Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using Complementary DFT and Machine Learning Approaches

Abbas, Sherif; Isayev, O; Stampfl, C; Shapter, J; Winkler, DA; Ford, MJ

Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using Complementary DFT and Machine Learning Approaches

https://hdl.handle.net/10536/DRO/DU:30152460
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posted on 2024-06-05, 11:59 authored by Sherif AbbasSherif Abbas, O Isayev, C Stampfl, J Shapter, DA Winkler, MJ Ford

Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using Complementary DFT and Machine Learning Approaches

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DOI - Is version of https://doi.org/10.1002/adts.201800128

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London, Eng.

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Yes

Link to full text

https://rss.onlinelibrary.wiley.com/doi/am-pdf/10.1002/adts.201800128

Language

eng

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C1.1 Refereed article in a scholarly journal

Journal

Advanced Theory and Simulations

Volume

2

Article number

1800128

Pagination

1-11

ISSN

2513-0390

eISSN

2513-0390

Issue

1

Publisher

Wiley

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National Computational Infrastructure (NCI), and Pawsey Supercomputing Centre with funding from the Australian Government and the Government of Western Australia Australian Research Council, ARC DP160101301 Naval Research (ONR) award N00014-16-1-2311 4016 Materials engineering

Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using Complementary DFT and Machine Learning Approaches

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Open access

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