rxnSMILES4AtomEco: Teaching Atom Economy with Reaction SMILES
Summary
This Learning Object introduces rxnSMILES4AtomEco, a computational tool for calculating atom economy (AE) using reaction SMILES. It includes Jupyter notebooks with examples (e.g., acetone synthesis) to enhance green chemistry education. Educators can use it to teach AE metrics and process design, fostering sustainability in curricula.
Article abstract: 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.
Full citation: Bridging Education and Process Design with Atom Economy via Reaction SMILES by
Samuele Giani and Simone Baffelli. Journal of Chemical Education 2025 102 (8), 3436-3442
DOI: 10.1021/acs.jchemed.5c00296
Article abstract: 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.
Full citation: Bridging Education and Process Design with Atom Economy via Reaction SMILES by
Samuele Giani and Simone Baffelli. Journal of Chemical Education 2025 102 (8), 3436-3442
DOI: 10.1021/acs.jchemed.5c00296
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