Prediction of electron‐solid interaction parameters using machine learning
The developed model achieved high prediction accuracy for various target materials across the broad electron energy spectrum. The outcomes demonstrate the effectiveness of machine learning methodology and the chosen models' suitability for addressing substantial physics challenges.
Authors
- Fatemeh Akbari (ORCID: https://orcid.org/0000-0002-2654-8029)
Institutions
- Carleton University (CA)
- University of Toledo (US)
Publication Details
- Journal
- Medical Physics
- Published
- 2024-10-12
- DOI
- https://doi.org/10.1002/mp.17445
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00