Caltech’s OrbNet deep learning tool outperforms state-of-the-art solutions.
Artificial intelligence (AI) machine learning is being applied to help accelerate the complex science of quantum mechanics—the branch of physics that studies matter and light on the subatomic scale. Recently a team of scientists at the California Institute of Technology (Caltech) published a breakthrough study in The Journal of Chemical Physics that unveils a new machine learning tool called OrbNet that can perform quantum chemistry computations 1,000 times faster than existing state-of-the-art solutions.
“We demonstrate the performance of the new method for the prediction of molecular properties, including the total and relative conformer energies for molecules in range of datasets of organic and drug-like molecules,” wrote the researchers.
Quantum chemistry is the scientific study that combines chemistry and physics. Also known as molecular quantum dynamics, quantum chemistry is a subset of chemistry that studies the properties and behavior of molecules at the subatomic level through the lens of quantum mechanics.
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