Coarse graining molecular dynamics simulation method and device for lithium ion battery

Abstract

The invention provides a coarse graining molecular dynamics simulation method and device for a lithium ion battery. The method comprises the following steps: constructing an electrode model of the lithium ion battery; wherein the electrode model is a basic model formed by blending a graphite particle active material and a polymer adhesive of the lithium ion battery; determining simulation conditions of the electrode model to establish an initial model of the lithium ion battery; determining a potential energy function used for describing interaction among particles in the initial model; determining system relaxation of the lithium ion battery according to the initial model and the potential energy function; and taking the system relaxation as a formal simulation initial state to simulate the mixing process of the electrode active material and the adhesive of the lithium ion battery. According to the method and the device, the established model can simulate more extensive electrode materials with similar structural characteristics to graphite materials and high polymer materials, the credibility of simulation results is improved, and the simulation efficiency and accuracy are also improved.

Description

Technical Field

[0001] This application relates to the field of lithium-ion battery technology, and in particular to a coarse-grained molecular dynamics simulation method and apparatus for lithium-ion batteries. Background Technology

[0002] In the fabrication of lithium-ion battery electrodes, many macroscopic physical phenomena often originate from atomic-scale microscopic processes, which directly affect the material structure and dynamic properties at the mesoscopic scale. Therefore, using molecular simulation methods to quantitatively study the physicochemical properties of the system during electrode fabrication is of significant scientific importance.

[0003] However, traditional all-atom simulation methods have several significant limitations: First, these methods require atomic-level modeling of all components in the electrode, such as active materials and binders, and precise description of complex interatomic interactions. This modeling process presents numerous challenges: in the model building phase, not only must the spatial coordinates and physical properties of all atoms in the system be accurately defined, but the corresponding topological structure must also be established, making the process extremely cumbersome. Second, existing force field parameters are usually only applicable to specific systems, and their transferability is often insufficient when applied to novel material systems, which to some extent limits the realization of high-throughput computing and material screening. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a coarse-grained molecular dynamics simulation method and apparatus for lithium-ion batteries. The established model can simulate a wider range of electrode materials with similar structural characteristics to graphite and polymer materials, thereby improving the reliability of the simulation results and also improving the efficiency and accuracy of the simulation.

[0005] In a first aspect, embodiments of this application provide a coarse-grained molecular dynamics simulation method for lithium-ion batteries, the coarse-grained molecular dynamics simulation method comprising: Construct an electrode model for a lithium-ion battery; wherein, the electrode model is the basic model of the blend of graphite particle active material and polymer binder in the lithium-ion battery; Determine the simulation conditions for the electrode model to establish an initial model of the lithium-ion battery; Determine the potential energy function used to describe the inter-particle interactions in the initial model; The system relaxation of the lithium-ion battery is determined based on the initial model and the potential energy function. The system relaxation was used as the initial state for the formal simulation to simulate the mixing process of the electrode active material and binder of the lithium-ion battery.

[0006] Furthermore, the construction of the electrode model for the lithium-ion battery includes: The graphite material with a layered structure in the lithium-ion battery is coarsened into a cubic rigid body composed of multiple coarsened particles; wherein, each layer of the cubic rigid body is composed of multiple coarsened particles laid flat, and each layer is stacked between each other by setting a particle spacing parameter. The polymeric adhesive for the lithium-ion battery is represented as a flexible chain structure formed by the sequential connection of multiple coarse-grained particles; wherein the chain length of the flexible chain structure is controlled by the number of particles. The electrode model is generated based on the cubic rigid body and the flexible chain structure.

[0007] Furthermore, the simulation conditions include the simulation unit system, particle type, simulation box side length, neighbor list, time step, and particle grouping.

[0008] Furthermore, determining the system relaxation of the lithium-ion battery based on the initial model and the potential energy function includes: The electrode material particle system in the initial model is set as a canonical ensemble; The potential energy function is used to model the interactions between particles in the initial model; The Verlet-Velocity algorithm is used to update the particle positions and velocities in the initial model through integration. The system potential energy, particle forces, and structural distribution of the initial model are statistically analyzed until the system of the initial model reaches equilibrium, so as to obtain the relaxation of the system.

[0009] Furthermore, the step of using the system relaxation as the initial state for formal simulation to simulate the mixing process of the electrode active material and binder of the lithium-ion battery includes: The system relaxation is simulated by setting the system configuration and the interparticle interaction potential function, and the time step and simulation duration are determined. The Verlet-Velocity algorithm is used to integrate the particle positions and velocities during system relaxation over time, and the particle trajectory data during system relaxation is output.

[0010] Furthermore, after simulating the mixing process of the electrode active material and binder in the lithium-ion battery, the coarse-grained molecular dynamics simulation method further includes: Using a preset data analysis program, the structure factors of the positive and negative electrode components of the lithium-ion battery under equilibrium conditions and the radial distribution function between each component are calculated, and a simulation animation of the electrode microstructure of the lithium-ion battery and the mixing process of active materials and binders is generated.

[0011] Secondly, embodiments of this application also provide a coarse-grained molecular dynamics simulation device for lithium-ion batteries, the coarse-grained molecular dynamics simulation device comprising: An electrode model construction module is used to construct an electrode model for a lithium-ion battery; wherein, the electrode model is the basic model of the graphite particle active material and polymer binder blend of the lithium-ion battery. An initial model determination module is used to determine the simulation conditions of the electrode model in order to establish an initial model of the lithium-ion battery. The potential energy function determination module is used to determine the potential energy function used to describe the interaction between particles in the initial model; A system relaxation generation module is used to determine the system relaxation of the lithium-ion battery based on the initial model and the potential energy function. The kinetic simulation module is used to simulate the mixing process of the electrode active materials and binders of the lithium-ion battery by using the system relaxation as the initial state for formal simulation.

