Predicting Atomistic Transitions with Transformers
Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find these transitions are extremely computationally intensive. Even with large-scale, accelerated material si...
Bewaard in:
| Hoofdauteurs: | , , , , |
|---|---|
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Taylor & Francis Group
2026-12-01
|
| Reeks: | Data Science in Science |
| Onderwerpen: | |
| Online toegang: | https://www.tandfonline.com/doi/10.1080/26941899.2026.2685344 |
| Tags: |
Geen labels, Wees de eerste die dit record labelt!
|