Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2510.21756 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866914113661173760 |
|---|---|
| author | Fonari, Alexandr Fallah, Farshad Rauch, Michael |
| author_facet | Fonari, Alexandr Fallah, Farshad Rauch, Michael |
| contents | The use of several open source scientific packages in the Schrödinger Materials Science Suite will be discussed. A typical workflow for materials discovery will be described, discussing how open source packages have been incorporated at every stage. Some recent implementations of machine learning for materials discovery will be discussed, as well as how open source packages were leveraged to achieve results faster and more efficiently. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_21756 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Utilizing SciPy and other open source packages to provide a powerful API for materials manipulation in the Schrödinger Materials Suite Fonari, Alexandr Fallah, Farshad Rauch, Michael Computational Physics Materials Science The use of several open source scientific packages in the Schrödinger Materials Science Suite will be discussed. A typical workflow for materials discovery will be described, discussing how open source packages have been incorporated at every stage. Some recent implementations of machine learning for materials discovery will be discussed, as well as how open source packages were leveraged to achieve results faster and more efficiently. |
| title | Utilizing SciPy and other open source packages to provide a powerful API for materials manipulation in the Schrödinger Materials Suite |
| topic | Computational Physics Materials Science |
| url | https://arxiv.org/abs/2510.21756 |