A method for analyzing a decomposition process of a magnesium ion battery electrolyte based on reactive molecular dynamics simulation

Abstract

The application relates to a method for analyzing the decomposition process of a Mg-ion battery electrolyte based on reactive molecular dynamics simulation, which comprises the following steps: constructing a Mg-ion battery model, adopting reactive force field molecular dynamics simulation, simulating the external voltage condition of the battery model by using an electrochemical kinetics method, simulating the inter-ion charge transfer by using a charge balance method, combining the three methods to simulate the discharge process of the Mg-ion battery, and tracking the species to which each snapshot of all atoms in the electrolyte of the Mg-ion battery belongs by using a reaction network integrator, so as to realize the decomposition process of the simulated electrolyte. Compared with the prior art, the method can more accurately analyze the electrolyte decomposition path and identify organic, inorganic and gaseous products by using the ReacNetGenerator method based on graph theory. The proposed multi-element hybrid analysis simulation method can more realistically simulate the reaction process, and can analyze the electrolyte decomposition process from the microscopic mechanism, thereby providing a basis for the further design of Mg battery electrolyte.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electrochemical simulation, and particularly relates to a method for simulating and analyzing Mg-ion battery electrolyte decomposition based on reactive molecular dynamics. BACKGROUND

[0002] Mg-ion batteries have higher theoretical capacity and better safety, and are energy storage devices with excellent development potential, but the poor stability of the battery electrolyte hinders the further research of Mg-ion batteries. In order to improve the performance of the battery, the decomposition of the Mg-ion battery electrolyte has been studied by means of SEM, cryo-EM, XPS, gas analysis and other means, but these experimental analysis methods cannot study the micro-process of the decomposition of the electrolyte.

[0003] In order to make up for the deficiency of experimental methods, various theoretical calculation methods, such as first-principle (DFT) and ab initio molecular dynamics (AIMD) small-scale calculations or classical dynamics (MD) and reactive force field molecular dynamics (Reax-ff MD) large-scale calculations, are used to study the micro-mechanism in the reaction process. But DFT and AIMD calculation cost is high, and is limited to small scale (hundreds of atoms) and short time (fs level) simulation. Classical MD cannot be used to simulate the process of bond breaking and bond forming. Single ReaxFF-MD is slightly insufficient when predicting and analyzing various products in the electrolyte reaction process as comprehensively as possible.

[0004] Therefore, it is urgent to study a method which can effectively simulate the micro-process inside the Mg-ion battery electrolyte. SUMMARY

[0005] The present application relates to the technical field of electrochemical simulation, and particularly relates to a method for simulating and analyzing Mg-ion battery electrolyte decomposition based on reactive molecular dynamics.

[0006] The purpose of the present application can be achieved by the following technical solutions:

[0007] The application provides a method for analyzing a Mg-ion battery electrolyte decomposition process based on reactive molecular dynamics simulation, which comprises the following steps: constructing a Mg-ion battery model, simulating the bonding and breaking of molecules by using a reactive force field molecular dynamics, simulating an external voltage by using an implicit degree of freedom electrochemical kinetics method, and simultaneously simulating the charge transfer between ions by using a charge balance method, combining the three simulation methods to simulate the discharge process of the Mg-ion battery, and then tracking the species to which each snapshot of all atoms in the electrolyte of the Mg-ion battery belongs by using a reaction network integrator, obtaining material conversion information, and realizing the simulation of the decomposition process of the electrolyte.

[0008] Further, the Mg-ion battery model comprises a cathode, an anode and an electrolyte, the cathode and the anode are both periodic and repeated magnesium metal units, and the electrolyte comprises a magnesium salt and an organic solvent.

[0009] Further, the organic solvent is one or more of DME, DGM and THF, and the magnesium salt is Mg(TFSI)2.

[0010] Further, the electrolyte composition constructed in the Mg-ion battery model comprises 0.5M Mg(TFSI)2 dissolved in DME, 0.5M Mg(TFSI)2 dissolved in DGM, and 0.5M Mg(TFSI)2 and 2M DMA dissolved in THF.

