Ervin Rems, Tim Šlosar, Sara Drvaric Talian, Matej Huš, Robert Dominko, Alessandra Serva
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Strongly vs weakly associating anions: Transport-structure relationship in LiTFSI-LiNO3 electrolytes
Liquid battery electrolytes based on mixtures of salts with weakly and strongly associating anions have emerged as a promising route toward high-performance, sustainable battery technologies. Their success is primarily attributed to the unique influence of salt composition on the solvation structure. Here, we employ classical molecular dynamics simulations, corroborated by experimental data, to study mixed lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) / lithium nitrate (LiNO3) in diglyme electrolytes, a formulation of particular interest for lithium–sulfur and lithium-oxygen batteries. We investigate how the ratio of weakly associating anions (TFSI-) to strongly associating anions (NO3-) affects ion transport within the electrolyte. Our findings reveal that the anion ratio significantly impacts both the solvation structure and the solvation dynamics, which together contribute to the distinct transport behavior observed in these systems. These findings underscore the tunability of battery electrolyte transport properties through careful mixing of anions.
期刊介绍:
Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions.
The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.