Modern Materials Design Advances
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Materials sciencePhys Org
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Science
Computational chemistry method can wring more information out of electronic structure calculations
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Machine-learning tools have boosted our capacity to determine the structure and physical properties of molecules and substances.
Ju Li's MIT team trains a new machine-learning model that can reveal properties of not only ground states, but also excited states.
CCSD(T) calculations are much more accurate than what you get from quantum mechanics.
The MIT -based group applied their model first to small, nonmetallic elements.
After being trained on small molecules, the model can be generalized to bigger and bigger molecules.
The examination of heavier transition metal elements could lead to the advent of new materials for batteries.
Once they demonstrate the ability to analyze large molecules with perhaps tens of thousands of atoms.