Electrolyte performance analysis method and system

Abstract

The invention discloses an electrolyte performance analysis method and system, and belongs to the technical field of electrolyte performance analys.The electrolyte performance analysis method includes the steps that after components and proportion data of an electrolyte are determined, calculation models of the corresponding components are constructed according to the components of the electrolyte; determining a model space of the electrolyte, and configuring corresponding components in the model space according to the calculation model of the components and the matching data so as to complete construction of an electrolyte model; determining a target parameter required by electrolyte analysis, and in the operation process of the electrolyte model, obtaining operation data of the target parameter so as to analyze the performance of the electrolyte through the operation data of the target parameter; in the operation process of the electrolyte model, the operation data of the target parameters are synchronously obtained, when the target parameters are multivariate data, the relevance between the multivariate data can be effectively guaranteed, and the accuracy of electrolyte characteristic evaluation is improved.

Description

Technical Field

[0001] The present application belongs to the technical field of electrolyte performance analysis, and specifically relates to an electrolyte performance analysis method and system. Background Art

[0002] At present, when measuring and analyzing electrolyte characteristics, it is difficult to simultaneously obtain the multivariate property data required for electrolyte performance evaluation in the same experiment, resulting in low correlation between data results, reduced accuracy and consistency of evaluation results, and reduced efficiency of the overall evaluation process. Summary of the invention

[0003] Purpose of the invention: This application develops an analysis method and system for electrolyte performance, aiming to solve the technical problem in the prior art that the low correlation between multivariate data leads to reduced accuracy in electrolyte characteristic evaluation.

[0004] Technical solution: In the first aspect, the present application provides a method for analyzing electrolyte performance, comprising:

[0005] determining the composition of the electrolyte and constructing a computational model of the composition;

[0006] Determining the ratio data of the components;

[0007] Determining a model space of the electrolyte, and configuring the components in the model space based on the calculation model and the ratio data to obtain an electrolyte model;

[0008] Determining target parameters, and running the electrolyte model to obtain operating data of the target parameters in the electrolyte model;

[0009] The performance of the electrolyte is analyzed based on the operating data.

[0010] In some embodiments, the step of constructing a computational model of the components comprises:

[0011] determining a structural model of the component;

[0012] A simulation force field is determined, and parameters of the structural model are configured based on the simulation force field to obtain the calculation model.

[0013] In some embodiments, the structural model includes a molecular model, and the step of configuring parameters of the structural model based on the simulation force field includes:

[0014] The bond lengths, bond angles, dihedral angles, and non-bonded interactions of the molecular model are configured.

[0015] In some embodiments, the step of configuring the components in the model space comprises:

[0016] determining the density of the component in the model space;

[0017] The computational model of the components is configured in the model space based on the density.

[0018] In some embodiments, before running the electrolyte model, the electrolyte performance analysis method further includes:

[0019] Based on an energy minimization algorithm, determining a molecular model of an abnormal state in the electrolyte model, and adjusting parameters of the molecular model of the abnormal state to eliminate the abnormal state;

[0020] An annealing calculation is performed on the electrolyte model based on the microcanonical ensemble and the simulated force field to reduce the system energy of the electrolyte model.

[0021] In some embodiments, before running the electrolyte model, the electrolyte performance analysis method further includes:

[0022] Under the condition that the electrolyte model operation condition is controlled to be constant, the electrolyte model is controlled to operate to a thermodynamic equilibrium state.

[0023] In some embodiments, the step of controlling the electrolyte model operating conditions to be constant comprises:

[0024] Controlling the electrolyte model to operate under constant temperature and pressure conditions;

[0025] Alternatively, the electrolyte model is controlled to run under the conditions of constant volume and temperature.

