Machine learning helps solve a central problem of quantum chemistry
Phys.org
February 18, 2026
By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major breakthrough toward solving a decades-old dilemma in quantum chemistry: the precise and stable calculation of molecular energies and electron densities with a so-called orbital-free approach, which uses considerably less computational power and therefore permits calculations for very large molecules.
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Originally published on Phys.org on 2/18/2026