Annual Review of Physical Chemistry, volume 74, issue 1, pages 313-336

Interactive Quantum Chemistry Enabled by Machine Learning, Graphical Processing Units, and Cloud Computing

Publication typeJournal Article
Publication date2023-04-24
scimago Q1
wos Q1
SJR4.696
CiteScore28.0
Impact factor11.7
ISSN0066426X, 15451593
Physical and Theoretical Chemistry
Abstract

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.

Expected final online publication date for the Annual Review of Physical Chemistry, Volume 74 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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