[0012] Furthermore, when constructing an electrode model for a lithium-ion battery, the electrode model construction module is also used for: The graphite material with a layered structure in the lithium-ion battery is coarsened into a cubic rigid body composed of multiple coarsened particles; wherein, each layer of the cubic rigid body is composed of multiple coarsened particles laid flat, and each layer is stacked between each other by setting a particle spacing parameter. The polymeric adhesive for the lithium-ion battery is represented as a flexible chain structure formed by the sequential connection of multiple coarse-grained particles; wherein the chain length of the flexible chain structure is controlled by the number of particles. The electrode model is generated based on the cubic rigid body and the flexible chain structure.

[0013] Thirdly, embodiments of this application also provide an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the coarse-grained molecular dynamics simulation method for lithium-ion batteries described above are performed.

[0014] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the coarse-grained molecular dynamics simulation method for lithium-ion batteries as described above.

[0015] This application provides a coarse-grained molecular dynamics simulation method and apparatus for lithium-ion batteries. First, an electrode model of the lithium-ion battery is constructed; wherein the electrode model is the basic model for the blending of graphite particle active material and polymer binder in the lithium-ion battery; the simulation conditions of the electrode model are determined to establish an initial model of the lithium-ion battery; a potential energy function is determined to describe the inter-particle interactions in the initial model; the system relaxation of the lithium-ion battery is determined based on the initial model and the potential energy function; finally, the system relaxation is used as the initial state for formal simulation to simulate the mixing process of the electrode active material and binder in the lithium-ion battery.

[0016] This application focuses on factors influencing the performance of lithium-ion cathodes / anodes, such as the ratio of active electrode materials (graphite particles) and binders (polymers), and their bonding strength. It optimizes the electrode model to simulate the battery electrode fabrication process and investigates the interaction mechanisms between the various electrode components at the microscale. The model established in this application can simulate a wider range of electrode materials with similar structural characteristics to graphite and polymers. By employing a coarse-grained approach to simulate the electrode's microscopic system, the simulation system maintains its basic structural framework across the spatial and temporal scales described by the coarse-grained scheme. This allows for description at larger spatial and temporal scales, improving the reliability, efficiency, and accuracy of the simulation results. Furthermore, by simulating the mixing process of active electrode materials (graphite particles) and binders (polymers), the optimal ratio parameters for preparing high-performance electrodes are determined, providing theoretical guidance for experiments.

[0017] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a coarse-grained molecular dynamics simulation method for lithium-ion batteries provided in this application embodiment; Figure 2 This is a schematic diagram of a polymer binder and graphite particle active material in a dry electrode material for a lithium-ion battery provided in an embodiment of this application. Figure 3A simulated structural diagram of a blend of graphite particle active material and polymer binder with different component proportions provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a coarse-grained molecular dynamics simulation device for a lithium-ion battery provided in an embodiment of this application. Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. Based on the embodiments of this application, every other embodiment obtained by those skilled in the art without inventive effort falls within the scope of protection of this application.

[0021] First, the applicable scenarios for this application will be introduced. This application can be applied to the field of lithium-ion battery technology.

[0022] In the fabrication of lithium-ion battery electrodes, many macroscopic physical phenomena often originate from atomic-scale microscopic processes, which directly affect the material structure and dynamic properties at the mesoscopic scale. Therefore, using molecular simulation methods to quantitatively study the physicochemical properties of the system during electrode fabrication is of significant scientific importance.

[0023] Research has revealed several significant limitations of traditional all-atom simulation methods. First, these methods require atomic-level modeling of all components in the electrode, such as active materials and binders, and precise description of complex interatomic interactions. This modeling process presents numerous challenges: in the model construction phase, not only must the spatial coordinates and physical properties of all atoms in the system be accurately defined, but the corresponding topological structure must also be established, making the process extremely cumbersome. Second, existing force field parameters are typically only applicable to specific systems, and their transferability is often insufficient when applied to novel material systems, which to some extent limits the realization of high-throughput computing and material screening.

[0024] Based on this, the embodiments of this application provide a coarse-grained molecular dynamics simulation method for lithium-ion batteries. The established model can simulate a wider range of electrode materials with similar structural characteristics to graphite and polymer materials, thereby improving the reliability of the simulation results and also improving the efficiency and accuracy of the simulation.

[0025] Please see Figure 1 , Figure 1 This is a flowchart illustrating a coarse-grained molecular dynamics simulation method for lithium-ion batteries, provided as an embodiment of this application. Figure 1 As shown in the embodiments of this application, the coarse-grained molecular dynamics simulation method includes: S101, Constructing an electrode model for a lithium-ion battery.

[0026] Regarding step S101 above, in specific implementation, an electrode model of a lithium-ion battery is constructed. According to the embodiments provided in this application, the electrode model is a basic model of the blend of graphite particle active material and polymer binder in a lithium-ion battery.

[0027] As an optional embodiment, regarding step S101 above, constructing the electrode model of the lithium-ion battery includes: Step 1011: The graphite material with a layered structure in the lithium-ion battery is coarsened into a cubic rigid body composed of multiple coarsened particles.