[0026] In some embodiments, the target parameter includes viscosity, and the step of acquiring the operating data of the viscosity includes:

[0027] During the operation of the electrolyte model, a shear simulation calculation is performed to apply a gradient rate to all atoms in the electrolyte model in a specified direction to obtain the viscosity operation data:

[0028]

[0029] Among them, η s is the viscosity; V is the volume of the model space; k B is the Boltzmann constant; T is temperature; t is time; P xy is the pressure tensor in the plane formed by the x-axis and the y-axis in the electrolyte model, P xz is the pressure tensor in the plane formed by the x-axis and the z-axis in the electrolyte model, P yzThe y-axis and the z-axis in the electrolyte model constitute a pressure tensor in the plane, and the x-axis, the y-axis and the z-axis are intersecting coordinate axes in the electrolyte model.

[0030] In some embodiments, the target parameter includes a dielectric constant, and a characterization formula of the operating data of the dielectric constant includes:

[0031]

[0032] Wherein, ε is the dielectric constant; M is the total dipole moment; V is the volume of the model space; k B is the Boltzmann constant; T is the temperature.

[0033] In a second aspect, an embodiment of the present application further provides an electrolyte performance analysis system, comprising:

[0034] A computational model building module determines the components of the electrolyte and builds a computational model of the components;

[0035] A component ratio confirmation module is used to determine the ratio data of the components;

[0036] An electrolyte model building module determines a model space of the electrolyte, and configures the components in the model space based on the calculation model and the ratio data to obtain an electrolyte model;

[0037] Running a data acquisition module to determine target parameters, and running the electrolyte model to acquire operating data of the target parameters in the electrolyte model;

[0038] A performance analysis module analyzes the performance of the electrolyte based on the operation data.

[0039] Beneficial effect: Compared with the prior art, an analysis method for electrolyte performance provided in an embodiment of the present application includes determining the components and ratio data of the electrolyte, and then constructing a calculation model of the corresponding components based on the components of the electrolyte; determining the model space of the electrolyte, and configuring the corresponding components in the model space according to the calculation model and ratio data of the components to complete the construction of the electrolyte model; determining the target parameters required for electrolyte analysis, and obtaining the operating data of the target parameters during the operation of the electrolyte model to analyze the performance of the electrolyte through the operating data of the target parameters; the present application synchronously obtains the operating data of the target parameters during the operation of the electrolyte model, and when the target parameters are multivariate data, the correlation between the multivariate data can be effectively guaranteed, thereby improving the accuracy of the evaluation of electrolyte characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 A flowchart of the steps of the method for analyzing the performance of the electrolyte provided in the embodiment of the present application;

[0042] Figure 2 A specific flow chart of step 100 in the method for analyzing electrolyte performance provided in an embodiment of the present application;

[0043] Figure 3 A specific flow chart of step 300 in the method for analyzing electrolyte performance provided in an embodiment of the present application;

[0044] Figure 4 A schematic diagram of module connections of an electrolyte performance analysis system provided in an embodiment of the present application;

[0045] Figure 5 A connection diagram of an electronic device provided in an embodiment of the present application;

[0046] Figure 6 It is a comparison chart of the experimental value and the calculated value of the electrolyte;

[0047] Figure 7 The graph of electrolyte density change under different Li+ concentrations;

[0048] Figure 8 It is the migration number change diagram under different Li+ concentrations;

[0049] Fig. 9 It is the diffusion coefficient variation diagram under different Li+ concentrations;

[0050] Fig.10 The conductivity change diagram under different Li+ concentrations;

[0051] Fig.11 is the graph of electrolyte concentration and density changing with temperature;

[0052] Fig.12 is the graph of migration number changing with temperature;

[0053] Fig.13 is the graph of the diffusion coefficient changing with temperature;

[0054] Fig.14 is the graph of conductivity changing with temperature;

[0055] Fig.15It is a chart showing the calculation results of various electrolytes with different ratios;

[0056] Fig.16 Molecular model diagram of solvent, additive and lithium salt in the method for analyzing the performance of electrolyte provided in the embodiment of the present application;

[0057] Fig.17 An electrolyte model diagram in the electrolyte performance analysis method provided in an embodiment of the present application;

