Correlations from ion-pairing and the Nernst-Einstein equation

Abstract

We present a new approximation to ionic conductivity well suited to dynamical atomic-scale simulations, based on the Nernst-Einstein equation. In our approximation, ionic aggregates constitute the elementary charge carriers, and are considered as non-interacting species. This approach conveniently captures the dominant effect of ion-ion correlations on conductivity, short range interactions in the form of clustering. In addition to providing better estimates to the conductivity at a lower computational cost than exact approaches, this new method allows to understand the physical mechanisms driving ion conduction in concentrated electrolytes. As an example, we consider Li${}^{+}$ conduction in poly(ethylene oxide), a standard solid-state polymer electrolyte. Using our newly developed approach, we are able to reproduce recent experimental results reporting negative cation transference numbers at high salt concentrations, and to confirm that this effect can be caused by a large population of negatively charged clusters involving cations.

References in corpus (2)

• Enhancing Cation Diffusion and Suppressing Anion Diffusion via Lewis-Acidic Polymer Electrolytes
• Diffusion of an ellipsoid in bacterial suspensions

Cited by in corpus (22)

• Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials
• Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties
• Ion Conductivity and Correlations in Model Salt-Doped Polymers: Effects of Interaction Strength and Concentration
• Theory of Ion Aggregation and Gelation in Super-Concentrated Electrolytes
• De novo Design of Polymer Electrolytes with High Conductivity using GPT-based and Diffusion-based Generative Models
• Heat and charge transport in H${}_2$O at ice-giant conditions from ab initio molecular dynamics simulations
• Li4-xGe1-xPxO4 a potential solid-state electrolyte for all-oxide microbatteries
• Gelation, Clustering and Crowding in the Electrical Double Layer of Ionic Liquids
• A Self-Improvable Polymer Discovery Framework Based on Conditional Generative Model
• Constant Chemical Potential-Quantum Mechanical-Molecular Dynamics simulations of the Graphene-electrolyte double layer
• Electrolytes for Li-ion all-solid-state batteries: a first-principles comparative study of Li10GeP2O12 and Li10GeP2S12 in the LISICON and LGPS phases
• Bayesian unsupervised learning reveals hidden structure in concentrated electrolytes
• Spectral denoising for unsupervised analysis of correlated ionic transport
• Superionic states formation in group III oxides irradiated with ultrafast lasers
• Computational Analysis of Composition-Structure-Property-Relationships in NZP-type Materials for Li-Ion Batteries
• Hydrodynamic Interactions in Ion Transport -- Theory and Simulation
• Length scales in electrolytes
• Scaling laws for concentration-gradient-driven electrolyte transport through a 2D membrane
• Theory of cell membrane interaction with glass
• Structural and Dynamical Crossovers in Dense Electrolytes
• Effect of Succinonitrile on Ion Transport in PEO-based Lithium Ion Battery Electrolytes
• Practical Considerations for Finite Concentrations Molecular Dynamics Simulations