[0028] Here, each layer in the cubic rigid body is composed of multiple coarse-grained particles laid flat, and each layer is stacked with the particle spacing parameter set.

[0029] Dry electrode technology is a novel manufacturing process for lithium-ion batteries. It eliminates the use of solvents in electrode production. Typically, the positive / negative electrode active materials are directly mixed with a binder and then sprayed directly onto the current collector. Alternatively, a self-supporting film can be fabricated using different processes and then laminated with the current collector. Graphite, due to its unique properties, has been widely used in dry electrode technology as an excellent positive / negative electrode active material.

[0030] Regarding step 1011 above, in specific implementation, the layered graphite structure is coarsened into an N*N*N cubic rigid body composed of individual rigid spheres. First, the interlayer spacing of the graphite material is calculated using Avogadro software. Then, a program is written in Perl to determine the position of each sphere and place it in the simulation box. Each layer of graphite material is composed of N*N spheres laid flat. Placing these spheres in parallel within each layer forms the cubic rigid body structure. Based on this, the spacing parameters between spheres in adjacent two-dimensional planes are adjusted by writing a program, thereby changing the interlayer spacing of the layered graphite. This method can also simulate other layered positive / negative electrode active materials besides graphite, and further enhances the study of ion transport between active material layers during subsequent simulations of lithium-ion battery charging and discharging processes.

[0031] Step 1012: The polymeric adhesive of the lithium-ion battery is represented as a flexible chain structure formed by the sequential connection of multiple coarse-grained particles.

[0032] Here, the chain length of the flexible chain structure is controlled by the number of particles.

[0033] Dry-process electrodes do not use solvents during fabrication. The polymer binder only makes point contact with the surface of the active material particles, without affecting the internal contact between the active material particles. This results in tighter contact between the active material particles and better electrode conductivity. Furthermore, Li+ can be more easily inserted and extracted on the surface of the active material, leading to higher capacity and advantages for high-rate discharge.

[0034] Regarding step 1012 above, in specific implementation, the polymer binder is coarsened into polymer chains composed of individual rigid microspheres, and the length of each polymer chain is changed by altering the number of microspheres. The performance of lithium-ion battery electrodes is affected by the proportions of various materials used in electrode fabrication. In flexible chain structures, the proportions of electrode active materials and binders in the electrode composition can be adjusted by modifying the parameters of the number of rigid bodies and the number of polymer chains, thereby achieving the goal of optimizing electrode performance by adjusting the component proportions.

[0035] Step 1013: Generate the electrode model based on the cubic rigid body and the flexible chain structure.

[0036] Regarding step 1013 above, in specific implementation, after the cubic rigid body and flexible chain structure are constructed, an electrode model is generated based on the cubic rigid body and flexible chain structure. In the embodiments provided in this application, the established electrode model, when describing the molecules of components such as active materials (graphite particles) and binders (polymer materials), ignores specific molecular structure information and describes them as spherical coarse-grained particles. Each coarse-grained particle can represent several atoms, several monomers, or even molecular fragments, and the intermolecular interactions are described using classical physical interactions. Please refer to [link to relevant documentation]. Figure 2 , Figure 2 This is a schematic diagram of a polymer binder and graphite particle active material in a dry electrode material for a lithium-ion battery, provided in an embodiment of this application. Figure 2 As shown, the positive / negative electrode active materials (graphite particles) of lithium-ion batteries are represented by layered cubic rigid bodies composed of coarse-grained particles, while the binder (polymer material) is represented by chains formed by coarse-grained particles.

[0037] According to the embodiments provided in this application, a data file readable by LAMMPS, i.e., a model geometry information file, is generated by writing a program. Creating the data file is called the LAMMPS modeling process. LAMMPS can read information such as the side length of the simulation box, the mass of the particles, their initial positions, and bonds through the `read_data` command. Based on the proportion of each component in the electrode material, we use Perl language to write a program to place particles representing each component into a periodic box and generate an input information file for LAMMPS software simulation. The information in the data file is established based on the `atom_style` and the molecular topology. In this simulation, we use the `full` atom_style. The `full` type contains particle information including bond, bond angle, dihedral angle, impproper, and charge.

[0038] S102, determine the simulation conditions of the electrode model to establish the initial model of the lithium-ion battery.

[0039] Regarding step S102 above, in specific implementation, the simulation conditions of the electrode model are determined to establish an initial model of the lithium-ion battery. Specifically, the simulation conditions include the simulation unit system, particle type, simulation box side length, neighbor list, time step, and particle grouping.

[0040] Here, according to the embodiments provided in this application, simulation conditions can be set by writing scripts (in files) required for LAMMPS simulation. Specifically, the in file is divided into six parts: 1. Global parameter settings for simulation; 2. Establishment of the system model (reading the data file and defining grouping information); 3. Setting of potential functions (force fields); 4. Temperature initialization; 5. System relaxation; 6. Formal simulation. The following describes the writing of the in file in more detail. It should be noted that the types of instructions that can be written in the in file are very rich. Here, only the instructions and related examples involved in the simulation of this system are simply listed. The first part, global parameter settings for simulation, contains eight instructions, namely units, dimension, boundary, atom_style, neighbor, neighbor_modify, newton, and timestep. The first instruction, units, is used to set the unit system. The writing rule is: units <style>。第二条指令dimension，用于设置模拟维度。编写规则是：dimension<N>。第三条指令boundary，用于设置边界条件。编写规则是：boundary<x><y><z>。第四条指令atom_style，用于设置原子类型。编写规则是：atom_style<style>。第五条指令neighbor，用于设置建立邻居列表。编写规则是：neighbor<skin><style>。第六条指令neigh_modify，用于设置邻居列表更新频率。编写规则是：neigh_modify<keyword><values>。第七条指令newton，用于设置开启或关闭牛顿第三定律。编写规则是：newton<flag>。第八条指令timestep，用于设置时间步长。编写规则是：timestep。

