Lithium battery formation temperature influence analysis method

Abstract

The invention discloses a lithium battery formation temperature influence analysis method, and belongs to the technical field of lithium ion battery manufacturing. The method comprises the following steps: constructing an electrolyte molecular model, carrying out molecular dynamics simulation under different temperature conditions, calculating the coordination number, binding energy and change trend of lithium ions, a solvent and anions, and deducing the influence mechanism of temperature on the desolvation process and SEI (solid electrolyte interface) structure formation. The method can be combined with quantum chemical calculation and experimental characterization results to realize systematic evaluation and optimization of lithium ion solvation behaviors, interface chemical components and formation process windows.

Description

Technical Field

[0001] This invention relates to a method for analyzing the influence of lithium battery formation temperature, belonging to the field of lithium-ion battery manufacturing technology. Background Technology

[0002] The formation process of lithium-ion batteries is a crucial step in forming a stable solid electrolyte interphase (SEI) film, which has a decisive impact on the battery's initial efficiency, cycle life, and low-temperature performance. This process mainly involves the reduction and decomposition of the electrolyte on the negative electrode surface to generate a film layer with electronic insulation and ion conductivity. The formation temperature directly affects the solvation structure of lithium ions in the electrolyte and the interfacial reaction pathway, thus determining the composition, thickness, and density of the SEI. Formation strategies at different temperatures have become an important research direction in the development of high-performance batteries.

[0003] Specifically, high temperatures are beneficial for promoting the contact coordination between lithium ions and anions (such as FSI⁻) to form an inorganic-rich SEI, but may also lead to an increase in thermal reduction side reactions of organic solvents, thickening of the film layer, and decreased stability; while low temperatures strengthen the ion-dipole interaction between lithium ions and solvents, resulting in an organic-dominated SEI structure, decreased ion migration ability, and intensified polarization.

[0004] Traditional experimental methods struggle to elucidate the fundamental impact of temperature on solvation structures and SEI formation at the microscopic scale. Molecular dynamics simulations (MDS), as a high-resolution computational method, can quantify the changes in coordination environment and binding energy of lithium ions at different temperatures, providing theoretical support for revealing the formation mechanism. However, there is currently a lack of analytical pathways and evaluation methods for applying MD simulation systems to optimize lithium battery formation temperatures, hindering their engineering application in battery design and process development.

[0005] Existing optimization methods for formation temperature mostly rely on macroscopic performance experiments and empirical iterations. Evaluation indicators are mainly based on outcome parameters such as capacity, internal resistance, and gas production. There is a lack of a unified evaluation framework that establishes a quantitative correlation between temperature changes and key microscopic characterization quantities such as solvation structure evolution, salt dissociation degree, and SEI precursor reaction tendency. As a result, temperature window screening has strong formulation and system dependence and poor transferability. It often requires a large number of repeated experiments to converge to a usable process range. The research and development cycle is long and it is difficult to explain the mechanism difference of "the same temperature has opposite effects in different electrolyte systems". Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for analyzing the influence of lithium battery formation temperature. This method can reveal the changes in the solvation structure of lithium ions in the electrolyte under different temperature conditions at the molecular level, and quantitatively evaluate the coordination behavior and binding strength between lithium ions and solvents or anions, thereby guiding the optimization of formation process and electrolyte system design. To achieve the above objectives / to solve the above technical problems, the present invention is implemented using the following technical solution: A method for analyzing the influence of lithium battery formation temperature, the method comprising: Establish an initial atomic-level model; Energy minimization is performed on the initial atomic-level model; Molecular dynamics simulations were performed on the initial atomic-level model after energy minimization under two or more temperature conditions to obtain simulation trajectory data; The radial distribution function between lithium ions, solvent, and anions during the simulation process is extracted from the simulated trajectory data. The coordination number of lithium ions is calculated by integration, and the trend of lithium ion change with temperature is compared. Quantum chemistry was used to calculate the lithium ion-ligand binding energy under different coordination structures. Energy interpolation was performed based on the coordination number results to analyze the desolvation trend. Based on the coordination relationships and binding energy changes between lithium ions, solvents, and anions, the compositional and structural characteristics of solid electrolyte interfacial films at different temperatures are analyzed.

[0007] The above technical solution is applicable to various lithium salt and solvent systems. It can reveal the regulatory effect of temperature on the structure of lithium-ion solvation shell and interface film at the atomic scale. It has the advantages of high visualization of results, wide applicability, and strong engineering guidance. It is suitable for fields such as lithium-ion battery electrolyte development, formation process design, and interface stability analysis.

[0008] Optionally, establishing the atomic-level initial model includes: A lithium electrolyte simulation system was established, including lithium salt, main solvent and auxiliary solvent, and periodic boundary conditions were set to establish an atomic-level initial model.

