Bonding’s next top model — Projecting bond properties with machine learning

(Institute of Industrial Science, The University of Tokyo) Researchers from The University of Tokyo Institute of Industrial Science have developed a machine learning-based model to predict the characteristics of bonded systems. Using the density of states of the individual component reactants, they have achieved accurate predictions of the binding energy, bond length, number of covalent electrons, and Fermi energy. The broadly applicable model is expected to make a significant contribution to the development of materials such as catalysts and nanowires.

​(Institute of Industrial Science, The University of Tokyo) Researchers from The University of Tokyo Institute of Industrial Science have developed a machine learning-based model to predict the characteristics of bonded systems. Using the density of states of the individual component reactants, they have achieved accurate predictions of the binding energy, bond length, number of covalent electrons, and Fermi energy. The broadly applicable model is expected to make a significant contribution to the development of materials such as catalysts and nanowires. 

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