CN114566226A - Simulation construction analysis method for high-conductivity and high-voltage electrolyte - Google Patents

Simulation construction analysis method for high-conductivity and high-voltage electrolyte Download PDF

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CN114566226A
CN114566226A CN202210193147.1A CN202210193147A CN114566226A CN 114566226 A CN114566226 A CN 114566226A CN 202210193147 A CN202210193147 A CN 202210193147A CN 114566226 A CN114566226 A CN 114566226A
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陈安国
付紫微
周雄
苏纪宏
刘富亮
班宵汉
唐月娇
刁思强
胡锦飞
石斌
陈晓涛
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Abstract

The invention belongs to the technical field of electrolyte simulation preparation, and particularly relates to a high-conductivity and high-voltage electrolyte simulation construction analysis method, which comprises the steps of molecular force field creation, full-atomic molecular dynamics simulation and quantum mechanics calculation.

Description

Simulation construction analysis method for high-conductivity and high-voltage electrolyte
Technical Field
The invention belongs to the technical field of electrolyte simulation preparation, and particularly relates to a high-conductivity and high-voltage electrolyte simulation construction analysis method.
Background
The organic electrolyte is a bridge connecting the positive electrode and the negative electrode, plays a role in transmitting ions in the lithium ion capacitor, and mainly comprises lithium salt, an organic solvent and an additive. Among lithium salts commonly used in lithium ion capacitors at present, LiPF6Is the most excellent lithium salt in comprehensive performance and the most main lithium salt in commercial electrolyte, but LiPF6The thermal stability is poor, the hydrolysis is easy, the conductivity is poor, and the method is not suitable for the lithium ion capacitor with high-rate discharge. The ionic liquid has the advantages of high thermal stability, low flash point, low volatility, excellent electronic conductivity, wide electrochemical window and the like, and has wide application prospect in the electrolyte of the lithium ion capacitor. The ionic liquid is suitable for a high-voltage pseudocapacitance lithium ion capacitor due to high electrochemical stability, and decomposition of electrolyte of the lithium ion capacitor during high-rate discharge can be reduced due to high-temperature stability of the ionic liquid. In addition, the excellent electronic conductivity of the ionic liquid can greatly improve the electronic transmission rate and the power characteristics of the lithium ion capacitor.
At present, manual experience and direct experiments are mostly adopted to explore the optimal formula of the electrolyte, which directly results in overlarge investment of manpower and material resources and higher time cost, and the selection of the formula highly depends on the experience of workers.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a simulation construction analysis method for high-conductivity and high-voltage electrolyte.
The method is realized by the following technical scheme:
a simulation construction and analysis method for high-conductivity and high-voltage electrolyte comprises the following steps:
first step molecular force field creation
The GAFF molecular force field of the organic solvent and lithium salt is determined by the following parameterization process, specifically as follows:
1) using Gaussian 09 program to generate initial conformation of organic solvent, lithium salt, then using 6-31G to optimize initial conformation of organic molecule at Hartree-Fock level;
2) for each molecule, a single point calculation was performed using B3LYP/6-31G at the Density Functional Theory (DFT) level and the initial charge per atom in the molecule was calculated using the limited electrostatic potential (RESP) method;
3) directly acquiring Van der Waals parameters and bonding parameters of each atom type from an AMBER molecular force field; the bonding parameters are bond stretching potential energy, angle bending potential energy and dihedral angle potential energy; wherein the van der Waals interaction is calculated using the conventional Lennard-Jones potential; the key stretching and angle bending potential energy items adopt a simple harmonic function form, and the dihedral angle potential energy items adopt a cosine function form;
4) for each type of organic molecule, 500 molecules were randomly mixed in a cubic box using the PACKMOL program, and then a molecular dynamics simulation of at least 100ns was performed for each organic solvent, and 100 organic molecules of different configurations were randomly selected from the molecular dynamics simulation trajectories; optimizing each configuration at HF/3-21G levels, and determining charge at B3LYP/6-31G levels; averaging the charges of the atoms in 100 different conformations, and finally determining the RESP charge of each atom;
5) multiplying the RESP charge of each atom by a coefficient of 0.85 to obtain a charge q;
second step full atomic molecular dynamics simulation
1) Respectively dissolving lithium salt into a single organic solvent to prepare an organic electrolyte with the lithium salt concentration of 1.0 mol/L;
