Please use this identifier to cite or link to this item:
Volltext verfügbar? / Dokumentlieferung
doi:10.22028/D291-48363 | Title: | Predicting Newtonian viscosity using machine learning trained on equilibrium molecular dynamics |
| Author(s): | Gao, Hongyu Honecker, Marc |
| Language: | English |
| Title: | The Journal of Chemical Physics |
| Volume: | 164 |
| Issue: | 1 |
| Publisher/Platform: | AIP |
| Year of Publication: | 2026 |
| DDC notations: | 500 Science |
| Publikation type: | Journal Article |
| DOI of the first publication: | 10.1063/5.0307668 |
| URL of the first publication: | https://doi.org/10.1063/5.0307668 |
| Link to this record: | urn:nbn:de:bsz:291--ds-483631 hdl:20.500.11880/42290 http://dx.doi.org/10.22028/D291-48363 |
| ISSN: | 1089-7690 0021-9606 |
| Date of registration: | 27-Jul-2026 |
| Faculty: | NT - Naturwissenschaftlich- Technische Fakultät |
| Department: | NT - Materialwissenschaft und Werkstofftechnik |
| Professorship: | NT - Prof. Dr. Martin Müser |
| Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Files for this record:
There are no files associated with this item.
Items in SciDok are protected by copyright, with all rights reserved, unless otherwise indicated.