A novel machine learning tool can calculate how much energy is needed to make or break a molecule with greater accuracy than conventional means, according to a new study published Tuesday in the journal Nature Communications.
As of yet, the tool can only work with simple molecules, but it carves a path to future advances in quantum chemistry.
"Using machine learning to solve the fundamental equations governing quantum chemistry has been an open problem for several years, and there's a lot of excitement around it right now," said co-creator Giuseppe Carleo, a research scientist at the New-York-City-based Flatiron Institute's Center for Computational Quantum Physics. A greater understanding of the creation and destruction of molecules could be, according to Carleo, a way to unveil the inner workings of the chemical reactions crucial for life.
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