AU2020104167A4 - A Preparation Method for Low-stress Electrode Material Sintering Based on the Mesoscale Model - Google Patents
A Preparation Method for Low-stress Electrode Material Sintering Based on the Mesoscale Model Download PDFInfo
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Abstract
of Descriptions
The invention discloses a preparation method for low-stress electrode material sintering
based on the mesoscale model, the specific steps are as follows: establish the all-atom model of
LST and GDC; establish the coarse-grained cluster model corresponding to the all-atom model;
optimize the coarse-grained model parameters; establish the LST-GDC multi-nanoparticle model;
perform simulated sintering to calculate the stress distribution state of the structure after sintering;
visualize the sintered structure and stress distribution. Using a preparation method for low-stress
electrode material sintering based on the mesoscale model of the above-mentioned structure,
through the method of coarse-grained processing, the molecular dynamics process that can
originally only simulate tens of thousands to hundreds of thousands of atoms at most is raised to
the mesoscale level, which is convenient to the study of the preparation process and the stress
distribution of precise measurement.
Description
Descriptions
A Preparation Method for Low-stress Electrode Material Sintering Based on the Mesoscale Model
Technical Field The invention specifically relates to a preparation method for low-stress sintering of electrode materials based on coarse-grained molecular dynamics, which belongs to the field of electrode materials of reversible Solid Oxide Fuel Cell (rSOFC).
Background Technology Porous electrode is one of the important components of rSOFC. Solid state sintering has a decisive effect on the effective transmission of electrode reactants/products in pores, compactness, porosity and effective electrical/ionic conductivity. However, in the development of positive/reverse dual-function electrode composite materials of rSOFC, due to the lack of knowledge of microstructure changes during the sintering process, rough sintering operation will cause problems such as local stress concentration and obvious residual stress of the final sintered materials, and eventually cause problems such as battery rupture during operation. In order to solve this problem, the patent develops a coarse-grained molecular dynamics method based on the mesoscale model. With the composite anode material LST-GDC of rSOFC as the research object, the patent studies the microstructure evolution in the preparation process, and analyzes the stress distribution, so as to provide a theoretical guidance for the low-stress preparation of rSOFC materials.
Summary of the Invention The purpose of the invention is to provide a preparation method for low-stress electrode material sintering based on the mesoscale model. With the composite anode material LST-GDC of rSOFC as the research object, the invention studies the microstructure evolution in the preparation process, and analyzes the stress distribution, so as to provide a theoretical guidance for the low-stress preparation of rSOFC materials.
In order to achieve the above purpose, the invention provides a preparation method for low-stress electrode material sintering based on the mesoscale model. The specific steps are as follows:
Step SI: Select the potential function that can reflect the interaction forces between all atoms contained in the LST-GDC system of rSOFC composite anode material;
Step S2: Import the unit cell models of LST and GDC through the observation module of the molecular modeling software, and obtain the coarse-grained unit cell by modifying its lattice constant to be the original integral multiples. The atom number, mass and charge number of the unit cell should also be changed to the original exponential multiples, so as to increase the number of atoms that can be expressed under the same amount of calculation;
Descriptions
Step S3: Establish the electrically neutral LST coarse-grained nanoclusters and GDC coarse-grained nanoclusters, respectively. The coarse-grained model potential function parameters should be fitted and optimized according to the corresponding coarse-grained multiples, and verified according to the all-atom model;
Step S4: Place two LST and GDC nanoclusters with the same ratio into a simulation box, and use the msi2lmp tool that comes with the molecular dynamics simulation software Lammps to convert them into the model data that can be identified by Lammps;
Step S5: Set and simulate related parameters: the sintering temperature of the simulation system is set to 1673K, and the integration step is selected to be Ifs; determine the initial position and velocity of the atom, predict the velocity of the atom at the next moment according to the potential energy of computing system and the atom forces, according to the Verlet integration algorithm, and use VonMises method to calculate the equivalent stress of each atom;
Step S6: Use Lammps software to perform molecular dynamics simulation calculation on the self-written program files, count the calculation results, and obtain the output files of related data of the simulation process and stress calculation results. The output files contain the change information of variable parameters and atomic coordinates, and select the Ovito software for visualization processing, which shows the whole microstructure evolution and the final stress distribution state.