[0009] The technical solution is as follows: By establishing an atomic-level simulation system of lithium electrolyte containing lithium salt, main solvent and auxiliary solvent and applying periodic boundary conditions, key microscopic processes such as solvation competition, salt dissociation and ion pair formation in actual formulations can be realistically reflected at the atomic scale. At the same time, it effectively reduces the statistical bias caused by finite size and boundary effects, and makes the coordination environment, diffusion and binding energy extracted under different temperature conditions more stable and comparable. This provides a consistent and reliable calculation basis for the subsequent construction of a quantitative evaluation path of "temperature-solvation structure-SEI formation tendency".

[0010] Optionally, establishing the lithium electrolyte simulation system includes: The molar ratio of each component in the electrolyte is set according to the experimental conditions; The pre-defined molar ratios of the components in the electrolyte are introduced into a closed space to form an initial simulation system. By randomly distributing all molecules evenly in the initial simulation system, the lithium electrolyte simulation system was established.

[0011] The technical solution is as follows: By setting the molar ratio of each component in the electrolyte according to experimental conditions and introducing them into a closed simulation box in proportion, the molecular dynamics system can be made consistent with the actual formulation in terms of composition, ensuring the specificity and comparability of temperature-dependent analysis of solvation structure and ion interaction. At the same time, by adopting random arrangement and uniform distribution of each molecule in the simulation box, the risk of the initial configuration introducing local aggregation, concentration gradient and non-real pre-organized structure can be reduced, the structural "memory effect" of the system in the equilibrium stage can be reduced, and the convergence efficiency and repeatability of subsequent structural sampling and statistics (such as coordination number, radial distribution, diffusion, etc.) can be improved, thereby enhancing the reliability and engineering reusability of temperature scanning analysis and process window evaluation results.

[0012] Optionally, the lithium salt is one or more of LiFSI, LiTFSI, and LiPF6.

[0013] The proposed technical solution involves limiting the lithium salt to one or more of LiFSI, LiTFSI, and LiPF6, which covers the mainstream lithium salt systems currently used in lithium-ion battery electrolytes. This allows the established molecular dynamics analysis pathway to adapt to the differences in anion structures and solvation characteristics of different salts. Consequently, it enables comparative quantification of the degree of salt dissociation, ion pair / aggregate formation tendency, and solvation shell stability under varying temperature conditions. This enhances the ability to identify the differences in formation temperature windows and SEI formation mechanisms, thereby increasing the method's versatility, transferability, and engineering application scope.

[0014] Optionally, the primary solvent and the secondary solvent include one or more combinations of EC, DEC, DMC, EMC, FEC, EDFA, and HFE.

[0015] The proposed technical solution limits the main solvent and auxiliary solvent to one or more combinations of EC, DEC, DMC, EMC, FEC, EDFA, and HFE, covering typical electrolyte solvent systems such as carbonate-based and fluorinated solvents. This allows molecular dynamics simulations to characterize the viscosity and mass transfer differences, solvation competition, and solvent / additive ratio changes in the first solvation shell of different solvent systems under temperature variations within a unified framework. Furthermore, it quantifies the impact on SEI precursor formation tendency and interfacial reaction pathways, thereby improving the applicability and transferability of formation temperature optimization conclusions to different formulation systems and enhancing the engineering application value of the method in battery formulation design and process development.

[0016] Optionally, the upper limit of the integral of the radial distribution function is selected to be 3.0 Å to 3.5 Å, which is used to calculate the coordination number of the first coordination layer of lithium ions.

[0017] The above technical solution: By limiting the upper limit of the integral of the radial distribution function to the range of 3.0 Å to 3.5 Å, the main peak region of the first coordination layer of lithium ions can be captured more stably, avoiding the miscalculation of the second coordination layer or long-range structures caused by thermal fluctuations into the coordination statistics, thereby improving the physical consistency of the coordination number calculation of the first coordination layer and the repeatability of cross-temperature comparisons; on this basis, the solvation shell reconstruction and ligand substitution behavior caused by temperature changes can be identified more sensitively, providing a more reliable quantitative input for subsequent evaluation of mapping micro-coordination indices to the formation temperature window.

[0018] Optionally, the binding energy is calculated using density functional theory optimization with B3LYP functional and 6-311G(d,p) basis set, and the binding energy value under arbitrary coordination number is estimated by linear interpolation.

[0019] The technical solution involves using the B3LYP functional and the 6-311G(d,p) basis set to optimize different coordination configurations using density functional theory. This allows for the high-precision acquisition of stable configurations and corresponding binding energies of lithium-ion-solvent / anion coordination systems, providing a traceable quantitative energy scale for molecular dynamics statistical results. Furthermore, by estimating the binding energy at any coordination number using linear interpolation, the discrete quantitative calculation results can be made continuous and directly matched with the coordination number distribution extracted during temperature scanning. This enables rapid evaluation and batch comparison of the "temperature-coordination structure-binding energy" index, reducing reliance on numerous repetitive quantum chemical calculations and improving the engineering efficiency and scalability of the analytical pathway.

[0020] Optionally, the calculation of lithium-ion-ligand binding energy under different coordination structures includes: The binding energy between lithium ions and different numbers of solvent molecules was calculated using density functional theory to characterize the trend of coordination strength variation. The formula for calculating the binding energy is as follows: , in, The binding energy is expressed in kcal / mol. For Li + The total energy of the complex formed with n solvent molecules; To isolate Li + The energy of ions; Let be the total energy of n isolated solvent molecules.

