ArticleChemical science2024
Cluster analysis as a tool for quantifying structure-transport properties in simulations of superconcentrated electrolyte.
Article in Chemical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Nonmonotonic Screening and Solvation Dynamics of the Electrical Double Layer in Concentrated Lithium Salt Electrolytes.Nature communications · 2026Article
- Domain oriented universal machine learning potential enables fast exploration of chemical space of battery electrolytes.Nature communications · 2025Article
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Authors and funding
2 authors.
Funding
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Abstract
Using molecular dynamics simulations and graph-theory-based cluster analysis, we investigate the structure-transport properties of typical water-in-salt electrolytes. We demonstrate that ions exhibit distinct dynamics across different ionic clusters-namely, solvent-separated ion pairs (SSIPs), contact ion pairs (CIPs), and aggregates (AGGs). We assess the average proportions of various ionic species and their lifetimes. Our method reveals a dynamic decoupling of ion kinetics, with each species independently contributing to the overall molecular motion. This is evidenced by the fact that the total velocity autocorrelation function (VACF) and power spectrum can be expressed as a weighted sum of independent functions for each species. The experimental data on the ionic conductivity of the studied LiTFSI electrolytes align well with our theoretical predictions at various concentrations, based on the proportions and diffusion coefficients of free ions derived from our analysis. The insights gained into the solvation structures and dynamics of different ionic species enable us to elucidate the physical mechanisms driving ion transport in such superconcentrated electrolytes, providing a comprehensive framework for the future design and optimization of electrolytes.
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