2) respectively adopting molecular dynamics simulation software Gromacs-4.6.7 to carry out molecular dynamics simulation on all organic electrolyte systems to carry out 10000 steps of energy minimization on all organic electrolyte systems by adopting a steepest descent method and a conjugate gradient method, then gradually heating the system temperature from 0K to about 300K, and carrying out 200ps of balance simulation under NPT ensemble, isothermal and isobaric conditions;
respectively carrying out 300ns molecular dynamics simulation on all organic electrolyte systems, and sequentially calculating the mean square displacement, the diffusion coefficient, the diffusion energy barrier, the diffusion pre-exponential factor and the conductivity of the lithium ions according to the molecular dynamics simulation track and formulas I, II, III and IV;
formula I (mean square displacement MSD):
Figure BDA0003525070510000031
where r is the particle displacement, N is the number of particles, t is the time, t is0Is the initial time;
formula II (diffusion coefficient D):
Figure BDA0003525070510000032
formula III (diffusion coefficient diffusion energy barrier E)aDiffusion pre-exponential factor D0)：
Figure BDA0003525070510000033
Wherein k isbIs the chemical equilibrium constant, T is the temperature;
formula IV (conductivity σ): sigma ═ nLiDq2Per kT, where nLi represents Li+D is diffusion coefficient, q is Li+K is a boltzmann constant, and T is a system temperature;
third step of quantum mechanical computation
1) Calculating the energy of the highest occupied orbital HOMO and the lowest unoccupied orbital LUMO of the organic solvent by using Gaussian 09, and calculating the energy difference between the HOMO and the LUMO;
2) the theoretical electrochemical stability window voltage was determined using Gaussian-09 software to perform quantum chemical calculations on the organic solvent at M05-2X/6-31+ G levels, and using LC- ω PBE/6-31+ G levels to estimate the dependence of the results on density functional theoretical DFT selection.
The charge q is obtained by quantum mechanics calculation and electrostatic potential energy fitting, the AMBER molecular force field uses RESP charges as the RESP charges, and researches find that the RESP charges used by AMBER are too high to estimate the actual charges of atoms due to intermolecular polarization, so that the charges need to be multiplied by a coefficient of 0.85, wherein the coefficient of 0.85 is an empirical value.
According to the invention, through computer simulation, the movement characteristics of molecules are understood from the angle of microstructure interaction, and the physical essence of experimental observation phenomena is effectively and reasonably explained; the computational simulation technology comprises Molecular Dynamics (MD) simulation, Monte Carlo (MC) simulation and the like; the obvious advantage of molecular dynamics simulation (MD) over monte carlo simulation (MC) is that it gives a path for conformational evolution of molecules of the system or a transmission path of molecules in bulk phase, etc.; reasonable explanation or prediction of physical properties of a research system is obtained through intermolecular interaction; meanwhile, the influence mechanism of the environment on the energy and conformation change of the system can be revealed from a molecular level through molecular dynamics simulation; one important example is the effect of temperature on the diffusion coefficient of molecules; in addition, under extreme temperature or extreme pressure conditions, various systems are difficult to research by using an experimental method, and the systems under the extreme conditions can be easily simulated by a molecular dynamics simulation method to research the state change of the systems and the dynamics characteristics of molecules under the extreme conditions;
the molecular dynamics simulation is based on the following newtonian classical equation of motion:
Figure BDA0003525070510000041
wherein m isiRepresents the mass of an atom and represents the mass of the atom,
Figure BDA0003525070510000042
represents the acceleration of the atom, fiRepresenting the force acting on each atom. In molecular dynamics simulation, we need to calculate the force f acting on each atomiAnd the interaction force f between atomsiCan be obtained from the potential energy U of the system:
Figure BDA0003525070510000051
while the potential energy U of the system comprises two parts: non-bond interaction UnbAnd bond interaction Ub
U＝Vnb+Vb (3)
In classical molecular dynamics, non-bond interactions VnbComprises two parts: electrostatic interaction Vnb-EleAnd Van der Waals interaction Vnb-vdw
Vnb＝Vnb-Ele+Vnb-vdw (4)
If we know the electrostatic charge per atom QiElectrostatic interaction Unb-EleCan be calculated by coulomb potential
Figure BDA0003525070510000052
Wherein epsilon0Represents the vacuum dielectric constant and d represents the real-time distance between two atoms. The remote processing of electrostatic interactions is also critical in the calculation of electrostatic interactions. And Van der Waals interaction Unb-vdwDifferent potential functions may be used for the calculation. Among these, the most commonly used potential function is the Lennard-Jones function, as follows:
Figure BDA0003525070510000053
in the Lennard-Jones potential function, we need two parameters σ (van der waals interaction diameter) and ε (potential well depth).
