MatOpt: A Python Package for Nanomaterials Design Using Discrete Optimization

Christopher L. Hanselman, Xiangyu Yin, David C. Miller, Chrysanthos E. Gounaris

Open source

DOI: 10.1021/acs.jcim.1c00984
Published: 2022-01-13
Container: Journal of Chemical Information and Modeling
Publisher: American Chemical Society (ACS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1021/acs.jcim.1c00984,
  title = {MatOpt: A Python Package for Nanomaterials Design Using Discrete Optimization},
  author = {Christopher L. Hanselman and Xiangyu Yin and David C. Miller and Chrysanthos E. Gounaris},
  year = {2022},
  journal = {Journal of Chemical Information and Modeling},
  doi = {10.1021/acs.jcim.1c00984},
  url = {https://doi.org/10.1021/acs.jcim.1c00984}
}

RIS

TY  - JOUR
TI  - MatOpt: A Python Package for Nanomaterials Design Using Discrete Optimization
AU  - Christopher L. Hanselman
AU  - Xiangyu Yin
AU  - David C. Miller
AU  - Chrysanthos E. Gounaris
PY  - 2022
JO  - Journal of Chemical Information and Modeling
DO  - 10.1021/acs.jcim.1c00984
UR  - https://doi.org/10.1021/acs.jcim.1c00984
ER  -

APA

Hanselman, C. L., Yin, X., Miller, D. C., & Gounaris, C. E. (2022). MatOpt: A Python Package for Nanomaterials Design Using Discrete Optimization. Journal of Chemical Information and Modeling. https://doi.org/10.1021/acs.jcim.1c00984

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crossref · retrieved 2026-09-25T11:56:29.359Z