[0021] The technical solution is as follows: By calculating the binding energy of complexes formed by lithium ions with different numbers of solvent molecules based on density functional theory, the trend of coordination strength changing with coordination number can be quantitatively characterized on an energy scale, thereby distinguishing the differences in microscopic solvation stability of different solvent systems. The binding energy is defined as the difference between the total energy of the complex and the energy of each isolated component, so that the energy decomposition has a clear physical meaning and is comparable across systems and temperatures. This provides a direct and quantifiable evaluation index for establishing the correlation between "temperature change - coordination structure reconstruction - binding energy change - formation reaction tendency", improving the interpretability and engineering applicability of formation temperature optimization analysis.

[0022] Optionally, the calculation of lithium-ion coordination number by integration includes: The local structure between lithium ions and oxygen atoms in the solvent or anion is calculated using the radial distribution function, and the coordination number is obtained by integrating the following formula: , in, Coordination number, unitless; The particle number density is [particles / ų], where Å is angstrom, 1 Å = 10^-10 m = 0.1 nm; It is a radial distribution function; The distance [Å] is the distance from the lithium ion to the coordinated atom. This is the cutoff distance of the first coordination layer.

[0023] The technical solution is as follows: By integrating the radial distribution function of lithium ions with oxygen atoms in the solvent or anions to calculate the coordination number, the local microstructure in the molecular dynamics trajectory can be transformed into a quantifiable statistical index, directly characterizing the composition and density of the first solvation shell. This method introduces particle number density and the cutoff distance of the first coordination layer, giving the coordination number calculation a clear physical meaning and a consistent evaluation benchmark across different temperatures and formulation systems. This allows for more sensitive identification of solvation structure reconstruction caused by temperature changes, the tendency of anions to participate in coordination, and the trend of ion pair / aggregate formation, providing reliable input for subsequent quantitative assessment and mechanistic explanation of the formation temperature window.

[0024] Optionally, the energy minimization process for the atomic-level initial model includes: The molecular force field parameters and atomic charge distribution selected in the atomic-level initial model are set, and the energy of the atomic-level initial model is minimized.

[0025] The above technical solution: By setting the molecular force field parameters and atomic charge distribution of the matching system in the energy minimization stage, and performing energy minimization processing on the atomic-level initial model, it is possible to effectively eliminate atomic overlap and non-physical high-energy configurations caused by random arrangement, reduce the interference of unreasonable short-range repulsion in the initial structure on subsequent dynamic evolution; at the same time, it enables the system to be in a more stable potential energy basin before entering equilibrium and temperature scanning, improves the convergence speed and repeatability of structure sampling, reduces statistical bias caused by differences in initial configuration, and thus improves the reliability of key evaluation indicators such as coordination number, radial distribution function, diffusion and binding energy, and the consistency of cross-temperature comparison.

[0026] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: (1) Revealing the microscopic mechanism of temperature on lithium-ion solvation structure: This invention, through molecular dynamics simulation combined with coordination number and radial distribution function analysis, systematically quantifies the coordination behavior between Li+ and solvent molecules and anions at different temperatures for the first time, revealing the temperature response law of solvation structure, and providing theoretical support for understanding the formation interface reaction mechanism.

[0027] (2) Achieve accurate prediction of Li+ binding energy and desolvation trend: Calculate the binding energy of Li+ complexes with different solvents using density functional theory (DFT), and perform energy interpolation by combining the simulation coordination number results. This can quantitatively assess the trend of desolvation energy barrier with temperature, thereby predicting SEI film formation behavior and improving the scientificity and accuracy of the formation window setting.

[0028] (3) It has both structural evolution tracking and data visualization capabilities: The present invention uses trajectory extraction and statistical analysis technology to track the dynamic change process of solvation shell structure in real time and output visualized coordination network diagram and energy change curve, which effectively assists material researchers in parameter adjustment and result judgment.

[0029] (4) The results are highly comparable to experimental characterization and have verifiability and reliability: The Li+ coordination behavior, binding strength and solvent structure change trends output by simulation can be verified by conventional experimental characterization methods such as XPS, ToF-SIMS and NMR, and have good engineering interpretability and scientific persuasiveness.