Further, in Step S, the potential function is composed of Born-Mayer-Huggins, which describes the short-range interaction force, and the Coulomb potential, which describes the long-range force of charge.
Further, in Step S3, establish the electrically neutral LST coarse-grained nanoclusters and GDC coarse-grained nanoclusters, respectively through Build Nanocluster.
Therefore, the invention adopts a preparation method for low-stress electrode material sintering based on the mesoscale model of the above structure, which has the following beneficial effects:
1. Through the method of coarse-grained processing, the molecular dynamics process that can originally only simulate tens of thousands to hundreds of thousands of atoms at most is raised to the mesoscale level (micron level), which is a more effective method to study the low-stress preparation process of electrode materials of reversible Solid Oxide Fuel Cell (rSOFC);
2. The invention will analyze the sintering process and stress distribution of LST-GDC from the microscopic point of view. The existing technology only qualitatively or quantitatively analyzes the sintering stress value from the macroscale, but the stress action mechanism in the
Descriptions
sintering process is relatively complex. The invention can deeply analyze the stress distribution in the sintering process, study and determine the low-stress preparation solutions.
3. The invention can realize the effective compatibility and organic combination of the molecular dynamics software Materials Studio with powerful modeling function and the molecular dynamics software Lammps with rich potential function and powerful dynamic calculation function, so as to construct a LST-GDC sintering model and lay a technical foundation for stress distribution of precise measurement. Materials Studio is a molecular dynamics simulation software based on graphical operation interface. Although the dynamic simulation function is not as powerful as Lammps, its modeling is relatively convenient, especially in the construction of complex models, it shows obvious advantages, which lays a foundation for subsequent calculation.
Detailed Description of the Presently Preferred Embodiments A preparation method for low-stress electrode material sintering based on the mesoscale model. The specific steps are as follows:
Step SI: Select the potential function that can reflect the interaction forces between all atoms contained in the LST-GDC system of rSOFC composite anode material;
Selection of potential function: The type of potential function uses Born-Mayer-Huggins and Coulomb potential as the mixed potential function to describe LST-GDC, because it can reflect the interaction between all atoms contained in such complex metal oxides as LST-GDC.
Step S2: Import the unit cell models of LST and GDC through the observation module of the molecular modeling software, modify the lattice constant to the original 2 or 3 or...or n multiples through Lattice Parameter, that is, the coarse-grained degree is n=2, 3, ... n, and the number of atoms in the unit cell should also be changed to the original exponential multiples accordingly. Meanwhile, the mass and charge number should also be changed to the original exponential multiples, so as to increase the number of atoms that can be expressed under the same amount of calculation.
Step S3: Establish the electrically neutral LST coarse-grained nanoclusters and GDC coarse-grained nanoclusters, respectively. The coarse-grained model potential function parameters should be fitted and optimized according to the corresponding coarse-grained multiples, and verified according to the all-atom model; optimize the potential parameters of coarse-grained model: Continuously adjust and describe the potential parameters of Bom-Mayer-Huggins to describe the coarse-grained model more accurately. The main manifestation is that the potential energy value and density value calculated under its new parameters match the all-atom model to verify the potential parameters when the final coarse-grained degree is 2, 3, ....
Descriptions
Set the parameters of molecular dynamics simulation in Lammps software: The boundary conditions are periodic boundary conditions, system temperature control method (set the initial temperature to 1673K and maintain the temperature), the ensemble is NPT (Number Pressure Temperature), and the potential function is composed of Bom-Mayer-Huggins and Coulomb potential, the specific manifestations are:
Z.Ze 2 a+a.-r. CC. U fo (b,+b,)exp( ' - -_ b, + bj
Of which, Uij is the total potential energy of all atoms i and j at distance rij, Zi and Zj are effective charges, ai, aj, bi and bj are repulsive force coefficients, Ci and Cj are attractive force coefficients, f0 is the size conversion coefficient, and f0 is 4.19kJ/(mol-A).
Establish the coarse-grained clusters of LST and GDC respectively through Build Nanocluster. Taking LST as an example, adjust the mass and charge number of each atom to the original 23, 33, ... multiples. Meanwhile, establish an all-atom model that is the same as that of the coarse-grained nanoparticles, and use the msi2lmp that comes with Lammps to convert these two models into Data files required by the molecular dynamics simulation software Lammps.