[0058] Attached figure numerals: 10, calculation model building module; 20, group distribution ratio confirmation module; 30, electrolyte model building module; 40, operation data acquisition module; 50, performance analysis module; 100, memory; 200, processor. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0060] Currently, the precise measurement and analysis of electrolyte characteristics by experimental means faces two core challenges: one is the high resource consumption, including experimental materials, equipment usage and labor costs; the other is the long work cycle, many key tests take days or even weeks, which seriously restricts the efficiency of research and development. In addition, the limitations of traditional experimental methods are becoming increasingly prominent. Specifically, there is usually a one-to-one correlation between a single test method and the physical parameters that can be obtained, which means that each experiment can only evaluate a specific performance indicator in a targeted manner, and it is difficult to simultaneously obtain the multivariate property data required for electrolyte performance evaluation in the same experiment. This fragmented testing method not only reduces the efficiency of the overall evaluation process, but also due to the differences in experimental conditions between independent experiments, such as small changes in temperature and pressure, it is very easy to introduce additional sources of error, thereby affecting the accuracy and consistency of the final results.

[0061] In view of this, an embodiment of the present application provides a method for analyzing electrolyte performance, including determining the components and ratio data of the electrolyte, and then constructing a calculation model of the corresponding components based on the components of the electrolyte; determining the model space of the electrolyte, and configuring the corresponding components in the model space according to the calculation model and ratio data of the components to complete the construction of the electrolyte model; determining the target parameters required for electrolyte analysis, and obtaining the operating data of the target parameters during the operation of the electrolyte model to analyze the performance of the electrolyte through the operating data of the target parameters; the present application synchronously obtains the operating data of the target parameters during the operation of the electrolyte model, and when the target parameters are multivariate data, the correlation between the multivariate data can be effectively guaranteed to improve the accuracy of the electrolyte characteristic evaluation.

[0062] In some embodiments, see Figure 1 , Figure 1 This is a step flow chart of the method for analyzing the performance of the electrolyte provided in an embodiment of the present application. The method for analyzing the performance of the electrolyte provided in an embodiment of the present application is specifically implemented through steps 100 to 500.

[0063] Step 100: Determine the components of the electrolyte and construct a calculation model of the components.

[0064] It is understood that the components of the electrolyte include solvents (such as carbonates), lithium salts (such as LiPF 6 Lithium hexafluorophosphate, LiBF 4 The selection and ratio of each component will affect the conductivity, stability and other properties of the electrolyte. This application models, runs and analyzes the components contained in the electrolyte and the ratio of each component to obtain the influence of specific components and ratios on the performance of the electrolyte. Please refer to Figure 2 , Figure 2 This is a specific flow chart of step 100 in the method for analyzing electrolyte performance provided in an embodiment of the present application. Step 100 is specifically implemented through steps 110 to 120:

[0065] Step 110: Determine the structural model of the component.

[0066] In some embodiments, the structural model of a component comprises a molecular model, see Fig.16 , Fig.16The molecular model diagrams of the solvent, additive and lithium salt in the analysis method of the electrolyte performance provided in the embodiment of the present application, after the molecular model is determined, the molecular model of each component is constructed by chemical drawing software or molecular modeling tools (such as ChemDraw, MarvinSketch, Avogadro, Jmol, PyMOL, BIOVIA Draw, etc.), and all atoms, the connection mode between atoms and the charge distribution should be correctly characterized when constructing the molecular model.

[0067] Step 120: Determine a simulation force field, and configure parameters of the structural model based on the simulation force field to obtain a calculation model.

[0068] It can be understood that after determining the structural model of the component, it is necessary to determine the simulation force field to define and calculate the interaction forces between and within molecules. Specifically, the force field can be selected from COMPASS molecular simulation package force field, COMPASSII molecular simulation package type II force field, COMPASSIII molecular simulation package type III force field or UNIVERSAL universal force field.

[0069] Specifically, when configuring parameters of the structural model, the bond length, bond angle, dihedral angle and non-bonded interaction of the molecular model are configured, wherein the non-bonded interaction includes van der Waals force and electrostatic force. The above parameters can be obtained through experiments and quantum chemical calculations.

[0070] Step 200: Determine the ratio data of the components.