[0030] (5) It has wide applicability and engineering expansion potential: This method is not only applicable to specific systems such as EDFA-FEC / LiFSI, but can also be extended to various solvent-lithium salt systems and different electrode materials. It can also be combined with actual process parameters for application scenarios such as battery formation temperature range optimization and electrolyte formulation screening, and has significant industrial application value. Attached Figure Description

[0031] Figure 1The diagram shows a flowchart of the lithium battery formation temperature influence analysis method provided in an embodiment of the present invention. Detailed Implementation

[0032] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0033] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are used only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0034] Example 1

[0035] like Figure 1 As shown, a method for analyzing the influence of lithium battery formation temperature is disclosed, characterized in that the method includes: Step 1: Establish an initial atomic-level model; Step 2: Perform energy minimization processing on the initial atomic-level model; Step 3: Perform molecular dynamics simulations on the initial atomic-level model after energy minimization under two or more temperature conditions, including isobaric and isothermal pre-equilibrium processes and constant-volume isothermal main simulation processes, and obtain simulation trajectory data. Step 4: Extract the radial distribution function between lithium ions, solvent, and anions during the simulation from the simulated trajectory data, calculate its coordination number by integration, and compare its trend with temperature. Step 5: Quantum chemistry is used to calculate the lithium ion-ligand binding energy under different coordination structures. Energy interpolation is performed based on the coordination number results to analyze the desolvation trend. Step 6: Analyze the compositional and structural characteristics of the solid electrolyte interface film at different temperatures based on the coordination relationship and binding energy changes between lithium ions, solvent, and anions.

[0036] The above technical solution is applicable to various lithium salt and solvent systems. It can reveal the regulatory effect of temperature on the structure of lithium-ion solvation shell and interface film at the atomic scale. It has the advantages of high visualization of results, wide applicability, and strong engineering guidance. It is suitable for fields such as lithium-ion battery electrolyte development, formation process design, and interface stability analysis.

[0037] In this embodiment, for step 1, an atomic-level initial model is established. First, a lithium electrolyte simulation system is established, including lithium salt, main solvent and auxiliary solvent, and periodic boundary conditions are set to establish an atomic-level initial model.

[0038] The lithium salt is LiFSI, LiTFSI, LiPF6 or a mixture thereof, and the solvent includes, but is not limited to, one or more combinations of EC ethylene carbonate, DEC diethyl carbonate, DMC dimethyl carbonate, EMC methyl ethyl carbonate, FEC fluoroethylene carbonate, EDFA difluoroethyl acetate, and HFE hydrofluoroether.

[0039] Specifically, it includes: (1) Constructing a molecular dynamics simulation system; This invention first constructs an initial molecular dynamics simulation model based on the lithium-ion battery electrolyte system to be studied. For example, taking the common electrolyte system LiFSI salt (lithium bisfluorosulfonylimide) dissolved in a mixed solvent of EDFA (ethyl difluoroacetate) and FEC (ethylene fluorocarbonate) as an example, its mass ratio or volume fraction is determined. The specific steps are as follows: 1. Component Determination and Proportion Setting: The molar ratio of each component in the electrolyte is set according to the experimental conditions, i.e., Li... + :EDFA:FEC:FSI - The ratio between these two values ​​needs to be such that the simulation model closely approximates the actual electrolyte structure to ensure the representativeness of the simulation results.

[0040] 2. Establish the Simulation Cell: Introduce the above components into a closed space according to the specified proportions to form the initial simulation system. Set periodic boundary conditions for this space, that is, set the boundaries of the simulation cell to be a continuous topological relationship to simulate the infinitely expanding environment of a real liquid system.

[0041] 3. Constructing the initial structure: Distribute all molecules evenly in the simulation box using a "random arrangement" method. To avoid unreasonable repulsive forces caused by molecules being too close together, an "energy minimization" step can be introduced to initially optimize the structure, so that the system is in a reasonable initial potential energy state.

[0042] 4. Definition of Interatomic Interactions: The interaction relationships between atoms are defined by selecting a classical molecular force field (such as Compass II). A force field is a set of parameters that describe the forces and energy relationships between atoms, including bond energy, angular energy, and non-bonded interactions (van der Waals forces, Coulomb forces, etc.), which determine the accuracy and computational efficiency of the simulation.

[0043] 5. Charge distribution setting: Calculate the charge distribution on atoms using quantum chemical methods such as RESP2 (Restrained Electrostatic Potential Fitting) to ensure the accuracy of physical behaviors such as charge transfer and electric field effects in the simulation.

[0044] (2) Temperature response simulation process; After constructing the initial model, a systematic temperature response simulation process is needed to investigate the effects of different temperature conditions on the solvation behavior of lithium ions. This process uses molecular dynamics simulations to model the motion behavior of all atoms in the system and observes the structural responses of lithium ions with solvents or anions by controlling the temperature variable. The specific steps are as follows: 1. System Pre-Equilibrium (Isobaric and Isothermal): Initial equilibrium is achieved using a nonbaric and isothermal (NPT) simulation. During this stage, the volume, temperature, and pressure of the simulated system can be freely adjusted. By constructing a reasonable volume and molecular arrangement, drastic energy fluctuations caused by an unreasonable initial configuration are eliminated. This process typically lasts 1 nanosecond (ns), with the target pressure set to 1 atmosphere (1 bar) and the temperature set to the target study temperature (e.g., -20℃, 25℃, or 45℃) to ensure the system reaches mechanical stability at the study temperature.

[0045] 2. Target Temperature Simulation (Volume-to-Temperature (NVT)): After completing the pre-equilibrium phase, the simulation transitions to the volume-to-temperature (NVT) stage. In this stage, the system volume remains constant, and only temperature and energy fluctuations are controlled. This is used to accurately study the structural response under specific temperature conditions. The simulation time is set to approximately 10 nanoseconds (ns), with a step size of 0.5 femtoseconds (fs) to ensure sufficient time resolution to capture the dynamic changes between molecules.

