High-throughput ab initio design of atomic interfaces using InterMatch
Eli Gerber (),
Steven B. Torrisi,
Sara Shabani,
Eric Seewald,
Jordan Pack,
Jennifer E. Hoffman,
Cory R. Dean,
Abhay N. Pasupathy and
Eun-Ah Kim
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Eli Gerber: Cornell University
Steven B. Torrisi: Harvard University
Sara Shabani: Columbia University
Eric Seewald: Columbia University
Jordan Pack: Columbia University
Jennifer E. Hoffman: Harvard University
Cory R. Dean: Columbia University
Abhay N. Pasupathy: Columbia University
Eun-Ah Kim: Cornell University
Nature Communications, 2023, vol. 14, issue 1, 1-7
Abstract:
Abstract Forming a hetero-interface is a materials-design strategy that can access an astronomically large phase space. However, the immense phase space necessitates a high-throughput approach for an optimal interface design. Here we introduce a high-throughput computational framework, InterMatch, for efficiently predicting charge transfer, strain, and superlattice structure of an interface by leveraging the databases of individual bulk materials. Specifically, the algorithm reads in the lattice vectors, density of states, and the stiffness tensors for each material in their isolated form from the Materials Project. From these bulk properties, InterMatch estimates the interfacial properties. We benchmark InterMatch predictions for the charge transfer against experimental measurements and supercell density-functional theory calculations. We then use InterMatch to predict promising interface candidates for doping transition metal dichalcogenide MoSe2. Finally, we explain experimental observation of factor of 10 variation in the supercell periodicity within a few microns in graphene/α-RuCl3 by exploring low energy superlattice structures as a function of twist angle using InterMatch. We anticipate our open-source InterMatch algorithm accelerating and guiding ever-growing interfacial design efforts. Moreover, the interface database resulting from the InterMatch searches presented in this paper can be readily accessed online.
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43496-5
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DOI: 10.1038/s41467-023-43496-5
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