Bonding interactions U in classical molecular dynamicsbComprises three parts: key expansion interaction Vb-stretchBond angle interaction Vb-angleInteraction with dihedral angle Vb-dihed：
Vb＝Vb-stretch+Vb-angle+Vb-dihed (7)
Key expansion interaction Vb-stretchCan be calculated by the following formula:
Figure BDA0003525070510000061
wherein k isbRepresenting the elastic coefficient connecting two atoms, d representing the real-time distance between two atoms, b0Representing the equilibrium distance of two atoms.
Bond angle interaction Vb-angleCan be calculated by the following formula:
Figure BDA0003525070510000062
wherein k isaRepresenting the elastic coefficient of the key angle bending, theta representing the real-time key angle value, theta0Representing the equilibrium value of the key angle.
Dihedral angle interaction Vb-dihedCan be calculated by the following formula:
Vb-dihed＝kφ(1+cos(nφ-φs)) (10)
wherein k isφRepresents the dihedral angle interaction constant, phi represents the real-time dihedral angle value, phisRepresenting the equilibrium value of the dihedral angles and n representing the multiplicity.
Has the beneficial effects that:
the method combines molecular dynamics simulation and quantum mechanics calculation, can provide an accurate evaluation method for preparing an electrolyte system with better matching with electrode materials, reduces the cost of research on economy, manpower and material resources, and improves the prediction precision of the electrochemical window voltage and the conductivity of the electrolytic liquid.
The method utilizes molecular dynamics simulation to calculate the mean square displacement, diffusion coefficient, diffusion energy barrier and diffusion pre-exponential factor of the lithium ions, can improve the evaluation on the thermal stability of the electrolyte, and further ensures the high-temperature safety of the battery.
According to the method, the influence of the molecular structure on ion diffusion can be better understood through quantum mechanical calculation, and the accuracy of theoretical calculation is effectively improved through method optimization, so that the reliability of a prediction result is improved.
Drawings
FIG. 1 shows DMC, EC, PC, LiPF6The RESP charge of each atom;
FIG. 2 shows LiPF6A graph of Li ion diffusion coefficients at different temperatures dissolved in PC, EC and DMC, respectively;
FIG. 3 shows LiPF6Conductivity maps at different temperatures dissolved in PC, EC and DMC, respectively;
FIG. 4 is a graph of free volume of PC, EC, DMC at different temperatures;
FIG. 5 shows LiPF6Electrochemical stability profile dissolved in DMC/EC mixtures;
FIG. 6 shows LiPF6Linear voltammograms dissolved in DMC/EC mixtures;
FIG. 7 is DMC/LiPF6Ionic conductivity plots of the electrolyte at different electric field strengths.
Detailed Description
The following is a detailed description of the embodiments of the present invention, but the present invention is not limited to these embodiments, and any modifications or substitutions in the basic spirit of the embodiments are included in the scope of the present invention as claimed in the claims.
