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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Defected phosphorene dataset and trained HNNP models

Research datakeyboard_double_arrow_right Dataset 09 Oct 2023Publisher:Zenodo
Authors: Lukáš Kývala; Andrea Angeletti; Cesare Franchini; Christoph Dellago;

doi: 10.5281/zenodo.8421093 , 10.5281/zenodo.8421111

Defected phosphorene dataset and trained HNNP models

Abstract

The dataset contains pristine monolayer phosphorene as well as structures with monovacancies and divacancies. The data was obtained using Density Functional Theory (VASP). The Perdew-Burke-Ernzerhof PBE functional was employed with an energy cutoff of 600 eV. The Brillouin zone was sampled by using a 3 × 3 × 1 Gamma-centered mesh. The input.data file is suitable for packages such as n2p2 and Runner. Information about neural network potential are provided in the publication (10.1021/acs.jpcc.3c05713).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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