Band gap predictions for 2.2 million 2D heterostructures
dataset
posted on 2021-08-27, 02:16 authored by David WinklerDavid Winkler, Joe Shapter, Mike J Ford, Amanda V. Ellis, Peter C. Sherrell, Nick A. Shepelin, Alexander CorlettoA .csv file containing the band gap predictions for 2.2M 2D heterostructures
Funding
ARC DP200101217
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School
- School of Molecular Sciences
Publication Date
2021-08-27Rights Statement
The Author reserves all moral rights over the deposited text and must be credited if any re-use occurs. Documents deposited in OPAL are the Open Access versions of outputs published elsewhere. Changes resulting from the publishing process may therefore not be reflected in this document. The final published version may be obtained via the publisher’s DOI. Please note that additional copyright and access restrictions may apply to the published version.Usage metrics
Categories
- Cheminformatics and quantitative structure-activity relationships
- Computational chemistry
- Atomic and molecular physics
- Nanochemistry
- Supramolecular chemistry
- Optical properties of materials
- Theoretical quantum chemistry
- Macromolecular and materials chemistry not elsewhere classified
- Theory and design of materials
Keywords
2D materialsheterostructuresactive learningmachine learningbandgap materialsCheminformatics and Quantitative Structure-Activity RelationshipsCheminformaticsComputational ChemistryMolecular PhysicsNanochemistry and Supramolecular ChemistryOptical Properties of MaterialsQuantum ChemistrySynthesis of MaterialsTheory and Design of Materials
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