KrononosFE/kronos-2026-2-38-mlip-discovery-pipeline
The Materials-Discovery Pipeline - Activation as a First-Class Filter Authors: Ford, P. I. Summary The method behind the low-activation alloy family: a three-stage GPU pipeline — a universal ML interatomic potential (CHGNet) screens thousands of compositions by formation energy, density-functional theory confirms the survivors, and an activation-transport down-select (OpenMC→FISPACT) rejects any whose waste class or decay heat is unacceptable. The novelty is… See the full description on the dataset page: https://huggingface.co/datasets/KrononosFE/kronos-2026-2-38-mlip-discovery-pipeline.
The Materials-Discovery Pipeline - Activation as a First-Class Filter
Authors: Ford, P. I.
Summary
The method behind the low-activation alloy family: a three-stage GPU pipeline — a universal ML interatomic potential (CHGNet) screens thousands of compositions by formation energy, density-functional theory confirms the survivors, and an activation-transport down-select (OpenMC→FISPACT) rejects any whose waste class or decay heat is unacceptable. The novelty is making activation a first-class filter, early.
Canonical records
- Zenodo (canonical DOI): https://doi.org/10.5281/zenodo.22132229
- Figshare DOI: https://doi.org/10.6084/m9.figshare.33361470
- Publisher: Kronos Fusion Energy — 2026 Physics De-Risking series
What's in this repository
*_Editorial_2026.pdf— the editorial edition of the paper.*_reproducibility_bundle.zip— the reproducibility bundle: toolkit source, the per-gate runs the paper cites, and a student pack (concept notes, tutorial, glossary,reproduce.ipynb,requirements.txt).
Reproduce
unzip *_reproducibility_bundle.zip -d bundle && cd bundle
pip install -r requirements.txt
jupyter notebook reproduce.ipynbScope
Physics and engineering only; no economics. Every quantity traces to a documented gate in the KRONOS de-risking register. Honest gates are stated in the paper.