积极学习指导计算发现有机非水性氧流电池的植物性氧化剂
Akash Jain1,2, Ilya A Shkrob1,3, Hieu A Doan1,2
1Joint Center for Energy Storage Research (JCESR), Argonne National Laboratory, Lemont, Illinois 60439, United States.
ACS applied materials & interfaces
|December 10, 2023
概括
研究人员探索了植物性黄类分子作为有机非水性氧化还原流电池 (O-NRFB) 的经济有效和环保的还原剂. 计算方法确定了改进能源存储解决方案的有希望的候选人.
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:
- 有机非水性氧化还原流电池 (O-NRFB) 使用丰富的材料提供可扩展的能量存储.
- 开发具有成本效益和对环境无害的氧化还原活性有机分子 (redoxmers) 对O-NRFBs至关重要.
- 植物性化合物是新型氧化还原体开发的可持续来源.
研究的目的:
- 以计算方式研究黄类衍生物作为O-NRFBs的潜在氧化还原剂.
- 使用天然产品架构设计和优化新型氧化还原剂.
- 探索机器学习在设计先进的储能材料中的应用.
主要方法:
- 在flavone和isoflavone支架的in silico衍生生成一个大库 (>40,000) 的候选分子.
- 利用了一种新的算法,在候选生成过程中惩罚过于复杂的分子结构.
- 采用基于贝叶斯优化的多目标主动学习算法来识别最佳的氧化还原体候选者.
主要成果:
- 确定了特定的黄和异黄衍生物,分别是有前途的阴解质和阳解质材料.
- 演示了调整自然产品衍生分子的氧化还原潜力的计算策略.
- 创建了一个多样化的潜在氧化还原剂库,具有O-NRFBs的理想特征.
结论:
- 黄类衍生物显示出作为O-NRFBs的氧化还原剂的显著潜力,提供了一个可持续的替代品.
- 该研究强调了将计算算法与专家化学知识相结合用于分子设计的有效性.
- 开发的方法可以加速发现用于可再生能源存储的先进材料.
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