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Obstructed surface states as the descriptor for predicting catalytic active sites in inorganic crystalline materials

MPS-Authors
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Xu,  Yuanfeng
Max Planck Institute of Microstructure Physics, Max Planck Society;

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Sessi,  Paolo
Nano-Systems from Ions, Spins and Electrons, Max Planck Institute of Microstructure Physics, Max Planck Society;

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Parkin,  Stuart S. P.       
Nano-Systems from Ions, Spins and Electrons, Max Planck Institute of Microstructure Physics, Max Planck Society;

Bernevig,  B. Andrei
Max Planck Institute of Microstructure Physics, Max Planck Society;

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Citation

Li, G., Xu, Y., Song, Z., Yang, Q., Zhang, Y., Liu, J., et al. (2022). Obstructed surface states as the descriptor for predicting catalytic active sites in inorganic crystalline materials. Advanced Materials, 34(26): 2201328. doi:10.1002/adma.202201328.


Cite as: https://hdl.handle.net/21.11116/0000-000A-9039-3
Abstract
The discovery of new catalysts that are efficient and sustainable is a major research endeavor for many industrial chemical processes. This requires an understanding and determination of the catalytic origins, which remains a challenge. Here, a novel method to identify the position of active sites based on searching for crystalline symmetry-protected obstructed atomic insulators (OAIs) that have metallic surface states is described. The obstructed Wannier charge centers (OWCCs) in OAIs are pinned by symmetries at some empty Wyckoff positions so that surfaces that accommodate these sites are guaranteed to have metallic obstructed surface states (OSSs). It is proposed and confirmed that the OSSs are the catalytic activity origins for crystalline materials. The theory on 2H-MoTe2, 1T′-MoTe2, and NiPS3 bulk single crystals is verified, whose active sites are consistent with the calculations. Most importantly, several high-efficiency catalysts are successfully identified just by considering the number of OWCCs and the symmetry. Using the real-space-invariant theory applied to a database of 34 013 topologically trivial insulators, 1788 unique OAIs are identified, of which 465 are potential high-performance catalysts. The new methodology will facilitate and accelerate the discovery of new catalysts for a wide range of heterogeneous redox reactions.