ArticleChemical science2022
Unraveling the origin of reductive stability of super-concentrated electrolytes from first principles and unsupervised machine learning.
Article in Chemical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Domain oriented universal machine learning potential enables fast exploration of chemical space of battery electrolytes.Nature communications · 2025Article
- Operando Study Insights into Lithiation/Delithiation Processes in a Poly(ethylene oxide) Electrolyte of All-Solid-State Lithium Batteries by Grazing-Incidence X-ray Scattering.ACS applied materials & interfaces · 2024Article
- Ab Initio Molecular Dynamics Simulations of Aqueous LiTFSI Solutions─Structure, Hydrogen Bonding, and IR Spectra.The journal of physical chemistry. B · 2024Article
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Authors and funding
2 authors.
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Abstract
Developing electrolytes with excellent electrochemical stability is critical for next-generation rechargeable batteries. Super-concentrated electrolytes (SCEs) have attracted great interest due to their high electrochemical performances and stability. Previous studies have revealed changes in solvation structures and shifts in lowest unoccupied molecular orbitals from solvents to anions, promoting the formation of an anion-derived solid-electrolyte-interphase (SEI) in SCE. However, a direct connection at the atomic level to electrochemical properties is still missing, hindering the rational optimization of electrolytes. Herein, we combine
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