Example 1
A simulation construction analysis method for high-conductivity and high-voltage electrolyte is disclosed, which takes LiPF6 as lithium salt, researches and explores an electrolyte model of the lithium salt in Propylene Carbonate (PC), Ethylene Carbonate (EC) and dimethyl carbonate (DMC), and comprises the following steps:
first step molecular force field creation
1) Initial conformations of PC, EC and DMC were generated using Gaussian 09 program, followed by optimization of the initial conformation of the organic molecule using 6-31G at Hartree-Fock level;
2) performing a single point calculation at the Density Functional Theory (DFT) level (B3 LYP/6-31G) for each molecule, and calculating the initial charge of each atom in the molecule using a constrained electrostatic potential method;
3) directly acquiring Van der Waals parameters and bonding parameters of each atom type from an AMBER molecular force field; the bonding parameters are bond stretching potential energy, angle bending potential energy and dihedral angle potential energy; wherein the van der Waals interaction is calculated using the conventional Lennard-Jones potential; the key stretching and angle bending potential energy items adopt a simple harmonic function form, and the dihedral angle potential energy items adopt a cosine function form;
the molecular dynamics simulation is based on the following newtonian classical equation of motion:
Figure BDA0003525070510000081
wherein m isiRepresents the mass of an atom and represents the mass of the atom,
Figure BDA0003525070510000091
represents the acceleration of the atom, fiRepresenting the force acting on each atom. In molecular dynamics simulation, we need to calculate the force f acting on each atomiAnd the interaction force f between atomsiCan be obtained from the potential energy U of the system:
Figure BDA0003525070510000092
while the potential energy U of the system comprises two parts: non-bond interaction UnbAnd bond interaction Ub；
U＝Vnb+Vb (3)
In classical molecular dynamics, non-bond interactions VnbComprises two parts: electrostatic interaction Vnb-EleAnd Van der Waals interaction Vnb-vdw；
Vnb＝Vnb-Ele+Vnb-vdw (4)
If we know the electrostatic charge per atom QiElectrostatic interaction Unb-EleThe coulomb potential can be used to calculate:
Figure BDA0003525070510000093
wherein epsilon0Represents the vacuum dielectric constant and d represents the real-time distance between two atoms. The remote processing of electrostatic interactions is also critical in the calculation of electrostatic interactions. And Van der Waals interaction Unb-vdwDifferent potential functions may be used for the calculation. Among these, the most commonly used potential function is the Lennard-Jones function, as follows:
Figure BDA0003525070510000101
in the Lennard-Jones potential function, we need two parameters σ (van der waals interaction diameter) and ε (potential well depth);
bonding interactions U in classical molecular dynamicsbComprises three parts: key expansion interaction Vb-stretchBond angle interaction Vb-angleInteraction with dihedral angle Vb-dihed：
Vb＝Vb-stretch+Vb-angle+Vb-dihed (7)
Key flex interaction Vb-stretchCan be calculated by the following formula:
Figure BDA0003525070510000102
wherein k isbRepresenting the elastic coefficient connecting two atoms, d representing the real-time distance between two atoms, b0Represents the equilibrium distance of two atoms;
key angle phaseInteraction Vb-angleCan be calculated by the following formula:
Figure BDA0003525070510000103
wherein k isaRepresenting the elastic coefficient of the key angle bending, theta representing the real-time key angle value, theta0A balance number representing a key angle;
dihedral angle interaction Vb-dihedCan be calculated by the following formula:
Vb-dihed＝kφ(1+cos(nφ-φs)) (10)
wherein k isφRepresents the dihedral angle interaction constant, phi represents the real-time dihedral angle value, phisRepresents the equilibrium value of dihedral angles, n represents the multiplicity;
4) for each type of organic molecule, 500 molecules were randomly mixed in a cubic box using the PACKMOL program, and then molecular dynamics simulation was performed for at least 100 nanoseconds (ns) for each organic solvent, and 100 organic molecules of different configurations were randomly selected from molecular dynamics simulation trajectories; optimizing each configuration at HF/3-21G levels, and determining charge at B3LYP/6-31G levels; averaging the charges of the atoms in 100 different conformations, and finally determining the RESP charge of each atom;
5) multiplying the RESP charge of each atom by a coefficient of 0.85 to obtain a charge q; the RESP charge of each atom of PC, EC, DMC, LiPF6 is shown in FIG. 1;
second step full atomic molecular dynamics simulation
1) Respectively dissolving LiPF6 into PC, EC and DMC to make the concentration of LiPF6 in the organic electrolyte be 1.0 mol/L;
2) molecular dynamics simulation is carried out on each organic electrolyte by adopting molecular dynamics simulation software Gromacs-4.6.7, which specifically comprises the following steps: firstly decomposing each organic electrolyte by adopting a steepest descent method and a conjugate gradient method to perform 10000 steps of energy minimization, then gradually heating the temperature from 0K to about 300K, and performing 200ps of balance simulation under the conditions of NPT ensemble, isothermal and isobaric pressure;
3) then, molecular dynamics simulation of 300ns is respectively carried out on each organic electrolyte, and all bonds related to hydrogen atoms are constrained by using an LINC algorithm in the molecular dynamics simulation process, so that the integration time step length can be increased to 2 fs; the calculated cutoff value for electrostatic interaction was calculated using the PME method for long range electrostatic force