[0071] It can be understood that the ratio data between the components includes the ratio between the various components, for example: a mixed solvent with a ratio of EC (ethylene carbonate): EMC (ethyl methyl carbonate): DMC (dimethyl carbonate) = 25:65:10, and on this basis, 1% VC (vinylene carbonate) and 1.3% FEC (fluoroethylene carbonate) are added as functional additives, and 1 mol / L LiPF 6 (Lithium hexafluorophosphate) is used as a lithium salt and is formulated to form an electrolyte.

[0072] Step 300: Determine the model space of the electrolyte, and configure the components in the model space based on the calculation model and the ratio data to obtain the electrolyte model.

[0073] In some embodiments, the model space of the electrolyte may be a cube or a box with periodic boundary conditions.

[0074] In some embodiments, see Figure 3 , Figure 3 This is a specific flow chart of step 300 in the method for analyzing electrolyte performance provided in an embodiment of the present application. The configuration of components in the model space is specifically implemented through steps 310 to 320:

[0075] Step 310: Determine the density of the component in the model space;

[0076] Step 320: Arrange the computational model of the components in the model space based on the density.

[0077] Understandably, see Fig.17 , Fig.17 The electrolyte model diagram in the electrolyte performance analysis method provided in the embodiment of the present application randomly inserts the calculation model of the components into the model space based on the ratio data between the components, and the electrolyte model is formed after the expected density is reached.

[0078] In some embodiments, when the computational model is placed, multiple iterations of adjustments are required to ensure the uniformity of the distribution of each component and the computational model in the model space and the accuracy of the density.

[0079] In some embodiments, before executing step 400 and running the electrolyte model, the electrolyte performance analysis method provided in the embodiments of the present application further includes performing energy minimization processing and equilibrium simulation processing on the electrolyte model.

[0080] In some embodiments, the step of energy minimization processing includes: after determining the molecular model and simulation force field of the component, configuring the parameters of the molecular model through the simulation force field to geometrically optimize the molecular model and obtain a stable structure under the corresponding simulation force field; after the electrolyte model is constructed, based on the energy minimization algorithm, determining the molecular model of the abnormal state in the electrolyte model, wherein the abnormal state includes overlapping or unnatural high-energy states, and adjusting the parameters of the molecular model of the abnormal state to eliminate the abnormal state; then selecting a microcanonical ensemble (NVE, the total number of particles N, volume V and energy E remain unchanged), performing annealing calculations on the electrolyte model through the simulation force field, and relaxing the molecules in the electrolyte model by increasing the temperature, so that the electrolyte model reaches the most stable low-energy state. It can be understood that during the heating stage of annealing, the temperature is increased so that the molecules in the electrolyte model have greater kinetic energy to break through local energy barriers, allowing the molecules to have a wider range of structural configuration possibilities; during the cooling stage of annealing, the kinetic energy of the molecules decreases, and at the same time, the relative position and configuration will gradually adjust, the total energy of the system will decrease, and a new low-energy configuration will be formed, gradually reaching a stable low-energy state as the temperature decreases.

[0081] In some embodiments, the equilibrium simulation process controls the electrolyte model to run to a thermodynamic equilibrium state while keeping the electrolyte model running under constant conditions, so as to improve the reliability of data during subsequent electrolyte model operation.

[0082] In some embodiments, the operating conditions of the electrolyte model are controlled to be constant, that is, the electrolyte model is controlled to operate under conditions of constant temperature and pressure, such as operating under an NPT (constant temperature and constant pressure) ensemble; or, the electrolyte model is controlled to operate under conditions of constant volume and temperature, such as operating under an NVT (constant temperature and constant volume) ensemble.

[0083] Step 400: Determine the target parameters, run the electrolyte model, and obtain the operating data of the target parameters in the electrolyte model.