[0011] Further, the reactive force field molecular dynamics is a reactive force field potential function molecular dynamics, which describes the bonding relationship between atoms by parameters such as atomic distance and atomic charge, and then simulates the bonding and breaking of molecules.

[0012] Further, the electrochemical kinetics is an implicit degree of freedom electrochemical kinetics, which allocates an additional variable to each atom in the model for representing a nearby local point, so as to apply an external voltage to the Mg-ion battery model.

[0013] Further, the charge balance is used to calculate the change of atomic charge during the simulation process.

[0014] Further, the specific acquisition process of each snapshot of all atoms in the electrolyte of the Mg-ion battery is that the atomic trajectory snapshot is recorded once every 0.2 ps by using the Lammps software.

[0015] Further, the reaction network integrator uses a graph theory-based reaction network integrator.

[0016] Further, the graph theory-based reaction network integrator is used to read a trajectory file containing bond sequence information in the reactive molecular dynamics simulation, and each snapshot in the trajectory file is regarded as an undirected graph, and each atom is regarded as a node.

[0017] The traversal identification of the species to which each node belongs is performed to obtain all species on the given trajectory, and a Markov model is used to filter the trajectory noise to obtain the reaction network and product information.

[0018] Compared with the prior art, the present application has the following advantages and beneficial effects:

[0019] 1. The present application more accurately analyzes the electrolyte decomposition path and more accurately identifies organic, inorganic and gaseous products by using the ReacNetGenerator method based on graph theory.

[0020] 2. The multi-element mixed analysis simulation means proposed in the present application can more realistically simulate the reaction process, and can analyze the electrolyte decomposition process from the microscopic mechanism, thereby providing a basis for the further design of Mg battery electrolytes. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 A flowchart of a method for analyzing the electrolyte decomposition process of a Mg ion battery based on reactive molecular dynamics simulation. DETAILED DESCRIPTION

[0022] The specific embodiments of the present application will be described in detail below through examples, which are implemented on the basis of the scheme described in the present application, and detailed embodiments and specific operation processes are given, but the protection scope of the present application is not limited to the following examples.

[0023] The present application will be further described below in combination with the drawings and specific examples. In the technical scheme, if the features such as part model, material name, connection structure, preparation means, material, structure or composition ratio are not explicitly stated, they are regarded as common technical features disclosed in the prior art.

[0024] Example 1

[0025] The present embodiment provides a method for analyzing the electrolyte decomposition process of a Mg ion battery based on reactive molecular dynamics simulation, as shown in Figure 1 The method comprises:

[0026] S1: Constructing a Mg ion battery model, the Mg ion battery model comprising a cathode, an anode and an electrolyte, the cathode and the anode being periodic and repeated magnesium metal units, and the electrolyte being 0.5M magnesium salt Mg(TFSI)2 dissolved in ethylene glycol dimethyl ether (DME).

[0027] S2: The reaction force field molecular dynamics (ReaxFF-MD) is used to simulate the bond formation and breaking of the molecules, the implicit degrees of freedom electrochemical dynamics (EChemDID) is used to simulate the external voltage, and the charge equilibration method (QEq) is used to simulate the charge transfer between ions. The three simulation methods are combined to simulate the discharge process of the Mg-ion battery. The reaction force field potential function molecular dynamics describes the bond formation between atoms through parameters such as atomic distance and atomic charge, and then simulates the bond formation and breaking of the molecules in the simulation process. The implicit degrees of freedom electrochemical dynamics assigns an additional variable to each atom in the model, which is used to represent the nearby local point to apply an external voltage to the Mg-ion battery model. The charge equilibration method is used to calculate the change of atomic charge during the simulation, which is a method for predicting the charge distribution in the molecule. The atomic chemical potential is constructed by using the atomic ionization potential, electronegativity, atomic radius, and shielding electrostatic interaction between all charges. By requiring equal chemical potential, the equilibrium charge depending on the geometry can be obtained.