Figure BDA0003525070510000124
The cutoff distance for van der Waals interactions is
Figure BDA0003525070510000125
The Parriello-Rahman algorithm is used to maintain the system at a pressure of 1 atmosphere. For each mixture system, 11 different simulated temperatures were used, including 253K, 263K, 273K, 283K, 293K, 300K, 313K, 323K, 333K, 343K, 353K; the velocity rescaling method is used for controlling the temperature;
4) sequentially calculating the mean square displacement, the diffusion coefficient, the diffusion energy barrier, the diffusion pre-exponential factor and the conductivity of the lithium ions according to the molecular dynamics simulation track and formulas I, II, III and IV;
formula I (mean square displacement MSD):
Figure BDA0003525070510000121
where r is the particle displacement, N is the number of particles, t is the time, t is0Is the initial time;
formula II (diffusion coefficient D):
Figure BDA0003525070510000122
formula III (diffusion coefficient diffusion energy barrier E)aDiffusion pre-exponential factor D0)：
Figure BDA0003525070510000123
Wherein kb is the chemical equilibrium constant and T is the temperature;
formula IV (conductivity σ): sigma ═ nLiDq2Per kT, where nLi represents Li+D is the diffusion coefficient, q is Li+Of (2)K is Boltzmann constant, and T is system temperature;
fig. 2 is a graph of Li ion diffusion coefficients of LiPF6 dissolved in PC, EC and DMC, respectively, at different temperatures;
as can be seen in fig. 4: diffusion of Li ions in DMC is fastest in three systems; compared with EC, PC can effectively promote Li + diffusion at low temperature, and Li + diffusion coefficient in EC and PC is equivalent at high temperature. Based on the diffusion coefficient D in fig. 4, we can use the arrhenius formula (i.e., formula III) to calculate the diffusion energy barrier (Ea) and diffusion index factor (D0) of Li ions in organic solution as shown in table 1;
TABLE 1
Figure BDA0003525070510000131
From table 1, it can be seen that: li+There is a minimum diffusion energy barrier in PC and a maximum diffusion energy barrier in EC, indicating that the temperature dependence of PC is minimum, DMC is centered, and the temperature dependence of EC is maximum. Although DMC is greater than the diffusion energy barrier E of PCaLarger, but the spread of DMC means that the pre-factor D0 is about four times that of PC;
calculating the conductivity of the electrolyte by using a formula IV, wherein the conductivity results of various organic electrolytes at different temperatures are shown in figure 3; as can be seen from fig. 3: LiPF at room temperature (30 ℃ C.)6The electrolyte system prepared by dissolving lithium salt in DMC has highest conductivity, lowest conductivity when dissolved in PC, and Li dissolved in DMC electrolyte+The electrical conductivity of (a) increases rapidly with increasing temperature;
from the molecular structures of PC, EC and DMC, it is known that: the ion conductivity of the open-loop organic molecular electrolyte is higher than that of the closed-loop organic molecular electrolyte. In fact, the open-loop organic molecules have better flexibility than the closed-loop organic molecules, so that the organic electrolyte has a larger free volume, as shown in fig. 4, which is beneficial to the diffusion of Li ions. In addition, we calculated the molecular interactions in three organic electrolyte systems: electrostatic interactions and van der waals interactions. We found that electrostatic interactions contributed much more to intermolecular interactions than van der waals interactions (see table 2), suggesting that electrostatic interactions have the greatest effect on Li ion transport;
TABLE 2
Figure BDA0003525070510000141
As can be seen from Table 2: the PC molecules in the PC electrolyte system have the strongest electrostatic interaction, while the DMC molecules in the DMC electrolyte system have the weakest electrostatic interaction. Studies have shown that strong electrostatic interactions between organic molecules of the electrolyte reduce the free volume of the organic molecular electrolyte. Conversely, if the electrostatic interaction between organic molecules is reduced, the free volume of the organic electrolyte is increased, effectively promoting the migration of ions. Thus, the DMC electrolyte system has the greatest free volume because of the weakest electrostatic interactions between its molecules. Interestingly, in the three electrolyte systems, the electrostatic interaction between the DMC organic molecules and Li ions is strongest, which shows that the enhancement of the electrostatic interaction between the organic molecules and Li ions can improve the movement of Li ions in the organic electrolyte. Therefore, designing an organic electrolyte having high conductivity requires reducing electrostatic interaction between organic molecules and improving electrostatic interaction between organic molecules and Li ions;
third step of quantum mechanical computation
1) Energy of the highest occupied orbital (HOMO) and the lowest unoccupied orbital (LUMO) of the organic solvent was calculated using Gaussian 09, and the energy difference between HOMO and LUMO was calculated as shown in table 3;
Figure BDA0003525070510000142
as can be seen from Table 3: the energies of HOMO and LUMO of EC are the lowest and the energies of HOMO and LUMO of DMC are the highest in the three organic electrolytes. This indicates that the EC electrolyte has the highest stability and the DMC stability is the lowest. And the energy difference between the HOMO and LUMO of EC is largest. However, the chemical reactions for transferring one electron from the three organic electrolytes all require a voltage of 8.8V or more, which indicates that the three organic electrolytes are relatively stable even at a high voltage (5V).