[0084] In some embodiments, the target parameter includes viscosity, and the step of acquiring the operating data of the viscosity includes:

[0085] See also Fig.17 , Fig.17 The electrolyte model diagram in the electrolyte performance analysis method provided in the embodiment of the present application, during the operation of the electrolyte model, a shear simulation calculation is performed, and a gradient rate is applied to all atoms in the electrolyte model in a specified direction to obtain the viscosity operation data:

[0086]

[0087] Among them, η s is the viscosity; V is the volume of the model space; k B is the Boltzmann constant; T is temperature; t is time; P xy is the instantaneous pressure tensor in the plane formed by the x-axis and y-axis in the electrolyte model, P xz is the instantaneous pressure tensor in the plane formed by the x-axis and z-axis in the electrolyte model, P yz is the instantaneous pressure tensor in the plane formed by the y-axis and the z-axis in the electrolyte model, and the x-axis, y-axis and z-axis are intersecting coordinate axes in the electrolyte model.

[0088] In some embodiments, the target parameter also includes a dielectric constant, and the characterization formula of the operating data of the dielectric constant includes:

[0089]

[0090] Where ε is the dielectric constant; M is the total dipole moment; V is the volume of the model space; k B is the Boltzmann constant; T is the temperature.

[0091] In some embodiments, the target parameter also includes a diffusion coefficient, expressed as LiPF 6 (lithium hexafluorophosphate) as an example, the steps for obtaining the diffusion coefficient include:

[0092] Opposite + Ions and PF 6 - Ions are labeled by establishing different trajectories under Li+ With PF 6 - The difference between the final position and the initial position of the ion determines the diffusion coefficient of the ion:

[0093]

[0094] Where D is the diffusion coefficient; t is the time; r(t) is the position at time t; and r(0) is the initial position.

[0095] In some embodiments, the target parameter also includes conductivity. A relationship between conductivity and diffusion coefficient is established based on the Einstein relationship to solve the conductivity:

[0096]

[0097] Where, κ is the conductivity; c is the concentration; e is the 0 is the charge at the initial moment; k B is the Boltzmann constant; T is the temperature; D + is the cation diffusion coefficient; D - is the negative ion diffusion coefficient.

[0098] Step 500: Analyze the performance of the electrolyte based on the operating data.

[0099] Understandably, the performance of the corresponding electrolyte formula is evaluated based on the operating data, and the best solvent combination, lithium salt and additive ratio are found to optimize the overall performance of the electrolyte. At the same time, the physical and chemical properties of electrolytes with different formulas obtained by calculation can be summarized to establish a corresponding database. Through a quick search method, the various properties of the required electrolyte coordination can be checked to shorten the R&D time and improve the R&D efficiency.

[0100] It can be understood that an embodiment of the present application provides a method for analyzing electrolyte performance, including determining the components and ratio data of the electrolyte, and then constructing a calculation model of the corresponding components based on the components of the electrolyte; determining the model space of the electrolyte, and configuring the corresponding components in the model space according to the calculation model and ratio data of the components to complete the construction of the electrolyte model; determining the target parameters required for electrolyte analysis, and obtaining the operating data of the target parameters during the operation of the electrolyte model to analyze the performance of the electrolyte through the operating data of the target parameters; the present application synchronously obtains the operating data of the target parameters during the operation of the electrolyte model, and when the target parameters are multivariate data, the correlation between the multivariate data can be effectively guaranteed to improve the accuracy of the electrolyte characteristic evaluation.

[0101] In order to verify the reliability of the analysis method of the electrolyte performance provided in the embodiment of the present application, the present application provides the following multiple groups of electrolytes with different proportions, and the performance of each group of electrolytes is analyzed using the method of the present application and the experimental method respectively:

[0102] In some embodiments, the solvent is mixed in a ratio of EC (ethylene carbonate): EMC (ethyl methyl carbonate): DMC (dimethyl carbonate) = 25:65:10, and 1% VC (vinylene carbonate) and 1.3% FEC (fluoroethylene carbonate) are added as functional additives. In addition, 1 mol / L LiPF 6 (Lithium hexafluorophosphate) is used as a lithium salt to ensure that the electrolyte has good electrochemical properties. Next, based on these formula components, experimental measurements are performed to obtain the actual conductivity of the electrolyte at different temperatures, and the theoretical conductivity at different temperatures is simulated and calculated using the analysis method for electrolyte performance provided in the embodiments of the present application, thereby comparing the experimental values ​​with the calculated values ​​to evaluate the performance consistency of the electrolyte.

