Machine learning aids in materials design

A long-held goal by chemists across many industries, including energy, pharmaceuticals, energetics, food additives and organic semiconductors, is to imagine the chemical structure of a new molecule and be able to predict ...

A machine learning model behind COVID-19 vaccine development

When starting a vaccine program, scientists generally have anecdotal understanding of the disease they're aiming to target. When COVID-19 surfaced over a year ago, there were so many unknowns about the fast-moving virus that ...

Machine learning aids in simulating dynamics of interacting atoms

A revolutionary machine-learning (ML) approach to simulate the motions of atoms in materials such as aluminum is described in this week's Nature Communications journal. This automated approach to "interatomic potential development" ...

Machine-learning models of matter beyond interatomic potentials

Combining electronic structure calculations and machine learning (ML) techniques has become a common approach in the atomistic modeling of matter. Using the two techniques together has allowed researchers, for instance, to ...

Machine learning boosts the search for 'superhard' materials

Superhard materials are in high demand in industry, from energy production to aerospace, but finding suitable new materials has largely been a matter of trial and error based on classical materials such as diamonds. Until ...

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