electrolyte material screening instruction, determining the candidate stability indices for each candidate material based on its structural parameters also includes:

[0118] Determine the element radii of each element included in a plurality of candidate materials; based on the element radii of each element included, determine the tolerance factors of each candidate material, wherein the corresponding tolerance factors characterize the degree of structural compactness of the candidate material.

[0119] Based on the tolerance factors corresponding to the multiple candidate materials, the candidate stability indices corresponding to the multiple candidate materials are determined.

[0120] For example, by shuffling the order of the elements in step S4 and randomly generating new chemical formulas, we obtain material set U1 (similar to the multiple candidate materials mentioned above); we then calculate the elemental radii of each material in U1, determine the tolerance factor, and retain the tolerance factor T. f For materials in the range of 0.9-1.1, a new set is obtained as U2;

[0121] Tolerance factor T f The calculation formula is as follows:

[0122]

[0123] Among them, T f R represents the tolerance factor. A R B R C R X These represent the element radii corresponding to positions A, B, C, and X, respectively.

[0124] S9: Following step S5, establish database W1 from material set U2;

[0125] S10: Use the trained XGBoost classification model to train and classify the band gap values ​​of materials in database W1; retain the materials whose band gap is predicted to be 1 to obtain a new database W2;

[0126] S11: Using the trained XGBoost regression model, predict the band gap values ​​of materials in database W2; based on the band gap values, further retain materials with band gaps greater than 4eV (same as the target conductivity index mentioned above) to obtain material set U3;

[0127] S12: Based on the elemental analysis of U3, and considering factors such as ease of synthesis and structural stability, materials are further screened to obtain the most likely and best novel garnet-type solid electrolyte candidate material (same as the target material mentioned above).

[0128] The XGBoost algorithm is an optimized version of the Gradient Boosting Decision Tree (GBDT) algorithm. It also builds a series of weak learners (CART regression trees) iteratively, but in each iteration, it optimizes the objective function more precisely, including a regularization term, and introduces the concept of gain for each split point, enabling the algorithm to find the optimal split point to minimize the objective function value.

[0129] For a dataset containing n data points in m dimensions, the XGBoost model can be represented as:

[0130]

[0131] in, f represents the total score. k Let x represent the k-th tree. i Let f represent the i-th sample. k (x i F represents the score of the i-th sample in the k-th tree, where F = {f(x) = w} q(x)}(q:R m →{1,2,...,T},w∈R T ) is a set of CART decision tree structures, R m Let R represent the set of m-dimensional real numbers. T Let q represent the T-dimensional set of real numbers, q be the tree structure mapping samples to leaf nodes, T be the number of leaf nodes, and w be the real number fraction of each leaf node. When constructing an XGBoost model, it is necessary to find the optimal parameters based on the principle of minimizing the objective function in order to establish the optimal model.

[0132] The above optional implementation methods can achieve at least the following beneficial effects:

[0133] (1) Compared with related technologies, this invention receives an electrolyte material screening instruction carrying a target demand index, which helps to use the target demand index as the screening standard for electrolyte materials and conduct targeted screening. Based on the structural parameters of multiple candidate materials, the corresponding candidate stability index is determined, which effectively realizes the quantitative evaluation of the structural stability of electrolyte materials. Through preliminary screening, that is, from multiple candidate materials, multiple initial materials with a candidate stability index greater than the target stability index are determined, which ensures that the electrolyte materials for subsequent conductivity performance evaluation can meet the application requirements in terms of structural stability, thereby helping to avoid further testing of structurally unstable materials and reducing screening costs. Based on the band gap parameters of multiple initial materials, the initial conductivity index corresponding to multiple initial materials is determined, which effectively realizes the quantitative evaluation of the conductivity performance of electrolyte materials. By screening target materials with an initial conductivity index greater than the target conductivity index from multiple initial materials, the rapid screening of electrolyte materials that meet the conductivity performance corresponding to the target requirements is realized, thereby solving the technical problem of low screening efficiency due to the limitations of complex electrolyte structure and other conditions.

[0134] (2) Compared with related technologies, the present invention determines the candidate chemical formula parameters corresponding to multiple candidate materials by using the structural parameters corresponding to multiple candidate materials respectively, effectively clarifying the structural stability characteristics characterized by the chemical composition of the electrolyte material. Thus, based on the candidate chemical formula parameters corresponding to multiple candidate materials, the candidate stability index corresponding to multiple candidate materials can be accurately determined. Therefore, based on the candidate stability index corresponding to the chemical formula parameters, efficient and accurate screening can be carried out, thereby ensuring that the electrolyte materials screened subsequently meet the target requirements in terms of chemical composition, while improving the efficiency of electrolyte screening.

