AIMNet2-rxn: A machine-learned potential for generalized reaction modeling on a millions-of-pathways scale
Dylan M. Anstine; Qiyuan Zhao; R.I. Zubatyuk; Shuhao Zhang; Veerupaksh Singla; Filipp Nikitin; Brett Matthew Savoie; Olexandr Isayev · 2026 · Science Advances
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Mechanistic modeling of chemical transformations offers a compelling basis for understanding reactivity and allows for prediction of reaction outcomes before attempting experiments. Despite progress in machine-learned interatomic…
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Metadata source: OpenAlex · DOI 10.1126/sciadv.aea1557