Step S4: Place two LST and GDC nanoclusters with the same ratio into a simulation box, and use the msi2lmp tool that comes with the molecular dynamics simulation software Lammps to convert them into the model data that can be identified by Lammps;
Step S5: Set and simulate related parameters: the sintering temperature of the simulation system is set to 1673K, and the integration step is selected to be Ifs; determine the initial position and velocity of the atom, predict the velocity of the atom at the next moment according to the potential energy of computing system and the atom forces, according to the Verlet integration algorithm, and use VonMises method to calculate the equivalent stress of each atom;
Stress calculation method: Use the VonMises stress formula to describe the stress distribution state of the entire structure. The VonMises stress is an equivalent stress. It uses stress contours to represent the stress distribution inside the model, which can clearly describe the change of stress in the entire model, so as to determine the most dangerous area in the model.
The stress value of each coarse particle is calculated by the VonMises formula, and its specific manifestation is:
(=1 = ( -(,)2+(,- _)2+((-, _)2+6(1 +r+ +I)/vol
Of which, ax, ay, and az are the positive stresses in the three directions of xyz, and vol is the Voronoi volume of each coarse particle.
Descriptions
Settings of system relaxation and simulation conditions: Select the isothermal-isobaric ensemble (NPT) to equilibrate constraints, and use the Nose-Hoover heat bath method to adjust the system temperature. The temperature value is set at 1673K, and the pressure is set at a simulation condition of 1bar for 500ps sintering.
Step S6: Use Lammps software to perform molecular dynamics simulation calculation on the self-written program files, count the calculation results, and obtain the output files of related data of the simulation process and stress calculation results. The output files contain the change information of variable parameters and atomic coordinates, and select the Ovito software for visualization processing, which shows the whole microstructure evolution and the final stress distribution state. Calculate with Lammps and output the sintered structure type coordinate file, use Ovito software to visualize the sintering process, and use its Slice section function to study the internal microstructure changes in the sintering process, and use Color Coding to render the overall stress distribution and obtain the relevant conclusions.
Embodiment 1
Step Sl: Establish the cluster model of LST and GDC: Import the unit cell model of LST and GDC through the observation module of Material Studio software, and modify the lattice constant to the original 3 multiples through Lattice Parameter, that is, the coarse-grained degree is n=3.
Step S2: Establish the coarse-grained clusters of LST and GDC respectively with a diameter of 4nm through Build Nanocluster; change the mass and charge number to the original 3 multiples. Meanwhile, establish an all-atom model that is the same as that of the coarse-grained nanoparticles, and use the msi2lmp that comes with Lammps to convert these two models into Data files required by the molecular dynamics simulation software Lammps.
Step S3: Continuously adjust and describe the potential parameters of Born-Mayer-Huggins, calculate the potential energy and density values of single nanoparticles, and finally obtain new parameter values so that the potential energy value error between the coarse-grained model and the all-atom model is less than 0.2%, and the density error is less than 1%.
Step S4: In Material Studio, randomly place 6 coarse-grained clusters of LST and 6 coarse-grained clusters of GDC in a 200Xx200Xx200 simulation box, which includes a total of 41,946 coarse-grained coarse particles; and use the msi2lmp tool that comes with Lammps to convert them into Data files required by the molecular dynamics simulation software Lammps.
Firstly, the initial structure is set at a temperature of 300K and a pressure of 1bar under the NPT ensemble, so as to obtain a relaxed structure. Secondly, use the relaxed configuration as the initial model, perform a 500ps sintering simulation, the sintering temperature is set to 1673K, the time step is set to Ifs, and the boundary conditions are periodic boundary conditions in the three
Descriptions
directions of XYZ. Sintering conditions can be observed obviously. The initial circular cluster configurations of GDC and LST have been completely fused together after sintering, the size of the box has been reduced from the original 200x200x200k to 94.7x95.3x96.2A, and the sintering behavior of the LST-GDC composite material has been successfully characterized.
Step S5: For more internal details of the sintered structure, Ovito software can be used for visualization and section analysis of the obtained sintered structure. It is concluded that at the initial stage of the simulation, the distance between the LST and GDC nanoclusters gradually decreases. At 20ps, LST-GDC nanoclusters contact and form a sintering neck. After the sintering neck is stable, the sintering enters a slow stage. Finally, a typical sintered morphology with continuous ducts can be observed obviously from the section configuration at 500ps.
