Novel Multi-Scale Modeling Framework for Structure and Transport in Complex Battery Electrolytes
Licentiate thesis, 2018
This thesis outlines a framework where ab initio molecular dynamics initially is used to simulate small periodic systems (∼100 - 1000 atoms) over relatively short time spans (∼1 ps) to obtain trajectories that subsequently are used to train the parameters of a classical force field by force matching. This optimization is performed over all parameters simultaneously by a genetic algorithm. The force fields developed are then used to simulate larger systems (∼1000 - 100 000 atoms) over longer time scales classically (∼1 ns - 1μs). The resulting trajectories are used to collect statistics for a hierarchical analysis, which resolves the structure in terms of dynamic clusters, and quantifies the life-time distribution, population dynamics, and transport properties of identified clusters and non-covalent bonds. The method is ultimately to be of general use to both qualitatively and quantitatively elucidate the ion transport mechanism in novel types of electrolytes as a function of composition.
hierarchical analysis
electrolytes
force field development
molecular dynamics
non-vehicular transport
multi-scale method
Lithium-ion batteries
genetic algorithms
Author
Rasmus Andersson
Chalmers, Physics, Condensed Matter Physics
Driving Forces
Sustainable development
Areas of Advance
Transport
Energy
Materials Science
Roots
Basic sciences
Infrastructure
C3SE (Chalmers Centre for Computational Science and Engineering)
Subject Categories
Other Physics Topics
Condensed Matter Physics
Publisher
Chalmers
Nexus, Origohuset
Opponent: Anders Hellman, Kemisk fysik, Chalmers