基于数据的发现,单原子催化剂的二氧化碳减少,考虑到pH的依赖性可逆电极尺度的可逆电极尺度
Yue Chu1,2, Yuhang Wang2,3, Di Zhang2
1School of Chemical Engineering, Dalian University of Technology, Dalian 116024, China.
The Journal of chemical physics
|May 2, 2025
概括
这项研究开发了一种依赖pH值的模型,用于使用单原子催化剂将二氧化碳电化学减少为一氧化碳. 该模型准确地预测了各种条件下的催化剂性能,识别了有希望的Fe,Cu和Ni催化剂.
科学领域:
- 电化学 电化学 电化学
- 材料科学 材料科学 材料科学
- 计算化学的计算化学
背景情况:
- 电化学二氧化碳减排 (CO2RR) 是气候变化缓解和能源解决方案的关键.
- 二氧化碳是CO2RR的经济价值产物.
- 单原子催化剂 (SAC) 对CO2RR具有前景,但它们的性能对pH敏感.
研究的目的:
- 开发一个统一的,pH值依赖的模型,用于d块过渡金属SACs在CO2RR到CO.
- 识别高绩效的SAC并了解管理其活动的因素.
- 为设计高效的CO2RR催化剂提供理论框架.
主要方法:
- 对939个实验CO2RR性能数据进行大规模数据挖掘.
- 密度函数理论 (DFT) 的计算.
- 对于101个SAC的pH依赖微动力学建模和pH电场合微动力学建模.
主要成果:
- 确定了12种高性能SAC (基于Fe,Cu,Ni),在pH范围内具有良好的CO选择性.
- 建立了*COOH和*CO中间体之间的缩放关系.
- 证明了电场效应的关键作用,并根据实验数据验证了模型.
结论:
- 开发的理论模型准确地捕捉了pH取决于CO2RR-to-CO的性能.
- 这为使用M-N-C催化剂优化CO2-CO转换提供了一个通用设计原则.
- 这些发现使下一代CO2RR催化剂的合理设计成为可能.
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