2) Quantum chemical calculations were performed on the organic solvent using Gaussian-09 software at M05-2X/6-31+ G levels, and using LC- ω PBE/6-31+ G levels, the dependence of the results on the selection of Density Functional Theory (DFT) was estimated, determining the theoretical electrochemical stability window voltage;
the oxidation stability of DMC pure solvent is 6.7eV, calculated using the PCM implicit solvation model, with a dielectric constant of 4, and its theoretical electrochemical stability window is around 5.3V. However, when DMC and PF6-When the complex is formed, the oxidation stability is only 6.2-6.5eV, and the theoretical electrochemical stability window is reduced to 4.8-5.1V. When EC and PF6-When the complex is formed, the oxidation stability can be improved to 6.8eV, and the theoretical electrochemical stability window can be improved to 5.4V. Thus, the LiPF of the present application6The voltage window dissolved in the DMC/EC mixture varied and the calculations are shown in FIG. 5; in DMC/EC mixtures, different molar ratios (e.g., 1:2, 2:1) were used in this example, and it can be seen from FIG. 5 that the theoretical electrochemical stability window can exceed 5V as the EC ratio increases.
Finally, the inventors have discovered that to validate the simulation calculation results, the DMC: four electrolytes, LiPF, were prepared separately in EC ratios6: DMC: the molar ratio of EC is 1:1: 0; 1:1: 1; 1:2: 1; 1:0:1, numbering the electrolytes as No. 1, No. 2, No. 3 and No. 4 in sequence, and then carrying out linear volt-ampere test on the prepared four electrolytes, wherein the test potential is 2.20-6.00V (reference constant current instrument), and the scanning rate is 50 mV/s; the results of the experiment are shown in FIG. 6, and LiPF can be seen from FIG. 66: DMC: when the molar ratio of EC is 1:0:1, the voltage window of the prepared electrolyte reaches 5.229V, which is close to the theoretical result obtained by simulation calculation. It should be noted that, in the actual determination of the electrochemical stability window, the complex environment of the electrolytic solution (and the electrode effect) is different from the ideal environment used in the theoretical calculation, so that the electrochemical stability window calculated in the theoretical calculation is different from the electrochemical stability window tested in the experiment.
Meanwhile, the method simulates different electric field strengths, DMC/LiPF in an environment with the simulated temperature of 50 DEG C6Li ion conductivity of the mixture system, as shown in fig. 7; as can be seen from fig. 7: li ion conductivity increases with increasing electric field strength; DMC/LiPF under the condition of electric field intensity of 3V/nm6The Li ion conductivity of the electrolyte system can reach more than 5S/m.
Three electrolytes, namely LiPF6+ EC, LiPF6+ PC and LiPF6+ DMC are given out in the application, so that the simulation construction analysis method is an effective electrolyte construction method, the conclusion obtained through a large number of chemical experiments is avoided, and the research steps and the test cost are simplified.

