Umberto Raucci, Hayley Weir, Sukolsak Sakshuwong, Stefan Seritan, Colton B Hicks, Fabio Vannucci, Francesco Rea, Todd J Martínez
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Interactive Quantum Chemistry Enabled by Machine Learning, Graphical Processing Units, and Cloud Computing.
Modern quantum chemistry algorithms are increasingly able to accurately predict molecular properties that are useful for chemists in research and education. Despite this progress, performing such calculations is currently unattainable to the wider chemistry community, as they often require domain expertise, computer programming skills, and powerful computer hardware. In this review, we outline methods to eliminate these barriers using cutting-edge technologies. We discuss the ingredients needed to create accessible platforms that can compute quantum chemistry properties in real time, including graphical processing units-accelerated quantum chemistry in the cloud, artificial intelligence-driven natural molecule input methods, and extended reality visualization. We end by highlighting a series of exciting applications that assemble these components to create uniquely interactive platforms for computing and visualizing spectra, 3D structures, molecular orbitals, and many other chemical properties.
期刊介绍:
The Annual Review of Physical Chemistry has been published since 1950 and is a comprehensive resource for significant advancements in the field. It encompasses various sub-disciplines such as biophysical chemistry, chemical kinetics, colloids, electrochemistry, geochemistry and cosmochemistry, chemistry of the atmosphere and climate, laser chemistry and ultrafast processes, the liquid state, magnetic resonance, physical organic chemistry, polymers and macromolecules, and others.