Breakthrough Reported in Machine Learning-Enhanced Quantum Chemistry (IMAGE)
Caption
The model’s structure. A neural network processes a molecular geometry to predict a semi-empirical quantum Hamiltonian, which is then solved self-consistently to predict a variety of chemical properties.
Credit
Image courtesy of Kipton Barros, Los Alamos National Laboratory.
Usage Restrictions
Image courtesy of Kipton Barros, Los Alamos National Laboratory.
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Original content