曲率调节的TM-doped CNTs中NRR的第一原则和机器学习研究
Xiaolin Jiang1, Hongchang Xu1, Lifu Zhang2
1School of Physics, Nankai University, Tianjin, 300071, China. zphu@nankai.edu.cn.
Physical chemistry chemical physics : PCCP
|June 4, 2025
概括
基质曲率显著影响缩单原子催化剂的性能. 较低的曲率通过优化电子结构和中间结合来提高效率,提供新的设计策略.
科学领域:
- 材料科学 材料科学 材料科学
- 催化剂是一种催化剂.
- 计算化学计算化学
背景情况:
- 单原子催化剂 (SAC) 对降解反应 (NRR) 显示出前景.
- SACs的结构和形态工程得到了充分的研究.
- 基质曲率对SAC的影响,特别是对NRR的影响,基本上尚未被探索.
研究的目的:
- 系统地研究基质曲率对单原子过渡金属合碳纳米管 (TM-N3CNTs) 的电催化降解反应 (NRR) 性能的影响.
- 分析曲率,电子结构,中间吸附和反应动力学之间的相互作用.
- 开发机器学习模型,以基于曲率衍生的描述符来预测催化活动.
主要方法:
- 第一个原理计算 (密度函数理论) 来建模具有不同曲率的TM-N3CNTs.
- 热力学和动力学因素的分析,包括分子吸附, *NNH和 *H中间结合能,以及超电位.
- 机器学习使用SISSO算法来识别与反应中间体和自由能量变化相关的关键描述符.
主要成果:
- 在W-N3CNT中,下基质曲率促进了脱局域电子分布和更强的W-N (*NNH) 键,从而减少了超电位.
- 高曲率系统表现出更高的初始反应活性.
- 机器学习模型成功地识别了与曲率,*NNH/*H比率和ΔG(*NNH) 相关的具有物理意义的描述符.
结论:
- 基质曲率是决定单原子催化剂的电催化NRR性能的一个关键因素,但尚未得到充分研究.
- 曲率影响电子特性和中间结合,从而控制催化活性和选择性.
- 这项研究为设计曲率优化的单原子催化剂提供了理论见解,以实现高效的缩.
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