[0041] 第二部分体系模型的建立包含两条指令，分别是read_data、group。第一条指令read_data，用于读取第二步中编写生成的data文件。编写规则是：read_data<file>。第二条指令group，用于对模型中的粒子进行分组。编写规则是：group<ID><style><args>。第三部分势函数（力场）的设置包含四条指令，分别是pair_style、pair_coeff、bond_style、bond_coeff。

[0042] 通过第二部分定义完粒子属性之后，就可以定义粒子之间相互作用的方式了。所谓相互作用其实就是粒子之间作用力的计算公式，计算公式是通过势能来表述的，因为势能在空间上的梯度就是力，即 F=-divU。任何对象的组成粒子之间相互作用都分为非键结和键结。非键结就是不通过化学键的相互作用，如范德华作用和静电作用。键结就是通过化学键的相互作用，如键作用、键角作用、二面角作用、离平面作用。在LAMMPS中，非键结作用通过pair_style和pair_coeff指令进行设置，键结相互作用通过bond_style和bond_coeff指令进行设置。

[0043] 第四部分温度初始化的设置包含一条指令，velocity。第一条指令velocity，用于设置粒子的初始速度。编写规则是：velocity<group-ID><style><args><keyword><value>。

[0044] 第五部分系统弛豫的设置包含九条指令，thermo，thermo_style，pair_style，pair_coeff，fix，dump，run，undump，unfix。由于随机生成的模型无法避免粒子交叠，因此需利用LAMMPS软件中的Soft势对体系进行能量最小化，将交叠的粒子缓慢推开。这一过程我们称之为系统弛豫。在系统弛豫部分，我们首先要定义基本输出日志信息，用来监控模拟是否正确。一般输出的都是系统量，如步数、温度、动能、势能、总能量等。

[0045] S103，确定用于描述所述初始模型中粒子间相互作用的势能函数。

[0046] 针对上述步骤S103，在具体实施时，确定用于描述初始模型中粒子间相互作用的势能函数。根据本申请提供的实施例，粒子间相互作用势能包含三部分，Lennard-Jones势(ULJ)用于正式模拟过程，Soft势(USOFT)用于系统弛豫过程，Finitely ExtensibleNonlinear Elastic 势(UFENE)用于高分子链中的粒子间键结作用。

[0047] 具体的，在本申请中使用的soft势函数如下所示：

[0048] 其中，A为能量系数，rc为截断半径。本模拟中体系设置为正则系综(恒定粒子数、恒定体积、恒定温度NVT)，利用Langevin热浴控制体系温度，Soft势进行时长为105的步长来对结构进行调整，保证粒子间没有交叠，且各组分较为均匀地分散在体系中。

[0049] 在本申请中涉及到的作用势为Lennard-Jone势(ULJ)和Finitely ExtensibleNonlinear Elastic势(UFENE)。Lennard-Jones势能计算公式如下：

[0050] 式中，rij是粒子i和j之间的距离，和σ分别是粒子和之间的能量和长度参数，rc是截断半径。各组分之间的势函数参数通过Lorentz-Berthelot混合法则计算得到。

[0051] Lorentz-Berthelot混合法则表示为：

[0052] 上述公式中，下标i和j分别代表不同类型的粒子。

[0053] Finitely Extensible Nonlinear Elastic势能计算公式如下：

[0054] FENE势用来描述高分子链效应，其中K是作用强度参数，R0是截断距离。

[0055] S104，根据所述初始模型和所述势能函数确定所述锂离子电池的系统弛豫。

[0056] 针对上述步骤S104，在具体实施时，根据初始模型和势能函数确定所述锂离子电池的系统弛豫。

[0057] 作为一种可选的实施例，针对上述步骤S104，所述根据所述初始模型和所述势能函数确定所述锂离子电池的系统弛豫，包括：步骤1041，将所述初始模型中的电极材料粒子系统设置为正则系综。

[0058] 步骤1042，使用所述势能函数对所述初始模型中粒子间相互作用进行建模。

[0059] 步骤1043，采用 Verlet-Velocity 算法对所述初始模型中的粒子位置和速度进行积分更新。

[0060] 步骤1044，统计所述初始模型的系统势能、粒子受力和结构分布，直至所述初始模型的体系达到平衡状，以得到所述系统弛豫。

[0061] 针对上述步骤1041-步骤1044，在具体实施时，在系统弛豫的过程中，为了使所有粒子在模拟盒子中均匀的分开，利用Soft势将粒子缓慢的推开。在整个体系弛豫过程中，将弛豫过程分为多个阶段。作为示例，体系设置为正则系综（恒定粒子数、恒定体积、恒定温度NVT），利用Langevin热浴控制体系温度，在不同阶段其温度参数分别设置为T = 0.1，0.3，0.5，0.8，1.0。Soft势中相互作用强度系数设置为A = 1.0，10.0，30.0，60.0。每个阶段的时间步长均设置为τ = 0.005，模拟时长为106时间步。模拟的同时计算系统势能及粒子受力，根据Verlet-Velocity积分算法确定下一时刻粒子位置，统计各个时刻计算结果，直至体系达到平衡状态。

