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Enhancing ReaxFF for molecular dynamics simulations of lithium-ion batteries: an interactive reparameterization
Paolo De Angelis1, Roberta Cappabianca2, Matteo Fasano2
1Department of Energy "Galileo Ferraris", Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino, Italy. paolo.deangelis@polito.it.
Scientific Reports
|January 10, 2024
Summary
This study refines ReaxFF force fields for lithium-ion battery simulations. The new ReaxFF improves lithium diffusion prediction in solid Lithium Fluoride, crucial for battery performance and safety.
Area of Science:
- Materials Science
- Computational Chemistry
- Electrochemistry
Background:
- Lithium-ion batteries (LIBs) are vital for green energy technologies.
- The solid-electrolyte interphase (SEI) is critical for LIB safety and performance.
- Accurate simulation of SEI components is needed.
Purpose of the Study:
- Enhance ReaxFF force field parametrization for SEI components.
- Focus on Lithium Fluoride (LiF) for improved molecular dynamics (MD) simulations.
- Improve prediction of LiF properties and lithium transport.
Main Methods:
- Developed an automated reparameterization protocol using Python libraries.
- Generated a dataset of LiF configurations for training.
- Performed MD simulations with the optimized ReaxFF.
Main Results:
- The new ReaxFF accurately models the solid nature of LiF.
- Significantly improved prediction of lithium diffusivity in LiF (two orders of magnitude).
- Highlighted ReaxFF's sensitivity to training data and interpolation challenges.
Conclusions:
- The optimized ReaxFF is effective for specific SEI phenomena.
- An interactive reparameterization protocol aids dataset construction.
- Further development of versatile force fields is needed for advanced simulations.
