(192f) Development and Implementation of Enhanced Sampling Approaches: Applications to Ion-Pairing in Battery Electrolytes and Nucleation of Nano-Porous Materials

Fast and accurate simulations of rare phenomena and their energetics are limited by the timescale accessible to conventional molecular dynamics (MD). The development of novel enhanced sampling approaches have provided significant thrusts to overcome those limitations. In this presentation, I will discuss two such examples from my research: one that utilizes an unconventional implementation of an existing method and another that develops a new statistical mechanical method for analyzing complex free energy landscapes.

In the first work, we utilize a biased-sampling (metadynamics) approach on a cluster model consisting of an ion-pair with a single shell of solvent. By sampling transitions between the ion-paired state and solvent separated ion-pair state, we demonstrate that quick estimates of the ion-pairing free energy can be obtained from cluster models that agree well with bulk solvent calculations [1]. However, the cluster model is 1 to 2 orders of magnitude faster than bulk solvent calculations. This has implications for the design of battery electrolytes because ion-pairing can significantly impact conductivity and performance of batteries. Our method provides a novel basis for the screening and assessment of candidates for electrolyte designs.

In the second work, we developed a novel graph theory-based sampling approach [2] for modeling the nucleation of weak electrolytes that overcomes limitations of existing approaches for bulk solvent systems. Our method seeks to exploit the property of materials whose crystal structure exhibit directional bonding and thus can be described as a “graph” of connected monomers. By utilizing a rigorous statistical-mechanics approach, we generate an ensemble of representative nuclei and their corresponding free energies via a “bootstrapping” approach in the nucleus size. Starting with a simple system of aqueous lithium fluoride (LiF), we elucidate the factors governing the nucleation and growth of LiF clusters. Subsequently, this work will be extended to complex materials such as zeolites and metal-organic frameworks.

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[1] Ajay Muralidharan, Tyler Lytle, and Arun Yethiraj. “Why Lithium Ions Stick to Some Anions and not Others”. The Journal of Physical Chemistry B (Accepted), 2021.

[2] Ajay Muralidharan, Xinyi Li, and J.R. Schmidt. “A Hierarchical Graph Theory-Based Sampling Approach to Study the Nucleation of Weak Electrolytes”. (In preparation), 2021