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Prediction Descriptor for Catalytic Activity of Platinum Nanoparticles/Metal-Organic Framework Composites
Peishan Qin1, Junyang Yan1, Wenlei Zhang2
1Key Laboratory of Flexible Electronics (KLOFE), Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing 211816, China.
Abstract:
Supported metal nanoparticles (MNPs) have exhibited superior catalytic performance in various heterogeneous catalysis applications, which is usually influenced or even determined by the physicochemical properties of their porous supports. It is well acknowledged that understanding the regulation mechanism of supports is an important prerequisite to predict the catalytic performance of supported MNPs as well as the development of advanced catalysts. Here, we demonstrated that different transition-metal clusters (from Group IIIB to Group IIB) within metal-organic frameworks (MOFs) could accurately regulate the surface electronic status of supported platinum nanoparticles (Pt NPs), and the Pt/MOF composites showed a periodic activity trend in hydrogenation of 1-hexene. A strong correlation was found between the catalytic activity of Pt/MOF composites and the number of electrons in their outmost d orbitals of the transition-metal species, suggesting that the latter could play the role of prediction descriptor. Furthermore, this descriptor can be extended to predict the hydrogenation activity of more Pt/MOF composites and provide an important guiding principle for the design of supported MNPs catalysts.
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