Machine learning workflow for analysis of high-dimensional order parameter space: A case study of polymer crystallization from molecular dynamics simulations.
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| Title: | Machine learning workflow for analysis of high-dimensional order parameter space: A case study of polymer crystallization from molecular dynamics simulations. |
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| Authors: | Tourani E; Materials Research and Innovation Laboratory, Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, Tennessee 37996, USA., Edwards BJ; Materials Research and Innovation Laboratory, Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, Tennessee 37996, USA., Khomami B; Materials Research and Innovation Laboratory, Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, Tennessee 37996, USA. |
| Source: | The Journal of chemical physics [J Chem Phys] 2025 Oct 28; Vol. 163 (16). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: American Institute of Physics Country of Publication: United States NLM ID: 0375360 Publication Model: Print Cited Medium: Internet ISSN: 1089-7690 (Electronic) Linking ISSN: 00219606 NLM ISO Abbreviation: J Chem Phys Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1089-7690 |
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| DOI: | 10.1063/5.0292454 |
