DOI: 10.1016/j.actamat.2017.05.009. Extracting knowledge from molecular mechanics simulations of grain boundaries using machine learning

Extracting knowledge from molecular mechanics simulations of grain boundaries using machine learning

10.1016/j.actamat.2017.05.009

Crossref journal-article

Elsevier BV

Acta Materialia (78)

Bibliography

Gomberg, J. A., Medford, A. J., & Kalidindi, S. R. (2017). Extracting knowledge from molecular mechanics simulations of grain boundaries using machine learning. Acta Materialia, 133, 100â108.

Authors 3

Joshua A. Gomberg (first)
Andrew J. Medford (additional)
Surya R. Kalidindi (additional)

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Dates

Type	When
Created	8 years, 3 months ago (May 23, 2017, 3:28 p.m.)
Deposited	3 years, 4 months ago (April 10, 2022, 9:40 a.m.)
Indexed	4 weeks, 1 day ago (Aug. 2, 2025, 1:16 a.m.)
Issued	8 years, 1 month ago (July 1, 2017)
Published	8 years, 1 month ago (July 1, 2017)
Published Print	8 years, 1 month ago (July 1, 2017)

Funders 1

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
Awards1
1. 70NANB14H191

BibTeX

@article{Gomberg_2017, title={Extracting knowledge from molecular mechanics simulations of grain boundaries using machine learning}, volume={133}, ISSN={1359-6454}, url={http://dx.doi.org/10.1016/j.actamat.2017.05.009}, DOI={10.1016/j.actamat.2017.05.009}, journal={Acta Materialia}, publisher={Elsevier BV}, author={Gomberg, Joshua A. and Medford, Andrew J. and Kalidindi, Surya R.}, year={2017}, month=jul, pages={100–108} }

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