[0062] S105，将所述系统弛豫作为正式模拟初始状态，以对所述锂离子电池的电极活性材料和黏合剂的混合过程进行模拟。

[0063] 作为一种可选的实施例，针对上述步骤S105，所述将所述系统弛豫作为正式模拟初始状态，以对所述锂离子电池的电极活性材料和黏合剂的混合过程进行模拟，包括：步骤1051，对所述系统弛豫进行模拟体系设定和粒子间作用势函数设定，并确定时间步长和模拟时长。

[0064] 步骤1052，基于Verlet-Velocity 算法对所述系统弛豫中的粒子位置和速度进行时间积分，输出所述系统弛豫中的粒子轨迹数据。

[0065] 针对上述步骤1052，在具体实施时，为了更好地从弛豫过程过度到正式模拟过程，将正式模拟过程分为两部分。两部分模拟除模拟时长设置不同，第一部分为1.5×106，第二部分为5×106，其余参数均相同。在整个正式模拟过程中，体系设置为正则系综（恒定粒子数、恒定体积、恒定温度NVT），利用Langevin热浴控制体系温度，温度参数设置为T = 1.0。Lennard-Jones势中相互作用强度系数设置为A = 1.0。时间步长均设置为τ= 0.005。模拟的同时计算系统势能及粒子受力，根据Verlet-Velocity积分算法确定下一时刻粒子位置，统计各个时刻计算结果，直至体系达到平衡状态。

[0066] 作为一种可选的实施例，在对所述锂离子电池的电极活性材料和黏合剂的混合过程进行模拟之后，本申请所提供的粗粒化分子动力学模拟方法还包括：利用预设数据分析程序，计算所述锂离子电池在平衡状态下正负极组分的结构因子以及各组分间的径向分布函数，并生成所述锂离子电池的电极微观结构及活性材料与黏合剂混合过程的模拟动画。

[0067] 针对上述步骤，在具体实施时，利用Fortran语言编写数据分析程序，计算统计平衡状态锂离子电池正 / 负极组分的结构因子、各组分间的径向分布函数，并利用Ovito软件呈现锂离子电池电极微观结构及活性材料与黏合剂混合过程的模拟动画。具体的，径向分布函数定义为：

[0068] 其中，r为粒子对之间距离，Δr为代表函数分辨率的参数，N为体系中粒子总数，V为体系体积。

[0069] 在一个示例性的实施例中，一种干法电极制备过程中，不同组分占比的石墨颗粒活性材料（模拟中由刚体模型表示）与给分子黏合剂（模拟中由高分子链表示）混合过程的模拟案例，具体模拟过程如下所示：（1）确定不同组分占比的石墨颗粒活性材料与高分子黏合剂共混基础模型。本实施例中，在石墨颗粒活性材料与高分子黏合剂总量不变的基础上（模型中通过总粒子数不变来实现），通过改变模型中刚体和高分子链的数量来实现石墨颗粒活性材料和高分子黏合剂占比的改变。本模型中每个刚体由64个粒子组成，每条高分子链由100个粒子组成。如图3所示，图3为本申请实施例所提供的一种不同组分占比的石墨颗粒活性材料与高分子黏合剂共混模拟结构图。如图3所示，本实施案例中，刚体的数量分别设置为2个、20个、60个。

[0070] （2）确定模拟条件：整个模拟过程中，所有量均采用LJ单位制，所有例子类型均为full。刚体分组设置为rigid，高分子链分组设置为chain。设置模拟盒子边长为Lx = 25σ，Ly = 25σ和Lz = 25σ，并在x轴，y轴和z轴方向上引入周期性边界条件。邻居列表设置为3bin，邻居列表更新频率设置为每10000个粒子更新一次。牛顿第三定律即粒子间相互作用设置为on。时间步长设置为0.005。

[0071] （3）确定用于描述各组分间作用的势能函数：在本实施例中，粒子间相互作用势能包含三部分，Lennard-Jones势(ULJ)用于正式模拟过程，Soft势(USOFT)用于系统弛豫过程，Finitely Extensible Nonlinear Elastic 势(UFENE)用于高分子链中的粒子间键结作用。

[0072] （4）系统弛豫过程：为了使所有粒子在模拟盒子中均匀的分开，我们利用Soft势将粒子缓慢的推开。在整个体系弛豫过程中，将弛豫过程分为多个阶段，体系设置为正则系综（恒定粒子数、恒定体积、恒定温度NVT），利用Langevin热浴控制体系温度，在不同阶段其温度参数分别设置为T = 0.1，0.3，0.5，0.8，1.0。Soft势中相互作用强度系数设置为A =1.0，10.0，30.0，60.0。每个阶段的时间步长均设置为τ = 0.005，模拟时长为106时间步。模拟的同时计算系统势能及粒子受力，根据Verlet-Velocity积分算法确定下一时刻粒子位置，统计各个时刻计算结果，直至体系达到平衡状态。

[0073] （5）正式模拟过程：为了更好地从弛豫过程过度到正式模拟过程，我们将正式模拟过程分为两部分。两部分模拟除模拟时长设置不同，第一部分为1.5×106，第二部分为5×106，其余参数均相同。在整个正式模拟过程中，体系设置为正则系综（恒定粒子数、恒定体积、恒定温度NVT），利用Langevin热浴控制体系温度，温度参数设置为T = 1.0。Lennard-Jones势中相互作用强度系数设置为A = 1.0。时间步长均设置为τ = 0.005。模拟的同时计算系统势能及粒子受力，根据Verlet-Velocity积分算法确定下一时刻粒子位置，统计各个时刻计算结果，直至体系达到平衡状态。