Claims (9)

1. A simulation construction analysis method for high-conductivity and high-voltage electrolyte is characterized by comprising the following steps:
first step molecular force field creation
The GAFF molecular force field of the organic solvent and lithium salt is determined by the following parameterization process, specifically as follows:
1) the initial conformation of the organic solvent, lithium salt was generated using Gaussian 09 program and then optimized at Hartree-Fock level using 6-31G @;
2) for each molecule, single point calculations were performed at the DFT level (B3 LYP/6-31G) and the initial charge per atom within the molecule was calculated using the RESP method;
3) directly acquiring Van der Waals parameters and bonding parameters of each atom type from the AMBER molecular force field;
4) for each type of organic molecule, 500 molecules were randomly mixed in a cubic box using the PACKMOL program, and then a molecular dynamics simulation of at least 100ns was performed for each organic solvent, and 100 organic molecules of different configurations were randomly selected from the molecular dynamics simulation trajectories; optimizing each configuration at HF/3-21G levels, and determining charge at B3LYP/6-31G levels; averaging the charges of the atoms in 100 different conformations, and finally determining the RESP charge of each atom;
5) multiplying the RESP charge of each atom by a coefficient of 0.85 to obtain a charge q;
second step full atomic molecular dynamics simulation
1) Respectively dissolving lithium salt into a single organic solvent to prepare an organic electrolyte with the lithium salt concentration of 1.0 mol/L;
2) respectively adopting molecular dynamics simulation software Gromacs-4.6.7 to carry out molecular dynamics simulation on all organic electrolyte systems, specifically adopting a steepest descent method and a conjugate gradient method to carry out 10000 steps of energy minimization, then gradually heating the system temperature from 0K to about 300K, and carrying out 200ps of balance simulation under the conditions of NPT ensemble, isothermal and isobaric pressure;
3) respectively carrying out 300ns molecular dynamics simulation on all organic electrolyte systems, and sequentially calculating the mean square displacement, the diffusion coefficient, the diffusion energy barrier, the diffusion pre-exponential factor and the conductivity of the lithium ions according to the molecular dynamics simulation track;
the third step of quantum mechanical computation
Calculating the energy of the highest occupied orbital HOMO and the lowest unoccupied orbital LUMO of the organic solvent by using Gaussian 09, and calculating the energy difference between the HOMO and the LUMO;
the theoretical electrochemical stability window voltage was determined using Gaussian-09 software to perform quantum chemical calculations on the organic solvent at M05-2X/6-31+ G levels, and using LC- ω PBE/6-31+ G levels to estimate the dependence of the results on DFT selection.
2. The method for modeling, constructing and analyzing a high conductivity, high voltage electrolyte of claim 1 wherein said bonding parameters are bond tensile potential, angle bending potential, dihedral angle potential.
3. The method for modeling construction and analysis of a high conductivity, high voltage electrolyte according to claim 1 wherein said van der waals interactions are calculated using Lennard-Jones potential.
4. The method for modeling construction and analysis of a high conductivity, high voltage electrolyte of claim 1 wherein said bond stretching and angular bending potential energy terms are calculated using simple harmonic functions.
5. The method for modeling, constructing and analyzing a high conductivity, high voltage electrolyte of claim 1 wherein said dihedral angle potential energy term is calculated using a cosine function.
6. The method for modeling, constructing and analyzing a high conductivity, high voltage electrolyte of claim 1 wherein the Mean Square Displacement (MSD) is calculated by the equation:
Figure FDA0003525070500000031
where r is the particle displacement, N is the number of particles, t is the time, t is0Is the initial time.
7. The method for modeling, constructing and analyzing a high conductivity, high voltage electrolyte of claim 1 wherein said diffusion coefficient D is calculated by the formula:
Figure FDA0003525070500000032
8. the method of claim 1, wherein the diffusion coefficient diffusion energy barrier E is selected from the group consisting ofaDiffusion pre-exponential factor D0The calculation formula of (2):
Figure FDA0003525070500000033
wherein k isbIs the chemical equilibrium constant, T is the temperature.
9. The method for modeling, constructing and analyzing a high conductivity, high voltage electrolyte of claim 1 wherein the conductivity σ is calculated by the formula: sigma ═ nLiDq2Per kT, where nLi represents Li+D is diffusion coefficient, q is Li+K is the boltzmann constant,t is the system temperature.
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EP4322043A1 (en) * 2022-06-28 2024-02-14 Tata Consultancy Services Limited Method and system for identifying electrolyte composition for optimal battery performance
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