Safe-and-Sustainable-by-Design and Digital Innovation Convergence for Pollution Mitigation: A Transformative Framework for Next-Generation Green Chemistry and Circular Materials Policy
DOI:
https://doi.org/10.64229/ewv1hy28Keywords:
Green chemistry, Safe-and-Sustainable-by-Design, Digital toxicity prediction, Sustainable catalysis, Circular economyAbstract
This review highlights the emerging convergence of artificial intelligence (AI), green chemistry, and Safe-and-Sustainable-by-Design (SSbD) principles as a strategic pathway for reducing pollution and accelerating circular manufacturing. By embedding sustainability attributes including safety, degradability, and material circularity at the earliest stages of molecular and process design, industries can shift from reactive environmental control to proactive risk prevention. AI-based predictive tools such as quantitative structure-activity relationship (QSAR) modeling, reaction optimization algorithms, and life-cycle decision systems are already improving hazard identification, solvent substitution, and waste minimization. Despite these advances, critical gaps remain. Scalable low-carbon catalytic systems are constrained by resource limitations and kinetic inefficiencies, while the absence of standardized SSbD indicators and interoperable digital infrastructures hinders cross-sector comparability. Moreover, limited integration of AI-derived toxicity predictions with techno-economic and life-cycle assessments (LCA) introduces uncertainty in regulatory translation. To address these challenges, future research should prioritize bioinspired catalysts, quantifiable degradation metrics, and AI-LCA hybrid models that couple circularity with safety by design. Strengthening ethical AI governance, transparent data practices, and global collaboration particularly in developing economies will be essential to ensure equitable and responsible technological adoption. Collectively, these advancements position the AI-SSbD-green chemistry nexus as a constructive and tangible route toward evidence-based, regenerative, and resilient industrial ecosystems.
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