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首页> 外文期刊>Journal of the American Chemical Society >Toward Totally Defined Nanocatalysis: Deep Learning Reveals theExtraordinary Activity of Single Pd/C Particles
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Toward Totally Defined Nanocatalysis: Deep Learning Reveals theExtraordinary Activity of Single Pd/C Particles

机译:Toward Totally Defined Nanocatalysis: Deep Learning Reveals theExtraordinary Activity of Single Pd/C Particles

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摘要

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

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