[0046] 3. Temperature Control Method Description: Throughout the simulation, the Nosé-Hoover temperature control algorithm was used to maintain a constant temperature, simulating the energy exchange between the heat bath system and the system itself. Simultaneously, the Parrinello-Rahman pressure control method was used to maintain a constant pressure, achieving a realistic reproduction of the thermodynamic conditions. The Nosé-Hoover method introduces a virtual "heat exchange variable" to bring the system to a specified temperature; the Parrinello-Rahman method simulates the isotropic or anisotropic deformation of a real system under external pressure.

[0047] 4. Temperature Settings and Simulation Grouping: Three representative temperature points were selected for comparative analysis: -20℃ (low-temperature working environment), 25℃ (normal temperature), and 45℃ (high-temperature environment). Three simulations were run separately, each using the same initial structure and simulation parameters to ensure comparability between variables and eliminate interference from other factors.

[0048] 5. Data Sampling and Trajectory Output: In the later stages of the simulation, atomic trajectories are sampled, and the structure is extracted at regular intervals for subsequent coordination number calculation, radial distribution function analysis, binding energy interpolation calculation, and density state analysis.

[0049] In this embodiment, the calculation of the lithium-ion coordination number specifically includes: Calculate Li using the Radial Distribution Function (RDF) + The local structure and coordination number between the oxygen (O) atom and the solvent or anion can be obtained by integrating the following formula: , in, Coordination number (unitless); The particle number density is [particles / ų], where Å (angstrom) is 1 Å = 10^-10 m = 0.1 nm; The radial distribution function (RDF) measures the distribution of a certain type of particle (e.g., O atom) in a system relative to a reference particle (e.g., Li). + The probability density function of Li at a distance r can be derived by statistically analyzing the simulated trajectory. + The spatial distribution pattern of a certain type of atom in the surrounding solvent or anions; For Li + The distance [Å] to the coordinated atom; The cutoff distance for the first coordination layer is usually determined based on the first minimum value after the first peak of the RDF, and is generally set to 3.0 Å. The upper limit of the integral of the radial distribution function is r. (c) The range of 3.0 Å to 3.5 Å was selected for calculating the coordination number of the first coordination layer of lithium ions.

[0050] This method can calculate Li separately. + With EDFA, FEC, FSI - The coordination number of the O atom in the solvent is used to determine the effect of temperature changes on the coordination trend of the main solvent / anion.

[0051] The technical solution is as follows: By establishing an atomic-level simulation system of lithium electrolyte containing lithium salt, main solvent and auxiliary solvent and applying periodic boundary conditions, key microscopic processes such as solvation competition, salt dissociation and ion pair formation in actual formulations can be realistically reflected at the atomic scale. At the same time, it effectively reduces the statistical bias caused by finite size and boundary effects, and makes the coordination environment, diffusion and binding energy extracted under different temperature conditions more stable and comparable. This provides a consistent and reliable calculation basis for the subsequent construction of a quantitative evaluation path of "temperature-solvation structure-SEI formation tendency".

[0052] In this embodiment, the binding energy is calculated using density functional theory (DFT) optimization with a B3LYP functional and a 6-311G(d,p) basis set, and the binding energy for any coordination number is estimated using linear interpolation. The binding energy calculation specifically includes: Calculate Li using density functional theory (DFT) + The binding energy with different numbers of solvent molecules characterizes the trend of coordination strength variation. The formula for calculating the binding energy is as follows:

[0053] in, The binding energy is expressed in kcal / mol. For Li + The total energy of the complex formed with n solvent molecules; To isolate Li + The energy of ions; Let be the total energy of n isolated solvent molecules (EDFA, FEC, etc.).

[0054] The simulation results can be used to estimate the binding energy at any coordination number through multi-point linear interpolation, and can be used to correspond to the actual coordination number.

[0055] The technical solution involves using the B3LYP functional and the 6-311G(d,p) basis set to optimize different coordination configurations using density functional theory. This allows for the high-precision acquisition of stable configurations and corresponding binding energies of lithium-ion-solvent / anion coordination systems, providing a traceable quantitative energy scale for molecular dynamics statistical results. Furthermore, by estimating the binding energy at any coordination number using linear interpolation, the discrete quantitative calculation results can be made continuous and directly matched with the coordination number distribution extracted during temperature scanning. This enables rapid evaluation and batch comparison of the "temperature-coordination structure-binding energy" index, reducing reliance on numerous repetitive quantum chemical calculations and improving the engineering efficiency and scalability of the analytical pathway.

[0056] In this embodiment, step 6 is further elaborated: the influence mechanism of temperature on the desolvation process and SEI formation is analyzed. Based on the results of RDF and binding energy changes with temperature, a correlation model of temperature on the evolution trend of solvation structure is established, and the influence on the desolvation rate is derived. The coordination number statistics, RDF curves, binding energy curves, desolvation trend diagrams, and their prediction results for SEI composition at different temperatures are output. A standardized data template is formed to guide the following applications: 1. Low-temperature / high-temperature adaptability assessment of the electrolyte system; 2. Optimization of the formation temperature window; 3. Determining the direction of SEI structure regulation.