[0028] S3: The graph theory-based reaction network integrator is used to track the species to which each snapshot of all atoms in the electrolyte of the Mg-ion battery belongs, obtain material conversion information, and realize the simulation of the decomposition process of the electrolyte. The specific process of obtaining each snapshot of all atoms in the electrolyte of the Mg-ion battery is to record the atomic trajectory snapshot once every 0.2 ps by using the Lammps software.

[0029] The graph theory-based reaction network integrator reads the trajectory file containing bond sequence information in the reactive molecular dynamics simulation, and takes each snapshot in the trajectory file as an undirected graph, and each atom as a node. The species to which each node belongs is identified, and all species on the given trajectory are obtained. Then, the Markov model is used to filter the trajectory noise to obtain the reaction network and product information.

[0030] Example 2

[0031] The difference between this example and Example 1 is that the electrolyte is 0.5M magnesium salt Mg(TFSI)2 dissolved in diglyme (DGM), and the remaining steps are the same as those of Example 1.

[0032] Example 3

[0033] The difference between this example and Example 1 is that the electrolyte is 0.5M magnesium salt Mg(TFSI)2 and 2M dimethylacetamide (DMA) dissolved in tetrahydrofuran (THF), and the remaining steps are the same as those of Example 1.

[0034] The foregoing description of the embodiments has been presented for the purpose of illustration and description. It is not intended to be exhaustive or to limit the application to the precise form disclosed. Modifications and variations are possible in light of the above teachings or can be acquired from practice of the application. As well, the description is presented in the context of the preferred embodiments as a number of alternatives. It is not intended to limit the application to the precise form described.

Claims

1. A method for analyzing Mg-ion battery electrolyte decomposition processes based on reactive molecular dynamics simulations, characterized in that, The method comprises: constructing a Mg-ion battery model, simulating the bonding and breaking of molecules by using a reactive force field molecular dynamics, simulating the external voltage by using an implicit degree of freedom electrochemical kinetics, and simultaneously simulating the charge transfer between ions by using a charge balance method, combining the three simulation methods to simulate the discharge process of the Mg-ion battery, and then using a reaction network integrator to track the species to which each snapshot of all atoms in the electrolyte of the Mg-ion battery belongs, to obtain material conversion information and realize the simulation of the decomposition process of the electrolyte. The Mg-ion battery model comprises a cathode, an anode and an electrolyte, the cathode and the anode are both periodic and repeated magnesium metal units, and the electrolyte comprises a magnesium salt and an organic solvent. The organic solvent is one or more of DME, DGM and THF, and the magnesium salt is Mg(TFSI)2. The electrolyte components constructed in the Mg-ion battery model include 0.5M Mg(TFSI)2 dissolved in DME, 0.5M Mg(TFSI)2 dissolved in DGM, and 0.5M Mg(TFSI)2 and 2M DMA dissolved in THF. The reactive force field molecular dynamics is a reactive force field potential function molecular dynamics, which describes the bonding relationship between atoms by using atomic distance and atomic charge parameters, and then simulates the bonding and breaking of molecules. The electrochemical kinetics is an implicit degree of freedom electrochemical kinetics, which assigns an additional variable to each atom in the model to represent the nearby local point, so as to apply an external voltage to the Mg-ion battery model. The charge balance method is used to calculate the change of atomic charge during simulation. The reaction network integrator uses a graph theory-based reaction network integrator. The graph theory-based reaction network integrator reads a trajectory file containing bond sequence information in the reactive molecular dynamics simulation, and regards each snapshot in the trajectory file as an undirected graph, and each atom as a node. Each node is identified by traversing the species to which it belongs, and all species on the given trajectory are obtained, and then a Markov model is used to filter the trajectory noise to obtain reaction network and product information.

2. The method for analyzing the decomposition process of Mg-ion battery electrolyte based on reactive molecular dynamics simulation according to claim 1, characterized in that, The specific acquisition process of each snapshot of all atoms in the electrolyte of the Mg-ion battery is that the Lammps software records an atomic trajectory snapshot every 0.2 ps.

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