[0103] Specifically, the experimental results are shown in Table 1, and the calculation results are shown in Table 2. Figure 6 The figure is a comparison chart of the experimental value and the calculated value of the electrolyte. By comparing the experimental data with the calculated data, it is found that the results of the two are highly consistent, which greatly proves the reliability and confidence of the analysis method of the electrolyte performance provided in the embodiment of the present application.

[0104] Table 1: Experimental values ​​of conductivity at different temperatures

[0105]

[0106]

[0107] Table 2: Simulated values ​​of conductivity at different temperatures

[0108]

[0109] In some embodiments, further simulation calculations are performed on electrolytes with different temperatures, different lithium ion concentrations, and different solvent ratios. First, a solvent mixture of EC (ethylene carbonate): EMC (ethyl methyl carbonate): DMC (dimethyl carbonate) = 30:30:40 is used, and 1.28% VC (vinylene carbonate) is added as a functional additive to adjust the LiPF 6 The concentrations of lithium salt are 0.4mol / L, 0.6mol / L, 0.8mol / L, 1.0mol / L, 1.2mol / L, 1.4mol / L, and 1.6mol / L, respectively. The simulation results Figures 7 to 10 As shown, Figure 7 The electrolyte density changes at different Li+ concentrations. Figure 8 The migration number changes under different Li+ concentrations. Fig. 9 The diffusion coefficient changes under different Li+ concentrations. Fig.10 The conductivity change diagram under different Li+ concentrations. The simulation results of different ion concentrations are fitted, and the fitting curve of density changing with ion concentration is ρ=0.1005c+1.0976, where c is the concentration and ρ is the density. Figure 7 Where x is c, y is ρ; the migration number of Li+ fluctuates around 0.48; the fitting curve of the diffusion coefficient changing with ion concentration is logD=-0.4738c-9.2941, where D is the diffusion coefficient, c is the concentration, Fig. 9 Where x is c, y is logD; the fitting curve of conductivity changing with ion concentration is σ = 1.07c 4 -4.40c 3 +5.76c 2 -2.56c+1.10(0.36≤c≤1.7), where σ is conductivity and c is concentration. Fig.10 Where x is c and y is σ. This can be used to determine the changes in various properties of the electrolyte at other uncalculated lithium ion concentrations.

[0110] In some embodiments, the changes in various properties of the electrolyte as the temperature changes are calculated. Figure 11-Figure 14 These are the simulation results of the electrolyte changing with temperature. Fig.11 is the graph of electrolyte concentration and density changing with temperature, Fig.12 is the graph of migration number changing with temperature, Fig.13 is the graph of the diffusion coefficient changing with temperature, Fig.14 The conductivity changes with temperature. The simulation results at different temperatures are fitted, and it can be seen that the density and concentration decrease with increasing temperature. The fitting curve of concentration changing with temperature is c=-0.0009T+1.2737, where c is the concentration and T is the temperature. Fig.11 Where y is c and x is T; the fitting curve of density changing with temperature is ρ=-0.001T+1.5118, where ρ is density and T is temperature. Fig.11 Where y is ρ, x is T; the migration number of Li+ increases slightly with increasing temperature, and the change range is small; the fitting curve of the diffusion coefficient changing with temperature is logD=-0.0132T-13.622 (T≤288K) and logD=-0.0062T-11.568 (T≥288K), where D is the diffusion coefficient, T is the temperature, and K is the Kelvin temperature scale. Fig.13 Where y is logD, x is T; the fitting curve of conductivity versus temperature is σ=0.0151T-3.5084, where σ is conductivity, T is temperature, Fig.14Where y is σ and x is T. This can be used to determine the changes in various properties of the electrolyte at other uncalculated temperatures.

[0111] In some embodiments, the density, lithium ion diffusion coefficient, migration number, conductivity, viscosity and dielectric constant of electrolytes with different solvent ratios are calculated. Fig.15 This is a chart of various calculation results for electrolytes with different ratios (for example only, including but not limited to this).

