alchemy: systematic enumeration and thermodynamic screening of small-molecule radical reaction networks
Year: 2026
Type: preprint
Abstract: Automated construction of chemical reaction networks is limited by the combinatorial growth of possible molecules, intermediates, and formal transformations. We present alchemy, an open-source Python workflow for systematic enumeration and screening of small-molecule radical reaction networks. Within an explicitly bounded graph space, alchemy generates connected, neutral C/N/H molecular graphs with single, double, or triple bonds and specified radical counts; RDKit sanitisation and canonicalisation then remove graph-invalid and duplicate records. Reaction candidates are constructed without learned reaction templates by combining bond-dissociation records into rearrangement and transfer stoichiometries. Parallel generation, disk-backed storage, machine-learning prediction of molecular Gibbs free energies, and Kuzu graph representation make the resulting formal network searchable. In a trimethylamine case study limited to at most five heavy atoms and one unpaired electron per reaction side, the workflow generated 41,735 unique molecular graphs and 60,035 first-generation radical-transfer records. A PaiNN model trained and tested on OpenBabel-generated QM9 geometries supplies rapid ranking scores, but QM9 contains no open-shell species and therefore cannot validate predictions for the radical chemistry enumerated here. alchemy therefore provides a reproducible route to efficient reaction-space enumeration while retaining practical filters for chemical plausibility and downstream mechanistic analysis.
Source: ChemRxiv
Institution: Deakin University
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7212030652