[0057] In this embodiment, by analyzing the trend of binding energy changes at different temperatures, it is determined whether the energy barrier required for lithium-ion desolvation decreases, thereby inferring the dominance of inorganic components (such as LiF) or organic components (such as ROCO2Li) in the SEI film. The simulation results can be compared and verified with experimental characterization results of X-ray photoelectron spectroscopy (XPS), time-of-flight secondary ion mass spectrometry (ToF-SIMS), and nuclear magnetic resonance (NMR) to improve the reliability and engineering adaptability of the simulation.

[0058] Example 2: Simulation analysis of solvation structure at different temperatures based on LiFSI-EDFA / FEC system This embodiment provides a molecular dynamics simulation method for a typical lithium-ion battery electrolyte system—LiFSI (lithium bisfluorosulfonylimide) dissolved in a mixed solvent of EDFA (ethyl difluoroacetate) and FEC (fluoroethylene carbonate). The simulation temperatures were set to -20℃, 25℃, and 45℃ to study the effect of temperature on Li. + The effect of solvation structure.

[0059] I. System Component Setting: Lithium salt: LiFSI, 20 moles; Solvent: The volume ratio of EDFA to FEC is 9:1, and the total number of solvent molecules is 400. Simulation box size: approximately 4.0 × 4.0 × 4.0 nm³, with periodic boundaries applied; The solution concentration is approximately 1 mol·L⁻¹ -1 II. Force Field and Initial Model Establishment: All molecular parameters are based on the Compass II force field; Atomic charges were fitted from electrostatic potentials calculated using B3LYP / 6-31G* via the RESP2 method; The initial random arrangement structure was generated using the Amorphous Cell module of Materials Studio software, followed by energy minimization.

[0060] III. Molecular Dynamics Simulation Settings: Pre-equilibrium phase: Run for 1 ns under the NPT ensemble, using the Nosé–Hoover hot bath and Parrinello–Rahman pressure control method to set the target temperature and 1 atm pressure; Main simulation phase: Simulations were performed at -20℃, 25℃, and 45℃ for 10 ns with a time step of 0.5 fs under the NVT ensemble. Output frequency: One frame is recorded every 500 steps, for a total of 20,000 frames of trajectory data.

[0061] IV. Data Analysis Methods: Select Li + As a reference atom, calculate its radial distribution function (RDF) compared to that of oxygen atoms in EDFA, FEC, and FSI⁻. Using 3.0 Å as the cutoff radius of the first coordination layer, the coordination number is obtained by integrating the RDF. The formula is as follows: ;

[0062] in, Coordination number (unitless); The particle number density is [particles / ų], where Å (angstrom) is 1 Å = 10^-10 m = 0.1 nm; This is the radial distribution function (RDF). For Li + The distance [Å] to the coordinated atom; This is the cutoff distance of the first coordination layer.

[0063] V. Simulation Results: At -20℃, Li + The coordination number with EDFA was 2.99, FEC was 1.20, and FSI⁻ was 1.58; At 25℃, Li + The coordination number with EDFA was 2.63, FEC was 0.79, and FSI⁻ was 2.09; At 45℃, Li +The coordination number with EDFA is 2.49, FEC is 0.63, and FSI⁻ is 2.29.

[0064] This result indicates that with increasing temperature, Li + It tends to form coordination with the anion FSI⁻, and the participation of solvent (especially FEC) decreases, indicating that high temperature promotes Li⁻ coordination. + - The trend of anion contact ion pair formation.

[0065] Example 3: Li under varying coordination number + Combining energy calculations with desolvation trend analysis; This embodiment uses the Li obtained in Example 1. + Based on the average coordination number at different temperatures, Li was further calculated. + The binding energy between the solvent molecules (EDFA and FEC) was analyzed to determine the influence trend of temperature on the desolvation process.

[0066] 1. Research Objective: During the formation process, lithium ions must first detach from their solvation shell before entering the negative electrode interface to form the SEI film. The energy barrier for desolvation is closely related to the binding strength between the solvent and lithium ions. This embodiment quantifies the trend of binding energy change with temperature to determine the ease of desolvation at different temperatures, and thus infers the influence of temperature on SEI structure formation.

[0067] 2. Source of coordination number data: Based on the MD simulation results of Example 1, at different temperatures, Li + The coordination numbers are as follows: temperature EDFA coordination number FEC coordination number -20℃ 2.99 1.20 25℃ 2.63 0.79 45℃ 2.49 0.63 3. Calculation method: Quantum chemical model establishment: Construction of Li + Complexes formed with EDFA / FEC, such as Li + (EDFA)3, Li + (EDFA)2、Li + (FEC)1 et al.; geometry optimization was performed using the B3LYP functional and the 6-311G(d,p) basis set, and frequency analysis confirmed it as a true minimum structure (without imaginary frequencies); the total energy of each complex was calculated. And the isolated Li + and the energy of solvent molecules and The formula for calculating binding energy is:

[0068] in, The binding energy is expressed in kcal / mol. For Li + The total energy of the complex formed with n solvent molecules; To isolate Li + The energy of ions; Let be the total energy of n isolated solvent molecules (EDFA, FEC, etc.).

