Machine Learning Applications in Designing Catalysts

Advancements in industrial chemistry, driven by innovations in catalysts and machine learning (ML), are revolutionizing industries, medicine, and environmental sustainability. ML accelerates catalyst discovery by identifying patterns and predicting outcomes, reducing reliance on costly trial-and-error methods. In enzyme engineering, ML enhances the precision and robustness of tailored biological catalysts, enabling applications in medicine and industry. Researchers are also developing alternatives to scarce, expensive precious metal catalysts, with breakthroughs in electrocatalysts showing promise for improving hydrogen fuel cells and clean energy storage. Additionally, catalytic processes are being explored to address the global plastic waste crisis by efficiently breaking down plastics, offering sustainable waste management solutions. These advancements position catalysts as key to solving critical challenges while promoting innovation and sustainability.