DOI: 10.1103/physrevb.96.024104. Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations

Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations

10.1103/physrevb.96.024104

Crossref journal-article

American Physical Society (APS)

Physical Review B (16)

Bibliography

Ward, L., Liu, R., Krishna, A., Hegde, V. I., Agrawal, A., Choudhary, A., & Wolverton, C. (2017). Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations. Physical Review B, 96(2).

Authors 7

Logan Ward (first)
Ruoqian Liu (additional)
Amar Krishna (additional)
Vinay I. Hegde (additional)
Ankit Agrawal (additional)
Alok Choudhary (additional)
Chris Wolverton (additional)

References 63 Referenced 338

Dates

Type	When
Created	8 years, 1 month ago (July 14, 2017, 6:09 p.m.)
Deposited	5 years, 10 months ago (Sept. 30, 2019, 1:55 a.m.)
Indexed	4 hours, 27 minutes ago (Aug. 22, 2025, 12:56 a.m.)
Issued	8 years, 1 month ago (July 14, 2017)
Published	8 years, 1 month ago (July 14, 2017)
Published Online	8 years, 1 month ago (July 14, 2017)

Funders 3

U.S. Department of Commerce 10.13039/100000190
Region: Americas
gov (National government)
Labels8
1. United States Department of Commerce
2. Department of Commerce
3. U.S. Commerce Dept.
4. Department of Commerce United States of America
5. US Department of Commerce and Labor
6. United States Department of Commerce and Labor
7. DOC
8. USDOC
Awards1
1. 70NANB14H012
National Institute of Standards and Technology 10.13039/100000161
Region: Americas
gov (National government)
Labels4
1. U.S. National Institute of Standards and Technology
2. National Institute for Standards and Technology
3. U.S. Department of Commerce's National Institute of Standards and Technology
4. NIST
National Science Foundation 10.13039/100000001
Region: Americas
gov (National government)
Labels4
1. U.S. National Science Foundation
2. NSF
3. US NSF
4. USA NSF
Awards1
1. DMR-1309957

BibTeX

@article{Ward_2017, title={Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations}, volume={96}, ISSN={2469-9969}, url={http://dx.doi.org/10.1103/physrevb.96.024104}, DOI={10.1103/physrevb.96.024104}, number={2}, journal={Physical Review B}, publisher={American Physical Society (APS)}, author={Ward, Logan and Liu, Ruoqian and Krishna, Amar and Hegde, Vinay I. and Agrawal, Ankit and Choudhary, Alok and Wolverton, Chris}, year={2017}, month=jul }

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