[0069] For non-integer coordination numbers, linear interpolation is used to calculate the corresponding binding energy between integer coordination numbers: ; 4. Calculation results: Based on EDFA coordination data, Li + (EDFA) n The interpolation of the binding energy yields the following: temperature EDFA coordination number Binding energy (EDFA) [kcal / mol] -20℃ 2.99 −117.1 25℃ 2.63 −108.9 45℃ 2.49 −105.7 Similarly, Li + (EDFA) n Binding energy interpolation calculations were performed on the complex: temperature FEC coordination number Binding energy (FEC) [kcal / mol] -20℃ 1.20 −58.4 25℃ 0.79 −39.9 45℃ 0.63 −31.8 5. Conclusion Analysis: The results above show that as the temperature increases, Li + The absolute values ​​of the binding energies with EDFA and FEC gradually decrease, indicating that the binding strength between lithium ions and solvents weakens with increasing temperature.

[0070] A decrease in binding energy means a reduction in the energy barrier required for desolvation, therefore, under high-temperature conditions, Li + It is easier to detach from the solvent and enter the negative electrode interface to participate in the formation of SEI film.

[0071] Meanwhile, the binding energy of EDFA decreases more slowly than that of FEC, indicating that EDFA has strong temperature adaptability and stability in the composite coordination structure.

[0072] In summary, this embodiment demonstrates that the method proposed in this invention can effectively predict the trend of temperature influence on the desolvation energy barrier, has a clear physical basis and energy comparability, and provides a quantitative basis for interface structure control and formation process optimization.

[0073] Example 4: Comparison of theoretical deduction and experimental verification of the effect of temperature change on SEI structure; Based on the solvation structure and binding energy trends obtained in Examples 1 and 2, this embodiment further derives the influence of temperature on the composition and structure of the SEI film from a theoretical perspective, and verifies it through experimental methods (XPS, ToF-SIMS, NMR), achieving a comparison and unification between simulation prediction and experimental observation.

[0074] I. Theoretical Derivation Basis Based on the results of Examples 1 and 2, the following conclusions can be drawn: 1. As temperature increases, Li + The coordination number with solvents (EDFA, FEC) decreases, and the anionic FSI... - The participation rate has increased; 2. Li + The reduced binding energy with the solvent indicates that the desolvation process is easier at high temperatures; 3. Anion-dominated solvation structures favor the formation of inorganic components (such as LiF and Li2SO4) in the SEI, while solvent-dominated structures are more likely to form organic components (CHCH3O). - wait).

[0075] Therefore, it can be inferred that: 1. Under −20°C conditions: SEI is rich in organic components, the film is thin but the electrochemical performance is poor; 2. At 25°C: Li⁺ has a moderate solvation structure and easily forms an inorganic-organic composite SEI rich in LiF, with moderate thickness and high stability; 3. At 45°C: FSI⁻ has the highest participation rate, with LiF and SO2 in SEI being the most abundant. - The content increased, but due to the solvent reduction side reaction induced by high temperature, the SEI film thickened and the organic component increased, resulting in decreased interfacial stability.

[0076] II. Experimental Conditions and Analytical Methods To verify the above theoretical predictions, three groups of graphite anode samples were prepared and subjected to formation treatment at -20°C, 25°C, and 45°C (10 cycles, current density of 0.1C), respectively. The samples were then characterized as follows: 1. X-ray photoelectron spectroscopy (XPS) Analyze the elemental composition (C, O, F, S, Li) and their chemical states; focus on: the LiF peak intensity in F 1s, the C–O / C–C ratio in C 1s, and the changes in S=O species in S 2p.

[0077] 2. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) Analysis of the types and spatial distribution of fragments in the SEI membrane; typical ion: CH3O - C2H3O - (Organic); Li - SO2 - (Inorganic); Compare 3D composition maps and depth profiles at different temperatures.

[0078] Nuclear magnetic resonance spectroscopy (NMR) use 7 Li and 17 O NMR, analysis of Li + The drift trend of the solvation environment with temperature changes; the change of chemical shift is observed to verify the evolution of coordination relationships in the simulation.

[0079] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0080] (1) Revealing the microscopic mechanism of temperature-induced lithium-ion solvation structure: This invention, through molecular dynamics simulations combined with coordination number and radial distribution function analysis, systematically quantifies for the first time the effects of temperature on the solvation structure of Li-ion at different temperatures. + The coordination behavior between the solvation structure and solvent molecules and anions reveals the temperature response law of the solvation structure, providing theoretical support for understanding the reaction mechanism of the formation interface.