[0074] （6）数据处理：使用Fortran编写的程序，计算石墨颗粒活性材料和高分子黏合剂的结构因子。使用Fortran编写的程序，计算石墨颗粒活性材料和高分子黏合剂的径向分布函数。

[0075] （7）电池设计：根据模拟结果，确定石墨颗粒活性材料和高分子黏合剂的最佳混合比例和黏结强度，以优化电极的微观结构，提高电池的性能。设计电极的微观结构，包括调整石墨颗粒的大小和形状，以及高分子黏合剂的分布，以优化电极的孔隙率和导电性，从而提高电池的充放电性能和循环寿命。以这些设计制备出电极和电池系统，可以满足不同应用的需求。

[0076] 在另一个示例性的实施例中，提供了一种干法电极制备过程中，某一确定组分占比的石墨颗粒活性材料（模拟中由刚体模型表示）与不同黏结强度的高分子黏合剂（模拟中由高分子链表示）混合过程的模拟案例，模拟步骤如图2所示，具体模拟过程如下所示：（1）确定某一组分占比的石墨颗粒活性材料与不同黏结强度的高分子黏合剂共混基础模型。本实施例中，在石墨颗粒活性材料与高分子黏合剂总量不变的基础上（模型中通过总粒子数不变来实现），通过改变模型中刚体和高分子链之间的作用强度来实现黏合剂黏结强度的改变。本模型中每个刚体由64个粒子组成，每条高分子链由100个粒子组成。本实施案例中，刚体的数量设置为40个。

[0077] （2）确定模拟条件。整个模拟过程中，所有量均采用LJ单位制，所有粒子类型均为full。刚体分组设置为rigid，高分子链分组设置为chain。设置模拟盒子边长为Lx = 25σ，Ly = 25σ和Lz = 25σ，并在x轴，y轴和z轴方向上引入周期性边界条件。邻居列表设置为3bin，邻居列表更新频率设置为每10000个粒子更新一次。牛顿第三定律即例子间相互作用设置为on。时间步长设置为0.005。

[0078] （3）确定用于描述各组分间作用的势能函数：在本实施例中，粒子间相互作用势能包含三部分，Lennard-Jones势(ULJ)用于正式模拟过程，Soft势(USOFT)用于系统弛豫过程，Finitely Extensible Nonlinear Elastic 势(UFENE)用于高分子链中的粒子间键结作用。

[0079] （4）系统弛豫过程：为了使所有粒子在模拟盒子中均匀的分开，我们利用Soft势将粒子缓慢的推开。在整个体系弛豫过程中，将弛豫过程分为多个阶段，体系设置为正则系综（恒定粒子数、恒定体积、恒定温度NVT），利用Langevin热浴控制体系温度，在不同阶段其温度参数分别设置为T = 0.1，0.3，0.5，0.8，1.0。Soft势中相互作用强度系数设置为A =1.0，10.0，30.0，60.0。每个阶段的时间步长均设置为τ = 0.005，模拟时长为106时间步。模拟的同时计算系统势能及粒子受力，根据Verlet-Velocity积分算法确定下一时刻粒子位置，统计各个时刻计算结果，直至体系达到平衡状态。

[0080] （5）正式模拟过程：为了更好地从弛豫过程过度到正式模拟过程，我们将正式模拟过程分为两部分。两部分模拟除模拟时长设置不同，第一部分为1.5×106，第二部分为5×106，其余参数均相同。在整个正式模拟过程中，体系设置为正则系综（恒定粒子数、恒定体积、恒定温度NVT），利用Langevin热浴控制体系温度，温度参数设置为T = 1.0。Lennard-Jones势中相互作用强度系数设置为A = 1.0，2.0，3.0。时间步长均设置为τ = 0.005。模拟的同时计算系统势能及粒子受力，根据Verlet-Velocity积分算法确定下一时刻粒子位置，统计各个时刻计算结果，直至体系达到平衡状态。

[0081] （6）数据处理：使用Fortran编写的程序，计算石墨颗粒活性材料和高分子黏合剂的结构因子。使用Fortran编写的程序，计算石墨颗粒活性材料和高分子黏合剂的径向分布函数。

[0082] （7）电池设计：根据模拟结果，设计石墨颗粒活性材料和高分子黏合剂的最佳混合比例和黏结强度，以优化电极的微观结构，提高电池的性能。设计电极的微观结构，包括调整石墨颗粒的大小和形状，以及高分子黏合剂的分布，以优化电极的孔隙率和导电性，从而提高电池的充放电性能和循环寿命。以这些设计制备出电极和电池系统，可以满足不同应用的需求。

[0083] 由实施例1可以看出，本申请可以对不同组分占比的石墨颗粒活性材料和高分子黏合剂混合过程进行模拟。由实施例2可以看出，本申请可以对不同黏结强度的高分子黏合剂合石墨颗粒活性材料混合过程进行模拟。

[0084] 本申请实施例提供的锂离子电池的粗粒化分子动力学模拟方法，首先，构建锂离子电池的电极模型；其中，所述电极模型是所述锂离子电池的石墨颗粒活性材料与高分子黏合剂共混的基础模型；确定所述电极模型的模拟条件，以建立所述锂离子电池的初始模型；确定用于描述所述初始模型中粒子间相互作用的势能函数；根据所述初始模型和所述势能函数确定所述锂离子电池的系统弛豫；最后，将所述系统弛豫作为正式模拟初始状态，以对所述锂离子电池的电极活性材料和黏合剂的混合过程进行模拟。

