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Hierarchically structured allotropes of phosphorus from data‐driven exploration

Abstract:

The discovery of materials is increasingly guided by quantum‐mechanical crystal‐structure prediction, but the structural complexity in bulk and nanoscale materials remains a bottleneck. Here we demonstrate how data‐driven approaches can vastly accelerate the search for complex structures, combining a machine‐learning (ML) model for the potential‐energy surface with efficient, fragment‐based searching. We use the characteristic building units observed in Hittorf’s and fibrous phosphorus to see...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Sub department:
Inorganic Chemistry
Oxford college:
St Anne's College
Role:
Author
ORCID:
0000-0001-6873-0278
Publisher:
Wiley
Journal:
Angewandte Chemie International Edition More from this journal
Volume:
59
Issue:
37
Pages:
15880-15885
Publication date:
2020-06-04
Acceptance date:
2020-06-02
DOI:
ISSN:
1433-7851
Language:
English
Keywords:
Pubs id:
1109034
Local pid:
pubs:1109034
Deposit date:
2020-06-04

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