Efficient Screening of Metal Promoters of Pt Catalysts for C-H Bond Activation in Propane Dehydrogenation from a Combined First-Principles Calculations and Machine-Learning Study

doi:10.1021/acsomega.3c02675

IMR OpenIR

	Efficient Screening of Metal Promoters of Pt Catalysts for C-H Bond Activation in Propane Dehydrogenation from a Combined First-Principles Calculations and Machine-Learning Study
	Zhou, Nuodan 1,2; Liu, Wen 3; Jan, Faheem 1,2; Han, ZhongKang 3; Li, Bo 4
通讯作者	Han, ZhongKang(hanzk@zju.edu.cn) ; Li, Bo(boli@synu.edu.cn)
	2023-06-21
发表期刊	ACS OMEGA
ISSN	2470-1343
卷号	8 期号:26 页码:23982-23990
摘要	Platinum-based materials are the most widely used catalystsinpropane direct dehydrogenation, which could achieve a balanced activitybetween both propane conversion and propene formation. One of thecore issues of Pt catalysts is how to efficiently activate the strongC-H bond. It has been suggested that adding second metal promoterscould greatly solve this problem. In the current work, first-principlescalculations combined with machine learning are performed in orderto obtain the most promising metal promoters and identify key descriptorsfor control performance. The combination of three different modesof adding metal promoters and two ratios between promoters and platinumsufficiently describes the system under investigation. The activityof propane activation and the formation of propene are reflected bythe increase or decrease of the adsorption energy and C-H bondactivation of propane and propene after the addition of promoters.The data of adsorption energy and kinetic barriers from first-principlescalculations are streamed into five machine-learning methods includinggradient boosting regressor (GBR), K neighbors regressor (KNR), randomforest regressor (RFR), and AdaBoost regressor (ABR) together withthe sure independence screening and sparsifying operator (SISSO).The metrics (RMSE and R (2)) from differentmethods indicated that GBR and SISSO have the most optimal performance.Furthermore, it is found that some descriptors derived from the intrinsicproperties of metal promoters can determine their properties. In theend, Pt3Mo is identified as the most active catalyst. Thepresent work not only provides a solid foundation for optimizing Ptcatalysts but also provides a clear roadmap to screen metal alloycatalysts.
资助者	Natural Science Foundation of Liao Ning Province ; Shenyang Normal University ; Program for Excellent Talents at Shenyang Normal University ; Fundamental Research Funds for the Central Universities, China
DOI	10.1021/acsomega.3c02675
收录类别	SCI
语种	英语
资助项目	Natural Science Foundation of Liao Ning Province[2021-MS-004] ; Shenyang Normal University[BS202208] ; Program for Excellent Talents at Shenyang Normal University ; Fundamental Research Funds for the Central Universities, China
WOS研究方向	Chemistry
WOS类目	Chemistry, Multidisciplinary
WOS记录号	WOS:001013711400001
出版者	AMER CHEMICAL SOC
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/178403
专题	中国科学院金属研究所
通讯作者	Han, ZhongKang; Li, Bo
作者单位	1.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, Shenyang 110016, Liaoning, Peoples R China 2.Univ Sci & Technol China, Sch Mat Sci & Engn, Shenyang 110016, Liaoning, Peoples R China 3.Zhejiang Univ, Sch Mat Sci & Engn, Hangzhou 310027, Peoples R China 4.Shenyang Normal Univ, Inst Catalysis Energy & Environm, Coll Chem & Chem Engn, Shenyang 110034, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Nuodan,Liu, Wen,Jan, Faheem,et al. Efficient Screening of Metal Promoters of Pt Catalysts for C-H Bond Activation in Propane Dehydrogenation from a Combined First-Principles Calculations and Machine-Learning Study[J]. ACS OMEGA,2023,8(26):23982-23990.
APA	Zhou, Nuodan,Liu, Wen,Jan, Faheem,Han, ZhongKang,&Li, Bo.(2023).Efficient Screening of Metal Promoters of Pt Catalysts for C-H Bond Activation in Propane Dehydrogenation from a Combined First-Principles Calculations and Machine-Learning Study.ACS OMEGA,8(26),23982-23990.
MLA	Zhou, Nuodan,et al."Efficient Screening of Metal Promoters of Pt Catalysts for C-H Bond Activation in Propane Dehydrogenation from a Combined First-Principles Calculations and Machine-Learning Study".ACS OMEGA 8.26(2023):23982-23990.