[0085] 本申请用于模拟干法制备锂离子电池电极过程中，石墨颗粒与高分子黏合剂的混合过程，并优化其配比参数和黏结强度，以解决现有技术中实验试错法的高成本问题。从影响锂离子正极 / 负极性能的电极活性材料（石墨颗粒）、黏合剂（高分子材料）的配比分数、黏结强度等因素出发，对电极模型进行建模优化，可用于模拟电池电极的制备过程，并从微观尺度上研究电极的各组分材料间相互作用机理。本申请中建立的模型可模拟更广泛的与石墨材料、高分子材料具有相似结构特征的电极材料，利用粗粒化方法对电极的微观体系进行模拟，在粗粒化方案所能描述的空间尺度和时间尺度上，模拟体系依然保持着基本结构框架, 这使得能够在较大的空间尺度和较长的时间尺度上描述，提高模拟结果的可信度，也提高了模拟的效率与准确性。通过对电极活性材料（石墨颗粒）、黏合剂（高分子材料）的混合过程进行模拟，从而摸索出制备优异性能电极的最优配比参数，为实验提供理论指导。

[0086] 请参阅图4，图4为本申请实施例所提供的一种锂离子电池的粗粒化分子动力学模拟装置的结构示意图。如图4中所示，所述粗粒化分子动力学模拟装置400包括：电极模型构建模块401，用于构建锂离子电池的电极模型；其中，所述电极模型是所述锂离子电池的石墨颗粒活性材料与高分子黏合剂共混的基础模型；初始模型确定模块402，用于确定所述电极模型的模拟条件，以建立所述锂离子电池的初始模型；势能函数确定模块403，用于确定用于描述所述初始模型中粒子间相互作用的势能函数；系统弛豫生成模块404，用于根据所述初始模型和所述势能函数确定所述锂离子电池的系统弛豫；动力学模拟模块405，用于将所述系统弛豫作为正式模拟初始状态，以对所述锂离子电池的电极活性材料和黏合剂的混合过程进行模拟。

[0087] 进一步的，所述电极模型构建模块401在用于构建锂离子电池的电极模型时，所述电极模型构建模块401还用于：将所述锂离子电池中具有层状结构的石墨材料粗粒化为由多个粗粒化粒子组成的立方形刚体；其中，所述立方形刚体中的每一层由多个粗粒化粒子平铺构成，每层之间通过设定粒子间距参数进行堆叠；将所述锂离子电池的高分子黏合剂表示为由多个粗粒化粒子依次连接形成的柔性链结构；其中，所述柔性链结构的链长度通过粒子数量进行调控；基于所述立方形刚体和所述柔性链结构生成所述电极模型。

[0088] 进一步的，所述模拟条件包括模拟单位制、粒子类型、模拟盒子边长、邻居列表、时间步长和粒子分组。

[0089] 进一步的，所述系统弛豫生成模块404在用于根据所述初始模型和所述势能函数确定所述锂离子电池的系统弛豫时，所述系统弛豫生成模块404还用于：将所述初始模型中的电极材料粒子系统设置为正则系综；使用所述势能函数对所述初始模型中粒子间相互作用进行建模；采用 Verlet-Velocity 算法对所述初始模型中的粒子位置和速度进行积分更新；统计所述初始模型的系统势能、粒子受力和结构分布，直至所述初始模型的体系达到平衡状，以得到所述系统弛豫。

[0090] 进一步的，所述动力学模拟模块405在用于将所述系统弛豫作为正式模拟初始状态，以对所述锂离子电池的电极活性材料和黏合剂的混合过程进行模拟时，所述动力学模拟模块405还用于：对所述系统弛豫进行模拟体系设定和粒子间作用势函数设定，并确定时间步长和模拟时长；基于Verlet-Velocity 算法对所述系统弛豫中的粒子位置和速度进行时间积分，输出所述系统弛豫中的粒子轨迹数据。

[0091] 进一步的，所述粗粒化分子动力学模拟装置还包括计算模块，在对所述锂离子电池的电极活性材料和黏合剂的混合过程进行模拟之后，所述计算模块用于：利用预设数据分析程序，计算所述锂离子电池在平衡状态下正负极组分的结构因子以及各组分间的径向分布函数，并生成所述锂离子电池的电极微观结构及活性材料与黏合剂混合过程的模拟动画。

[0092] 请参阅图5，图5为本申请实施例所提供的一种电子设备的结构示意图。如图5中所示，所述电子设备500包括处理器510、存储器520和总线530。

[0093] 所述存储器520存储有所述处理器510可执行的机器可读指令，当电子设备500运行时，所述处理器510与所述存储器520之间通过总线530通信，所述机器可读指令被所述处理器510执行时，可以执行如上述图1所示方法实施例中的锂离子电池的粗粒化分子动力学模拟方法的步骤，具体实现方式可参见方法实施例，在此不再赘述。

[0094] 本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质上存储有计算机程序，该计算机程序被处理器运行时可以执行如上述图1所示方法实施例中的锂离子电池的粗粒化分子动力学模拟方法的步骤，具体实现方式可参见方法实施例，在此不再赘述。

[0095] 所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。

[0096] 在本申请所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其它的方式实现。以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，又例如，多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些通信接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。

