Unravelling abnormal in-plane stretchability of two-dimensional metal–organic frameworks by machine learning potential molecular dynamics

Dong Fan; Aydin Ozcan; Pengbo Lyu; Guillaume Maurin

doi:10.1039/d3nr05966a

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Unravelling abnormal in-plane stretchability of two-dimensional metal–organic frameworks by machine learning potential molecular dynamics

Journal article

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Unravelling abnormal in-plane stretchability of two-dimensional metal–organic frameworks by machine learning potential molecular dynamics

Dong Fan, Aydin Ozcan, Pengbo Lyu and Guillaume Maurin

Nanoscale, Vol.16(7), pp.3438-3447

2024

DOI: https://doi.org/10.1039/d3nr05966a

Abstract

The concept of negative in-plane stretchability is proposed taking a 2D MOF, namely NiF 2 (pyrazine) 2 , as a case study, combining high-precision first-principles calculations and machine-learning potential (MLP) approaches.

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Title: Unravelling abnormal in-plane stretchability of two-dimensional metal–organic frameworks by machine learning potential molecular dynamics
Creators - without role: Dong Fan - Université de Montpellier, Institut Charles Gerhardt Montpellier - ICGM
Aydin Ozcan - Université de Montpellier, Institut Charles Gerhardt Montpellier - ICGM
Pengbo Lyu - Université de Montpellier, Institut Charles Gerhardt Montpellier - ICGM
Guillaume Maurin - Université de Montpellier, Institut Charles Gerhardt Montpellier - ICGM
Publication Details: Nanoscale, Vol.16(7), pp.3438-3447
Identifiers: 9937378609311
Academic Unit: Institut Charles Gerhardt Montpellier - ICGM
Language: English
Resource Type: Journal article
Local Fields: hal-04990558