Step S6: The stress distribution of the sintered structure is rendered by using the Color Coding function in the Ovito software through the stress value of each atom. The stress distribution of the sintered structure can be intuitively observed from Figure 3, and it can be analyzed that the overall stress value is mainly provided by LST material, and the overall stress value is higher than that of GDC.
The method provided in the above embodiments can simulate the microstructure changes and stress distribution of LST-GDC in different sintering processes with coarse-grained molecular dynamics, and observe the sintering process visually, which provides a theoretical guidance for low-stress preparation of rSOFC.
Finally, it should be noted that: The above embodiments are only used to illustrate the technical solutions of the invention, rather than restrict them. Although the invention has been described in detail with reference to the preferred embodiments, those ordinary technical personnel in the field should understand that: They can still modify or equivalently replace the technical solutions of the invention, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the invention.
Claims (3)
1. A preparation method for low-stress electrode material sintering based on the mesoscale model, which is characterized in that: The specific steps are as follows,
Step Si: Select the potential function that can reflect the interaction forces between all atoms contained in the LST-GDC system of rSOFC composite anode material;
Step S2: Import the unit cell models of LST and GDC through the observation module of the molecular modeling software, and obtain the coarse-grained unit cell by modifying its lattice constant to be the original integral multiples. Meanwhile, the atom number, mass and charge number of the unit cell should also be changed to the original exponential multiples, so as to increase the number of atoms that can be expressed under the same amount of calculation;
Step S3: Establish the electrically neutral LST coarse-grained nanoclusters and GDC coarse-grained nanoclusters, respectively. The coarse-grained model potential function parameters should be fitted and optimized according to the corresponding coarse-grained multiples, and verified according to the all-atom model;
Step S4: Place two LST and GDC nanoclusters with the same ratio into a simulation box, and use the msi2lmp tool that comes with the molecular dynamics simulation software Lammps to convert them into the model data that can be identified by Lammps;
Step S5: Set and simulate related parameters: the sintering temperature of the simulation system is set to 1673K, and the integration step is selected to be Ifs; determine the initial position and velocity of the atom, predict the velocity of the atom at the next moment according to the potential energy of computing system and the atom forces, according to the Verlet integration algorithm, and use VonMises method to calculate the equivalent stress of each atom;
Step S6: Use Lammps software to perform molecular dynamics simulation calculation on the self-written program files, count the calculation results, and obtain the output files of related data of the simulation process and stress calculation results. The output files contain the change information of variable parameters and atomic coordinates, and select the Ovito software for visualization processing, which shows the whole microstructure evolution and the final stress distribution state.
2. A preparation method for low-stress electrode material sintering based on the mesoscale model as described in Claim 1, which is characterized in that: In Step S, the potential function is composed of Born-Mayer-Huggins, which describes the short-range interaction force, and the Coulomb potential, which describes the long-range force of charge.
3. A preparation method for low-stress electrode material sintering based on the mesoscale model as described in Claim 1, which is characterized in that: In Step S3, establish the electrically neutral LST coarse-grained nanoclusters and GDC coarse-grained nanoclusters, respectively through Build Nanocluster.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113970478A (en) * | 2021-09-06 | 2022-01-25 | 武汉科技大学 | Method for measuring bonding strength of laser cladding interface based on molecular dynamics |
| CN114757047A (en) * | 2022-04-28 | 2022-07-15 | 西安交通大学 | Multi-scale modeling calculation method for bearing steel material M50 alloy |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113970478A (en) * | 2021-09-06 | 2022-01-25 | 武汉科技大学 | Method for measuring bonding strength of laser cladding interface based on molecular dynamics |
| CN113970478B (en) * | 2021-09-06 | 2023-12-19 | 武汉科技大学 | Method for measuring bonding strength of laser cladding interface based on molecular dynamics |
| CN114757047A (en) * | 2022-04-28 | 2022-07-15 | 西安交通大学 | Multi-scale modeling calculation method for bearing steel material M50 alloy |
| CN114757047B (en) * | 2022-04-28 | 2024-04-02 | 西安交通大学 | Multi-scale modeling calculation method for bearing steel material M50 alloy |
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