A Systematic Theoretical Study on the Structure-Property Relationships of Fluorinated Linear Carbonates Based on Molecular Simulation and Machine Learning

Haoxuan He; Lin Wei (70005); Yuxuan Chen; Yaqian Deng; Zhengyuan Xiong; Dian Zhou; Peinan Lin; Yiren Tao; Rui Xia; E. Zhang; Jiaxin Chen; Yenan Xu; Xinyu Liu; Yuqing Liao; Yu Ying; Qiang Ru; Jianhui Li

doi:10.1039/d6ta02519f

January 1, 2026Journal of Materials Chemistry A

A Systematic Theoretical Study on the Structure-Property Relationships of Fluorinated Linear Carbonates Based on Molecular Simulation and Machine Learning

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Key Points

This research aims to understand the relationship between the molecular structure of fluorinated linear carbonates and their properties for use in lithium metal batteries.
Utilized molecular simulations to analyze the properties of various fluorinated linear carbonates.
Applied machine learning techniques to predict performance outcomes based on structural variations.
Conducted systematic theoretical studies on the impact of fluorination patterns on electrolyte properties.
Identified key fluorination patterns that enhance the electrochemical stability of the linear carbonates.
Demonstrated significant improvements in electrolyte performance metrics for lithium metal batteries with optimized fluorination.
Provided predictive models that accurately forecast the behavior of different fluorinated carbonate combinations.

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Implication

Systematic theoretical study explores how fluorination affects properties of fluorinated linear carbonates, indicating potential for better lithium metal batteries.

Abstract

Electrolyte engineering utilizing fluorinated linear carbonates (DMC, EMC, and DEC) holds immense promise for high-voltage lithium metal batteries. Despite extensive research, a systematic understanding of how fluorination patterns precisely dictate...

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Cite This Study

He et al. (2026) studied this question.

synapsesocial.com/papers/6a250b8b7def13d035e1b93e https://doi.org/10.1039/d6ta02519f

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A Systematic Theoretical Study on the Structure-Property Relationships of Fluorinated Linear Carbonates Based on Molecular Simulation and Machine Learning

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

A Systematic Theoretical Study on the Structure-Property Relationships of Fluorinated Linear Carbonates Based on Molecular Simulation and Machine Learning

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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