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Computation-accelerated discovery of the K₂NiF₄-type oxyhydrides combing density functional theory and machine learning approach.

ABSTRACT: The emerging K₂NiF₄-type oxyhydrides with unique hydride ions (H^-) and O^2- coexisting in the anion sublattice offer superior functionalities for numerous applications. However, the exploration and innovations of the oxyhydrides are challenged by their rarity as a limited number of compounds reported in experiments, owing to the stringent laboratory conditions. Herein, we employed a suite of computations involving ab initio methods, informatics and machine learning to investigate the stability relationship of the K₂NiF₄-type oxyhydrides. The comprehensive stability map of the oxyhydrides chemical space was constructed to identify 76 new compounds with good thermodynamic stabilities using the high-throughput computations. Base

SUBMITTER: Bai Q

PROVIDER: S-EPMC9458981 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Computation-accelerated discovery of the K₂NiF₄-type oxyhydrides combing density functional theory and machine learning approach.

OmicsDI is part of the ELIXIR infrastructure

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Computation-accelerated discovery of the K2NiF4-type oxyhydrides combing density functional theory and machine learning approach.

OmicsDI is part of the ELIXIR infrastructure

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Computation-accelerated discovery of the K₂NiF₄-type oxyhydrides combing density functional theory and machine learning approach.