Research record
Project overview
Build and train atomistic neural networks to predict molecular or material potential-energy surfaces and related properties.
Catalog editorial description
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editor · 2026-09-18 — Catalog classification and summary; not maintainer acknowledgement.
Research classification
Chemical sciences · Physical sciences
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editor · 2026-09-18 — 分子与材料势能面及量子化学性质预测，建议化学和物理科学。
Research question
Not supplied. The repository description is not treated as a formal research question.
Sources & versions
- Reference role
- primary
- Last successful public check
- 2026-09-22T08:38:14.276Z
- Latest public check attempt
- 2026-09-22T08:38:14.276Z · ok
- GitHub metrics
- Stars 941 · checked · latest attempt 2026-09-22T08:38:14.276Z (ok)
Forks 251 · checked · latest attempt 2026-09-22T08:38:14.276Z (ok) - Latest default-branch commit
- Unknown
- Source activity check
- missing · last successful check unknown · latest attempt 2026-09-22T08:38:14.276Z (unavailable)
- Source status
- Active at last observation
- License
- Unknown — check the source terms
- Fixed commit
- Not available
Default-branch activity is separate from the fixed reference above. Source terms apply. A fixed commit identifies content; it does not establish scientific validity.
Related research
Tool
SchNetPack tool
Build and train atomistic neural networks to predict molecular or material potential-energy surfaces and related properties.
Claims & evidence
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Research questions and code contributions belong with the original project. Catalog corrections can be proposed separately.