[0097] 所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。

[0098] 另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。

[0099] 所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个处理器可执行的非易失的计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备（可以是个人计算机，服务器，或者网络设备等）执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器（Read-OnlyMemory，ROM）、随机存取存储器（Random Access Memory，RAM）、磁碟或者光盘等各种可以存储程序代码的介质。

[0100] 最后应说明的是：以上所述实施例，仅为本申请的具体实施方式，用以说明本申请的技术方案，而非对其限制，本申请的保护范围并不局限于此，尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，其依然可以对前述实施例所记载的技术方案进行修改或可轻易想到变化，或者对其中部分技术特征进行等同替换；而这些修改、变化或者替换，并不使相应技术方案的本质脱离本申请实施例技术方案的精神和范围，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。< / style>

Claims

1. A coarse-grained molecular dynamics simulation method for lithium-ion batteries, characterized in that, The coarse-grained molecular dynamics simulation method includes: Construct an electrode model for a lithium-ion battery; wherein, the electrode model is the basic model of the blend of graphite particle active material and polymer binder in the lithium-ion battery; Determine the simulation conditions for the electrode model to establish an initial model of the lithium-ion battery; Determine the potential energy function used to describe the inter-particle interactions in the initial model; The system relaxation of the lithium-ion battery is determined based on the initial model and the potential energy function. The system relaxation was used as the initial state for the formal simulation to simulate the mixing process of the electrode active material and binder of the lithium-ion battery.

2. The coarse-grained molecular dynamics simulation method according to claim 1, characterized in that, The electrode model for constructing a lithium-ion battery includes: The graphite material with a layered structure in the lithium-ion battery is coarsened into a cubic rigid body composed of multiple coarsened particles; wherein, each layer of the cubic rigid body is composed of multiple coarsened particles laid flat, and each layer is stacked between each other by setting a particle spacing parameter. The polymeric adhesive for the lithium-ion battery is represented as a flexible chain structure formed by the sequential connection of multiple coarse-grained particles; wherein the chain length of the flexible chain structure is controlled by the number of particles. The electrode model is generated based on the cubic rigid body and the flexible chain structure.

3. The coarse-grained molecular dynamics simulation method according to claim 1, characterized in that, The simulation conditions include the simulation unit system, particle type, simulation box side length, neighbor list, time step, and particle grouping.

4. The coarse-grained molecular dynamics simulation method according to claim 1, characterized in that, The process of determining the system relaxation of the lithium-ion battery based on the initial model and the potential energy function includes: The electrode material particle system in the initial model is set as a canonical ensemble; The potential energy function is used to model the interactions between particles in the initial model; The Verlet-Velocity algorithm is used to update the particle positions and velocities in the initial model through integration. The system potential energy, particle forces, and structural distribution of the initial model are statistically analyzed until the system of the initial model reaches equilibrium, so as to obtain the relaxation of the system.

5. The coarse-grained molecular dynamics simulation method according to claim 1, characterized in that, The step of using the system relaxation as the initial state for formal simulation to simulate the mixing process of the electrode active material and binder of the lithium-ion battery includes: The system relaxation is simulated by setting the system configuration and the interparticle interaction potential function, and the time step and simulation duration are determined. The Verlet-Velocity algorithm is used to integrate the particle positions and velocities during system relaxation over time, and the particle trajectory data during system relaxation is output.

6. The coarse-grained molecular dynamics simulation method according to claim 1, characterized in that, After simulating the mixing process of the electrode active material and binder in the lithium-ion battery, the coarse-grained molecular dynamics simulation method further includes: Using a preset data analysis program, the structure factors of the positive and negative electrode components of the lithium-ion battery under equilibrium conditions and the radial distribution function between each component are calculated, and a simulation animation of the electrode microstructure of the lithium-ion battery and the mixing process of active materials and binders is generated.

7. A coarse-grained molecular dynamics simulation device for lithium-ion batteries, characterized in that, The coarse-grained molecular dynamics simulation device includes: An electrode model construction module is used to construct an electrode model for a lithium-ion battery; wherein, the electrode model is the basic model of the graphite particle active material and polymer binder blend of the lithium-ion battery. An initial model determination module is used to determine the simulation conditions of the electrode model in order to establish an initial model of the lithium-ion battery. The potential energy function determination module is used to determine the potential energy function used to describe the interaction between particles in the initial model; A system relaxation generation module is used to determine the system relaxation of the lithium-ion battery based on the initial model and the potential energy function. The kinetic simulation module is used to simulate the mixing process of the electrode active materials and binders of the lithium-ion battery by using the system relaxation as the initial state for formal simulation.

8. The coarse-grained molecular dynamics simulation device according to claim 7, characterized in that, When constructing an electrode model for a lithium-ion battery, the electrode model construction module is further configured to: The graphite material with a layered structure in the lithium-ion battery is coarsened into a cubic rigid body composed of multiple coarsened particles; wherein, each layer of the cubic rigid body is composed of multiple coarsened particles laid flat, and each layer is stacked between each other by setting a particle spacing parameter. The polymeric adhesive for the lithium-ion battery is represented as a flexible chain structure formed by the sequential connection of multiple coarse-grained particles; wherein the chain length of the flexible chain structure is controlled by the number of particles. The electrode model is generated based on the cubic rigid body and the flexible chain structure.

9. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. The machine-readable instructions are executed by the processor to perform the steps of the coarse-grained molecular dynamics simulation method for lithium-ion batteries as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the coarse-grained molecular dynamics simulation method for lithium-ion batteries as described in any one of claims 1 to 6.

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