Toward Totally Defined Nanocatalysis: Deep Learning Reveals the Extraordinary Activity of Single Pd/C Particles

Toward Totally Defined Nanocatalysis: Deep Learning Reveals the Extraordinary Activity of Single Pd/C Particles Full article

Journal

Journal of the American Chemical Society
ISSN: 0002-7863 , E-ISSN: 1520-5126

Output data

Year: 2022, Volume: 144, Number: 13, Pages: 6071-6079 Pages count : 9 DOI: 10.1021/jacs.2c01283

Authors

Eremin Dmitry B. ^1,2 , Galushko Alexey S. ² , Boiko Daniil A. ² , Pentsak Evgeniy O. ² , Chistyakov Igor V. ² , Ananikov Valentine P. ²

Affiliations

1	Bridge Institute and Department of Chemistry, University of Southern California, 1002 Childs Way, Los Angeles, California 90089-3502, United States
2	Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Pr. 47, Moscow 119991, Russia

Homogeneous catalysis is typically considered “well-defined” from the standpoint of catalyst structure unambiguity. In contrast, heterogeneous nanocatalysis often falls into the realm of “poorly defined” systems. Supported catalysts are difficult to characterize due to their heterogeneity, variety of morphologies, and large size at the nanoscale. Furthermore, an assortment of active metal nanoparticles examined on the support are negligible compared to those in the bulk catalyst used. To solve these challenges, we studied individual particles of the supported catalyst. We made a significant step forward to fully characterize individual catalyst particles. Combining a nanomanipulation technique inside a field-emission scanning electron microscope with neural network analysis of selected individual particles unexpectedly revealed important aspects of activity for widespread and commercially important Pd/C catalysts. The proposed approach unleashed an unprecedented turnover number of 109 attributed to individual palladium on a nanoglobular carbon particle. Offered in the present study is the Totally Defined Catalysis concept that has tremendous potential for the mechanistic research and development of high-performance catalysts.

Eremin D.B. , Galushko A.S. , Boiko D.A. , Pentsak E.O. , Chistyakov I.V. , Ananikov V.P.
Toward Totally Defined Nanocatalysis: Deep Learning Reveals the Extraordinary Activity of Single Pd/C Particles
Journal of the American Chemical Society. 2022. V.144. N13. P.6071-6079. DOI: 10.1021/jacs.2c01283 WOS Scopus OpenAlex

Web of science:	WOS:000789021900047
Scopus:	2-s2.0-85127606895
OpenAlex:	W4220934643

DB	Citing
OpenAlex	156
Scopus	17
Web of science	21