[0112] Accordingly, see Figure 4 , Figure 4 This is a schematic diagram of the module connection of the electrolyte performance analysis system provided in the embodiment of the present application. The embodiment of the present application also provides an electrolyte performance analysis system, including:

[0113] The calculation model building module 10 determines the components of the electrolyte and builds a calculation model of the components.

[0114] The component ratio confirmation module 20 determines the component ratio data.

[0115] The electrolyte model building module 30 determines the model space of the electrolyte, and configures the components in the model space based on the calculation model and the ratio data to obtain the electrolyte model.

[0116] The operation data acquisition module 40 determines the target parameter, and operates the electrolyte model to obtain the operation data of the target parameter in the electrolyte model.

[0117] The performance analysis module 50 analyzes the performance of the electrolyte based on the operation data.

[0118] In some embodiments, the computing model building module 10 is specifically used to:

[0119] Determine the structural model of the components.

[0120] The simulation force field is determined, and parameters of the structural model are configured based on the simulation force field to obtain a calculation model.

[0121] In some embodiments, the computing model building module 10 is specifically used to:

[0122] The structural model includes the molecular model, and configures the bond lengths, bond angles, dihedral angles and non-bonded interactions of the molecular model.

[0123] In some embodiments, the electrolyte model building module 30 is specifically used to:

[0124] Determines the density of the species in model space.

[0125] A computational model that configures components in model space based on density.

[0126] In some embodiments, the electrolyte performance analysis system is further used to:

[0127] Based on an energy minimization algorithm, a molecular model of an abnormal state is determined in the electrolyte model, and parameters of the molecular model of the abnormal state are adjusted to eliminate the abnormal state;

[0128] Annealing calculations were performed on the electrolyte model based on the microcanonical ensemble and simulated force field to reduce the system energy of the electrolyte model.

[0129] In some embodiments, the electrolyte performance analysis system is further used to:

[0130] Under the condition that the electrolyte model operation conditions are controlled to be constant, the electrolyte model is controlled to operate to a thermodynamic equilibrium state.

[0131] In some embodiments, the electrolyte performance analysis system is further used to:

[0132] Control the electrolyte model to run under constant temperature and pressure conditions;

[0133] Alternatively, the controlled electrolyte model is run at constant volume and temperature.

[0134] In some embodiments, the electrolyte performance analysis system is further used to:

[0135] During the operation of the electrolyte model, shear simulation calculations are performed to apply a gradient rate to all atoms in the electrolyte model in a specified direction to obtain the viscosity operation data.

[0136] Accordingly, an embodiment of the present application further provides an electronic device, see Figure 5 , Figure 5 A connection diagram of an electronic device provided in an embodiment of the present application includes a memory 100 and a processor 200, the memory 100 and the processor 200 are connected to each other in communication, the memory 100 stores computer instructions, and the processor 200 executes the analysis method of the electrolyte performance provided in the embodiment of the present application by executing the computer instructions. Specifically, the memory 100 and the processor 200 are connected via a communication bus.

[0137] In some embodiments, the processor 200 may be a central processing unit (CPU). The processor 200 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0138] In some embodiments, the memory 100 is a non-transitory computer-readable storage medium that can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the methods in the method embodiments of the present application. The processor 200 executes various functional applications and data processing of the processor 200 by running the non-transitory software programs, instructions and modules stored in the memory 100, that is, implementing the methods in the above method embodiments.

[0139] In some embodiments, the memory 100 may include a program storage area and a data storage area, wherein the program storage area may store an application required for operating the device or at least one function; the data storage area may store data created by the processor 200, etc. In addition, the memory 100 may include a high-speed random access memory 100, and may also include a non-volatile memory 100, such as at least one disk memory 100, a flash memory device, or other non-volatile solid-state memory 100. In some embodiments, the memory 100 may optionally include a memory 100 remotely arranged relative to the processor 200, and these remote memories 100 may be connected to the processor 200 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0140] In some embodiments, one or more modules are stored in the memory 100 and when executed by the processor 200, the methods in the above method embodiments are performed.

