在和离子电池中预测电解质降解反应的图形理论算法
Lyuben Borislavov1, Alia Tadjer1,2, Radostina Stoyanova1
1Institute of General and Inorganic Chemistry, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria.
Materials (Basel, Switzerland)
|February 26, 2025
概括
这项研究引入了结合化学信息学和量子化学的新算法,以预测电池材料降解的副产品. 它有助于识别不必要的反应,提高可持续储能设备的稳定性和性能.
科学领域:
- 材料科学 材料科学 材料科学
- 电化学 电化学 电化学
- 计算化学的计算化学
背景情况:
- 可持续的储能需要用于可充电金属离子电池的新材料.
- 电化学电池材料的稳定性对于电池容量和循环性能至关重要.
- 识别影响复杂电池系统电化学稳定的副作用是具有挑战性的.
研究的目的:
- 开发一种算法,用于预测电化学系统中氧化还原反应的可行的副产品.
- 研究电解质降解机制,专注于乙烯碳酸盐 (EC) 和二甲 (DG).
- 为了模拟电极表面对电解质溶剂降解的影响.
主要方法:
- 结合化学信息学和量子化学方法.
- 开发了一种算法来产生潜在的氧化还原反应的副作用.
- 通过电解质溶剂的脱反应对电极表面的影响进行模拟.
主要成果:
- 预计EC的降解产物包括CO,CO2,乙烯,乙烯氧化物和基离子.
- 预计DG的降解产品主要涉及氧离子.
- 与DG相比,EC降解产生的气体产品数量明显高.
结论:
- 开发的算法准确地预测电解质降解产品,通过实验数据验证.
- 它提供了一种快速的方法来推断新型电解质溶剂的降解产品.
- 该方法可以适应预测电化学系统中其他材料的降解.
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