SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Stanford Univ., CA (United States); Italian Inst. of Technology (IIT) (Italy); SLAC
SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Stanford Univ., CA (United States)
Stanford Univ., CA (United States)
SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Stanford Univ., CA (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
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.
@article{osti_2006436,
author = {Raucci, Umberto and Weir, Hayley and Sakshuwong, Sukolsak and Seritan, Stefan and Hicks, Colton B. and Vannucci, Fabio and Rea, Francesco and Martínez, Todd J.},
title = {Interactive Quantum Chemistry Enabled by Machine Learning, Graphical Processing Units, and Cloud Computing},
annote = {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.},
doi = {10.1146/annurev-physchem-061020-053438},
url = {https://www.osti.gov/biblio/2006436},
journal = {Annual Review of Physical Chemistry},
issn = {ISSN 0066-426X},
number = {1},
volume = {74},
place = {United States},
publisher = {Annual Reviews},
year = {2023},
month = {02}}