[0135] (3) Compared with related technologies, this invention determines the spatial structural parameters corresponding to multiple candidate materials based on the structural parameters corresponding to each candidate material. This effectively clarifies the structural stability characteristics of the electrolyte material in terms of spatial structure. Thus, based on the spatial structural parameters corresponding to these candidate materials, the candidate stability index corresponding to each candidate material is accurately determined. Therefore, the stability of the electrolyte material can be accurately reflected based on the candidate stability index corresponding to the spatial structural parameters. This provides a screening basis for subsequent screening of electrolyte materials, thereby ensuring that the electrolyte materials screened subsequently meet the target requirements in terms of spatial structure and improving the efficiency of electrolyte screening.

[0136] (4) Compared with related technologies, this invention utilizes high-throughput screening technology and deep learning algorithms to set a series of screening conditions based on the correlation between material composition, crystal structure and material properties, thereby achieving the technical effect of battery material screening; it has the technical effects of low cost, high efficiency, accuracy and strong usability.

[0137] (5) Compared with related technologies, the present invention can quickly and accurately identify the feature parameters that play a key role in predicting band gap parameters by setting a predetermined weight threshold, and select the initial feature parameters whose corresponding screening weight is greater than the predetermined weight threshold. Furthermore, by determining the correlation index, it can analyze which feature parameters have redundancy or multicollinearity, thereby determining the target feature parameters for predicting band gap parameters. This helps to focus on the most relevant and effective feature parameters when predicting band gap parameters, improving the accuracy of prediction and reducing unnecessary waste of computational resources.

[0138] (6) Compared with related technologies, this invention provides a data basis for subsequent calculation of tolerance factors by determining the element radii corresponding to multiple elements. Based on the element radii corresponding to multiple elements in each candidate material, the tolerance factors corresponding to multiple candidate materials are determined. This enables quantitative evaluation of the structural compactness and geometric stability of specific electrolyte materials such as perovskite and garnet, simplifies the evaluation process of structural stability, and helps to quickly identify structurally stable electrolyte materials.

[0139] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0140] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0141] Example 2

[0142] According to embodiments of the present invention, an apparatus for implementing the above-described electrolyte material screening method is also provided. Figure 3 This is a structural block diagram of an electrolyte material screening device according to an embodiment of the present invention, such as... Figure 3 As shown, the device includes: a receiving module 302, a response module 304, a first determining module 306, a second determining module 308, and a third determining module 310. The device will be described in detail below.

[0143] A receiving module 302 is used to receive an electrolyte material screening instruction, wherein the electrolyte material screening instruction carries a target demand index, which includes at least a target stability index and a target conductivity index; a response module 304 is connected to the receiving module 302, and is used to determine the candidate stability index corresponding to each of the candidate materials based on the structural parameters corresponding to the candidate materials in response to the electrolyte material screening instruction; a first determining module 306 is connected to the response module 304, and is used to determine a plurality of initial materials from the plurality of candidate materials whose candidate stability index is greater than the target stability index; a second determining module 308 is connected to the first determining module 306, and is used to determine the initial conductivity index corresponding to each of the plurality of initial materials based on the band gap parameters corresponding to the plurality of initial materials; a third determining module 310 is connected to the second determining module 308, and is used to determine the target material from the plurality of initial materials based on the initial conductivity index corresponding to the plurality of initial materials, wherein the target material is an initial material whose initial conductivity index is greater than the target conductivity index.

[0144] It should be noted here that the above-mentioned receiving module 302, response module 304, first determining module 306, second determining module 308 and third determining module 310 correspond to steps S102 to S110 in the implementation of the electrolyte material screening method. The multiple modules and the corresponding steps are the same in terms of implementation examples and application scenarios, but are not limited to the content disclosed in the above embodiment 1.

[0145] Example 3

[0146] According to another aspect of the present invention, an electronic device is also provided, comprising: a processor; and a memory for storing processor-executable instructions, wherein the processor is configured to execute instructions to implement the electrolyte material screening method of any of the above embodiments.

[0147] Example 4

[0148] According to another aspect of the present invention, a computer-readable storage medium is also provided, which, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to perform the electrolyte material screening method described above.

