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Scientists are using deep learning methods to predict material properties and optimize synthesis conditions. In a recent study, researchers from Tokyo University of Science used deep learning to predict single-molecule magnets from a pool of 20,000 metal complexes. This approach streamlines the material discovery process and has potential applications in various fields.