[0081] (2) Implementing Li + Accurate prediction of the combination of energy and desolvation tendency: Calculation of Li using density functional theory (DFT) + By combining the binding energy of complexes with different solvents with the simulated coordination number results for energy interpolation, the trend of the desolvation energy barrier with temperature can be quantitatively evaluated, thereby predicting SEI film formation behavior and improving the scientificity and accuracy of the formation window setting.

[0082] (3) It has both structural evolution tracking and data visualization capabilities: The present invention uses trajectory extraction and statistical analysis technology to track the dynamic change process of solvation shell structure in real time and output visualized coordination network diagram and energy change curve, which effectively assists material researchers in parameter adjustment and result judgment.

[0083] (4) The results are highly comparable to experimental characterization, demonstrating verifiability and reliability: the simulation output of Li + The trends in coordination behavior, binding strength, and solvent structure can be verified by conventional experimental characterization methods such as XPS, ToF-SIMS, and NMR, demonstrating good engineering interpretability and scientific persuasiveness.

[0084] (5) It has wide applicability and engineering expansion potential: This method is not only applicable to specific systems such as EDFA-FEC / LiFSI, but can also be extended to various solvent-lithium salt systems and different electrode materials. It can also be combined with actual process parameters for application scenarios such as battery formation temperature range optimization and electrolyte formulation screening, and has significant industrial application value.

[0085] 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 technical principles 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 analyzing the influence of lithium battery formation temperature, characterized in that, The method includes: Establish an initial atomic-level model; Energy minimization is performed on the initial atomic-level model; Molecular dynamics simulations were performed on the initial atomic-level model after energy minimization under two or more temperature conditions to obtain simulation trajectory data; The radial distribution function between lithium ions, solvent, and anions during the simulation process is extracted from the simulated trajectory data. The coordination number of lithium ions is calculated by integration, and the trend of lithium ion change with temperature is compared. Quantum chemistry was used to calculate the lithium ion-ligand binding energy under different coordination structures. Energy interpolation was performed based on the coordination number results to analyze the desolvation trend. Based on the coordination relationships and binding energy changes between lithium ions, solvents, and anions, the compositional and structural characteristics of solid electrolyte interfacial films at different temperatures are analyzed.

2. The method for analyzing the influence of lithium battery formation temperature according to claim 1, characterized in that, The establishment of the atomic-level initial model includes: A lithium electrolyte simulation system was established, including lithium salt, main solvent and auxiliary solvent, and periodic boundary conditions were set to establish an atomic-level initial model.

3. The method for analyzing the influence of lithium battery formation temperature according to claim 2, characterized in that, The establishment of the lithium electrolyte simulation system includes: The molar ratio of each component in the electrolyte is set according to the experimental conditions; The pre-defined molar ratios of the components in the electrolyte are introduced into a closed space to form an initial simulation system. By randomly distributing all molecules evenly in the initial simulation system, the lithium electrolyte simulation system was established.

4. The method for analyzing the influence of lithium battery formation temperature according to claim 2, characterized in that, The lithium salt is one or more of LiFSI, LiTFSI, and LiPF6.

5. The method for analyzing the influence of lithium battery formation temperature according to claim 2, characterized in that, The primary solvent and auxiliary solvent include one or more combinations of EC, DEC, DMC, EMC, FEC, EDFA, and HFE.

6. The method for analyzing the influence of lithium battery formation temperature according to claim 1, characterized in that, The upper limit of the integral of the radial distribution function is selected to be 3.0 Å to 3.5 Å, which is used to calculate the coordination number of the first coordination layer of lithium ions.

7. The method for analyzing the influence of lithium battery formation temperature according to claim 1, characterized in that, The binding energy was calculated using density functional theory optimization with B3LYP functional and 6-311G(d,p) basis set, and the binding energy value under arbitrary coordination number was estimated by linear interpolation.

8. The method for analyzing the influence of lithium battery formation temperature according to claim 1, characterized in that, The calculation of lithium-ion-ligand binding energy under different coordination structures includes: The binding energy between lithium ions and different numbers of solvent molecules was calculated using density functional theory to characterize the trend of coordination strength variation. The formula for calculating the binding energy is as follows: ， in, The binding energy is expressed in kcal / mol. For Li + The total energy of the complex formed with n solvent molecules; To isolate Li + The energy of ions; Let be the total energy of n isolated solvent molecules.

9. The method for analyzing the influence of lithium battery formation temperature according to claim 1, characterized in that, The calculation of lithium-ion coordination number by integration includes: The local structure between lithium ions and oxygen atoms in the solvent or anion is calculated using the radial distribution function, and the coordination number is obtained by integrating the following formula: ， in, Coordination number, unitless; The particle number density is [particles / ų], where Å is angstrom, 1 Å = 10^-10 m = 0.1 nm; It is a radial distribution function; The distance [Å] is the distance from the lithium ion to the coordinated atom. This is the cutoff distance of the first coordination layer.

10. The method for analyzing the influence of lithium battery formation temperature according to claim 1, characterized in that, The energy minimization process for the atomic-level initial model includes: The molecular force field parameters and atomic charge distribution selected in the atomic-level initial model are set, and the energy of the atomic-level initial model is minimized.

Images