[0141] In some embodiments, the specific details of the above-mentioned electronic device can be understood by referring to the corresponding related descriptions and effects in the above-mentioned method embodiments, and will not be repeated here.

[0142] The present application has introduced in detail a method and system for analyzing electrolyte performance provided by the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for analyzing electrolyte performance, characterized in that: include: determining the composition of the electrolyte and constructing a computational model of the composition; Determining the ratio data of the components; Determining a model space of the electrolyte, and configuring the components in the model space based on the calculation model and the ratio data to obtain an electrolyte model; Determining target parameters, and running the electrolyte model to obtain operating data of the target parameters in the electrolyte model; The performance of the electrolyte is analyzed based on the operating data.

2. The method for analyzing electrolyte performance according to claim 1, characterized in that: The step of constructing the computational model of the components comprises: determining a structural model of the component; A simulation force field is determined, and parameters of the structural model are configured based on the simulation force field to obtain the calculation model.

3. The method for analyzing electrolyte performance according to claim 2, characterized in that: The structural model includes a molecular model, and the step of configuring parameters of the structural model based on the simulation force field includes: The bond lengths, bond angles, dihedral angles, and non-bonded interactions of the molecular model are configured.

4. The method for analyzing electrolyte performance according to claim 1, characterized in that: The step of configuring the components in the model space comprises: determining the density of the component in the model space; The computational model of the components is configured in the model space based on the density.

5. The method for analyzing electrolyte performance according to claim 2, characterized in that: Before running the electrolyte model, the electrolyte performance analysis method further includes: Based on an energy minimization algorithm, determining a molecular model of an abnormal state in the electrolyte model, and adjusting parameters of the molecular model of the abnormal state to eliminate the abnormal state; An annealing calculation is performed on the electrolyte model based on the microcanonical ensemble and the simulated force field to reduce the system energy of the electrolyte model.

6. The method for analyzing electrolyte performance according to claim 1, characterized in that: Before running the electrolyte model, the electrolyte performance analysis method further includes: Under the condition that the electrolyte model operation condition is controlled to be constant, the electrolyte model is controlled to operate to a thermodynamic equilibrium state.

7. The method for analyzing electrolyte performance according to claim 6, characterized in that: The step of controlling the electrolyte model operating conditions to be constant comprises: Controlling the electrolyte model to operate under constant temperature and pressure conditions; Alternatively, the electrolyte model is controlled to run under the conditions of constant volume and temperature.

8. The method for analyzing electrolyte performance according to claim 1, characterized in that: The target parameter includes viscosity, and the steps of acquiring the operating data of the viscosity include: During the operation of the electrolyte model, a shear simulation calculation is performed to apply a gradient rate to all atoms in the electrolyte model in a specified direction to obtain the viscosity operation data: Among them, η s is the viscosity; V is the volume of the model space; k B is the Boltzmann constant; T is temperature; t is time; P xy is the pressure tensor in the plane formed by the x-axis and the y-axis in the electrolyte model, P xz is the pressure tensor in the plane formed by the x-axis and the z-axis in the electrolyte model, P yz The y-axis and the z-axis in the electrolyte model constitute a pressure tensor in the plane, and the x-axis, the y-axis and the z-axis are intersecting coordinate axes in the electrolyte model.

9. The method for analyzing electrolyte performance according to claim 1, characterized in that: The target parameter includes a dielectric constant, and the characterization formula of the operating data of the dielectric constant includes: Wherein, ε is the dielectric constant; M is the total dipole moment; V is the volume of the model space; k B is the Boltzmann constant; T is the temperature.

10. An analysis system for electrolyte performance, characterized in that: include: A computational model building module determines the components of the electrolyte and builds a computational model of the components; A component ratio confirmation module is used to determine the ratio data of the components; An electrolyte model building module determines a model space of the electrolyte, and configures the components in the model space based on the calculation model and the ratio data to obtain an electrolyte model; Running a data acquisition module to determine target parameters, and running the electrolyte model to acquire operating data of the target parameters in the electrolyte model; A performance analysis module analyzes the performance of the electrolyte based on the operation data.

Images