Researchers at Yokohama National University have utilized machine learning and AI to predict the molecular selectivity of chemical reactions, specifically nucleophilic additions to cyclic ketones. By combining AI with chemical knowledge, they analyzed sterics and orbitals to determine how these factors influence reaction outcomes. Their study demonstrated the ability to predict reaction selectivity, enhancing the efficiency of chemical synthesis processes. This approach aims to streamline the development of pharmaceuticals and natural products.
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