Identifying key factors of peroxymonosulfate activation on single-atom M–N–C catalysts: a combined density functional theory and machine learning study†

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Yun Sun, Jiachun Cao, Qianyu Li, Didi Li and Zhimin Ao
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引用次数: 1

Abstract

Through a combination of density functional theory and machine learning, the intrinsic factors underlying the activation of peroxymonosulfate on a range of single-atom catalysts were revealed.

Abstract Image

确定单原子M-N-C催化剂上过氧单硫酸盐活化的关键因素:密度泛函理论和机器学习研究的结合
过硫酸盐为基础的高级氧化工艺在处理有机污染物方面得到了广泛的好评,但过氧单硫酸盐(PMS)活化的内在因素尚未确定。本研究结合密度泛函理论和机器学习,利用一系列掺杂过渡金属的单原子催化剂,研究了PMS活化的内在因素。选择了三种石墨烯负载的单原子催化剂(M@N2C2, M@N3C1和M@N4,其中M是过渡金属原子)进行PMS吸附和活化。利用d波段理论有效地描述了PMS吸附能与催化剂电子性能之间的关系。基于few-shot学习算法,建立了机器学习模型,揭示了容易获得的属性与能量势垒之间的潜在模式。低能势垒结果表明,最佳候选粒子为V@N4、Cr@N4和Hf@N3C1。代表催化性能的五个电子和几何特征按重要性降序排列为基团数、d电子数、电负性、半径和氮原子数。基于这五个特征,提出了一种新的内禀描述符,可以有效地预测未知催化剂的性能。本研究为PMS活化提供了机理解释和定量指导,有望成为未来开发高效催化剂的一种广泛应用的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Materials Chemistry A
Journal of Materials Chemistry A CHEMISTRY, PHYSICAL-ENERGY & FUELS
CiteScore
19.50
自引率
5.00%
发文量
1892
审稿时长
1.5 months
期刊介绍: The Journal of Materials Chemistry A, B & C covers a wide range of high-quality studies in the field of materials chemistry, with each section focusing on specific applications of the materials studied. Journal of Materials Chemistry A emphasizes applications in energy and sustainability, including topics such as artificial photosynthesis, batteries, and fuel cells. Journal of Materials Chemistry B focuses on applications in biology and medicine, while Journal of Materials Chemistry C covers applications in optical, magnetic, and electronic devices. Example topic areas within the scope of Journal of Materials Chemistry A include catalysis, green/sustainable materials, sensors, and water treatment, among others.
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