[0149] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0150] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0151] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0152] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0153] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0154] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0155] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for screening electrolyte materials, characterized in that, include: Receive an electrolyte material screening instruction, wherein the electrolyte material screening instruction carries a target demand index, and the target demand index includes at least: a target stability index and a target conductivity index; In response to the electrolyte material screening instruction, the candidate stability index corresponding to each of the multiple candidate materials is determined based on the structural parameters corresponding to each candidate material. From the plurality of candidate materials, a plurality of initial materials with a candidate stability index greater than the target stability index are selected; Based on the band gap parameters corresponding to the plurality of initial materials, the initial conductivity index corresponding to each of the plurality of initial materials is determined; Based on the initial conductivity index corresponding to the plurality of initial materials, a target material is determined from the plurality of initial materials, wherein the target material is an initial material whose initial conductivity index is greater than the target conductivity index; The step of determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective structural parameters includes: determining the element radii corresponding to each of the multiple elements included in the multiple candidate materials; determining the tolerance factor corresponding to each of the multiple candidate materials based on the element radii corresponding to the multiple elements, wherein the corresponding tolerance factor characterizes the structural compactness of the corresponding candidate material; and determining the candidate stability index corresponding to each of the multiple candidate materials based on the tolerance factor corresponding to each of the multiple candidate materials. Before determining the initial conductivity index corresponding to each of the plurality of initial materials based on the band gap parameters corresponding to each of the plurality of initial materials, the process includes: determining characteristic parameters corresponding to each of the plurality of atomic positions corresponding to each of the plurality of initial materials, wherein the atomic positions are predetermined positions in the structure corresponding to the initial materials; and, when the characteristic parameters include coordination bond parameters and element category parameters, determining the band gap parameters corresponding to each of the plurality of initial materials based on the coordination bond parameters and element category parameters corresponding to each of the plurality of initial materials.

2. The method according to claim 1, characterized in that, The step of determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective structural parameters includes: Based on the structural parameters corresponding to the plurality of candidate materials, the chemical formula parameters corresponding to the plurality of candidate materials are determined. Based on the candidate chemical formula parameters corresponding to the multiple candidate materials, the candidate stability index corresponding to each of the multiple candidate materials is determined.

3. The method according to claim 1, characterized in that, The step of determining the candidate stability index corresponding to each of the multiple candidate materials based on their respective structural parameters includes: Based on the structural parameters corresponding to the plurality of candidate materials, the spatial structural parameters corresponding to the plurality of candidate materials are determined. Based on the spatial structure parameters corresponding to the multiple candidate materials, the candidate stability index corresponding to each of the multiple candidate materials is determined.

4. The method according to claim 1, characterized in that, The determination of bandgap parameters corresponding to the plurality of initial materials based on characteristic parameters corresponding to the plurality of initial materials includes: Determine the screening weights corresponding to each of the multiple feature parameters; From the plurality of feature parameters, determine a plurality of initial feature parameters whose corresponding screening weights are greater than a predetermined weight threshold; Determine the correlation index between any two initial feature parameters among the plurality of initial feature parameters to obtain a plurality of correlation indices; Based on the plurality of relevant indices and the plurality of corresponding feature parameters, the target feature parameters corresponding to the plurality of initial materials are determined respectively; Based on the target characteristic parameters corresponding to the plurality of initial materials, the band gap parameters corresponding to the plurality of initial materials are determined.

5. An electrolyte material screening device, characterized in that, include: A receiving module is used to receive an electrolyte material screening instruction, wherein the electrolyte material screening instruction carries a target demand index, and the target demand index includes at least a target stability index and a target conductivity index; The response module is used to respond to the electrolyte material screening instruction and determine the candidate stability index corresponding to each of the multiple candidate materials based on the structural parameters corresponding to each candidate material. The first determining module is used to determine, from the plurality of candidate materials, a plurality of initial materials whose candidate stability index is greater than the target stability index; The second determining module is used to determine the initial conductivity index corresponding to each of the plurality of initial materials based on the band gap parameters corresponding to the plurality of initial materials respectively; The third determining module is used to determine a target material from the plurality of initial materials based on the initial conductivity index corresponding to each of the plurality of initial materials, wherein the target material is an initial material whose initial conductivity index is greater than the target conductivity index; The response module is further configured to determine the element radii corresponding to the multiple elements included in the plurality of candidate materials; determine the tolerance factors corresponding to the plurality of candidate materials based on the element radii corresponding to the multiple elements included in the plurality of candidate materials, wherein the corresponding tolerance factors characterize the structural compactness of the corresponding candidate material; and determine the candidate stability index corresponding to the plurality of candidate materials based on the tolerance factors corresponding to the plurality of candidate materials. The device is further configured to, before determining the initial conductivity index corresponding to the plurality of initial materials based on the band gap parameters corresponding to the plurality of initial materials, determine the characteristic parameters corresponding to the plurality of atomic positions corresponding to the plurality of initial materials, wherein the atomic positions are predetermined positions in the structure corresponding to the initial materials; and, when the characteristic parameters include coordination bond parameters and element category parameters, determine the band gap parameters corresponding to the plurality of initial materials based on the coordination bond parameters and element category parameters corresponding to the plurality of initial materials.

6. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the electrolyte material screening method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is able to perform the electrolyte material screening method as described in any one of claims 1 to 4.

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