首页|Well-defined high entropy-metal nanoparticles:Detection of the multi-element particles by deep learning

Well-defined high entropy-metal nanoparticles:Detection of the multi-element particles by deep learning

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Characterizing and control the chemical compositions of multi-element particles as single metal nanoparticles(mNPs)on the surfaces of catalytic metal oxide supports is challenging.This can be attrib-uted to the heterogeneity and large size at the nanoscale,the poorly defined catalyst nanostructure,and thermodynamic immiscibility of the strongly repelling metallic elements.To address these challenges,an ultrasonic-assisted coincident electro-oxidation-reduction-precipitation(U-SEO-P)is presented to fabri-cate ultra-stable PtRuAgCoCuP NPs,which produces numerous active intermediates and induces strong metal-support interactions.To sort the active high-entropy mNPs,individual NPs are described on the support surface and the role of deep learning in understanding/predicting the features of PtRuAgCoCu@TiOx catalysts is explained.Notably,this deep learning approach required minimal to no human input.The as-prepared PtRuAgCoCu@TiOx catalysts can be used to catalyze various important chemical reactions,such as a high reduction conversion(100％in 30 s),with no loss of catalytic activity even after 20 cycles of nitroarene and ketone/aldehyde,which is several times higher than commercial Pt@TiOx owing to individual PtRuAgCoCuP NPs on TiOx surface.In this study,we present the"Totally Defined Catalysis"concept,which has enormous potential for the advancement of high-activity catalysts in the reduction of organic compounds.

Metal nanoparticlesDeep learningCatalystReduction

Manar Alnaasan、Wail Al Zoubi、Salh Alhammadi、Jee-Hyun Kang、Sungho Kim、Young Gun Ko

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Department of Electronics Engineering,Yeungnam Univeristy,280 Daeha-ro,Gyeongsan,38541,Republic of Korea

Materials Electrochemistry Laboratory,School of Materials Science and Engineering,Yeungnam University,Gyeongsan 38541,Republic of Korea

Department of Future Energy Convergence,Seoul National University of Science and Technology,232 Gongneung-Ro,Nowon-Gu,Seoul 01811,Republic of Korea

School of Materials Science and Engineering,Institute of Materials Technology,Yeungnam University,Gyeongsan 38541,Republic of Korea

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2024

10.1016/j.jechem.2024.06.038

能源化学
中国科学院大连化学物理研究所 中国科学院成都有机化学研究所

能源化学

CSTPCDEI
影响因子：0.654
ISSN：2095-4956
年,卷(期)：2024.98(11)