Bridging Education and Process Design with Atom Economy via Reaction SMILES

Green chemistry demands efficient, sustainable chemical processes, yet atom economy (AE) calculations often rely on tedious, error-prone manual methods, limiting their educational and practical use. We introduce rxnSMILES4AtomEco, a Python module which computes atom economy from reaction SMILES using RDKit, paired with https://mybinder.org Jupyter Notebooks for easy accessibility. This tool assesses elementary, simple reactions and composite, stepwise reactions, exemplified by acetone synthesis, spanning cumene decomposition (38.2% AE), isopropanol dehydrogenation (96.6% AE), and propene oxidation (100.0% AE), and ibuprofen synthesis, contrasting Boots company wasteful six-step route (40.1% AE) with BHC company efficient three-step process (77.5% AE), visualized for intuitive learning and optimization. For educators, rxnSMILES4AtomEco supports classrooms teaching of green chemistry and cheminformatics (e.g., SMILES generation and parsing) hands-on with no software setup required, whereas, for process designers, it streamlines sustainable pathway optimization. The AE calculation used in this tool, however, excludes chemical yield: future enhancements could integrate yield data, enhancing real-world applicability.