Abstract
Traditionally, electrolyte solvents in batteries have been regarded primarily as carrier for ion transporters. Here, we reveal the critical roles of solvents in transforming microscale anode materials into porous nanostructures and in facilitating the formation of thinner, more efficient solid-electrolyte interphase (SEI) layers. Using machine-learning-assisted molecular dynamics simulations combined with density functional theory calculations on Na–CuS batteries, we unveil the significant yet previously unclear impact of solvent choice on solvation/desolvation dynamics, a complex area that has been difficult to resolve with traditional methods. We demonstrate that solvent choice significantly impacts the capacity, particularly the rate performance, primarily due to the desolvation dynamics, thus establishing a direct correlation between solvent selection and battery performance. Our findings highlight DEGDME as the optimal solvent for Na–CuS half-cells, due to its low Na desolvation energy and favorable Na–O bond energy. This leads to exceptional energy capacity (610 mAh/g at 2C) and ultrafast charging capability (520 mAh/g at 30C). This research marks a significant advancement in energy storage technology by demonstrating the crucial role of solvent selection in anode morphology, SEI formation, and desolvation energy optimization.
Original language | English |
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Article number | 151970 |
Journal | Chemical Engineering Journal |
Volume | 491 |
DOIs | |
Publication status | Published - 2024 Jul 1 |
Bibliographical note
Publisher Copyright:© 2024
Keywords
- DFT calculations
- Desolvation dynamics
- Machine-learning-assisted molecular dynamics
- Na-ion battery
- Porous nanostructures
- Solvent
ASJC Scopus subject areas
- General Chemistry
- Environmental Chemistry
- General Chemical Engineering
- Industrial and Manufacturing Engineering