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Coarse-grained versus fully atomistic machine learning for zeolitic imidazolate frameworks.

ABSTRACT: Zeolitic imidazolate frameworks are widely thought of as being analogous to inorganic AB₂ phases. We test the validity of this assumption by comparing simplified and fully atomistic machine-learning models for local environments in ZIFs. Our work addresses the central question to what extent chemical information can be "coarse-grained" in hybrid framework materials.

SUBMITTER: Faure Beaulieu Z

PROVIDER: S-EPMC10513772 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Coarse-grained <i>versus</i> fully atomistic machine learning for zeolitic imidazolate frameworks.

Faure Beaulieu Zoé Z Nicholas Thomas C TC Gardner John L A JLA Goodwin Andrew L AL Deringer Volker L VL

Chemical communications (Cambridge, England) 20230921 76

Zeolitic imidazolate frameworks are widely thought of as being analogous to inorganic AB<sub>2</sub> phases. We test the validity of this assumption by comparing simplified and fully atomistic machine-learning models for local environments in ZIFs. Our work addresses the central question to what extent chemical information can be "coarse-grained" in hybrid framework materials. ...[more]

PMID: 37668310

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