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Interactive Quantum Chemistry Enabled by Machine Learning, Graphical Processing Units, and Cloud Computing.
Raucci, Umberto; Weir, Hayley; Sakshuwong, Sukolsak; Seritan, Stefan; Hicks, Colton B; Vannucci, Fabio; Rea, Francesco; Martínez, Todd J.
Affiliation
  • Raucci U; Stanford PULSE Institute, SLAC National Accelerator Laboratory, Menlo Park, California, USA.
  • Weir H; Department of Chemistry, Stanford University, Stanford, California, USA; email: Todd.Martinez@stanford.edu.
  • Sakshuwong S; Current affiliation: Italian Institute of Technology, Genova, Italy.
  • Seritan S; Stanford PULSE Institute, SLAC National Accelerator Laboratory, Menlo Park, California, USA.
  • Hicks CB; Department of Chemistry, Stanford University, Stanford, California, USA; email: Todd.Martinez@stanford.edu.
  • Vannucci F; Department of Management Science and Engineering, Stanford University, Stanford, California, USA.
  • Rea F; Stanford PULSE Institute, SLAC National Accelerator Laboratory, Menlo Park, California, USA.
  • Martínez TJ; Department of Chemistry, Stanford University, Stanford, California, USA; email: Todd.Martinez@stanford.edu.
Annu Rev Phys Chem ; 74: 313-336, 2023 Apr 24.
Article in En | MEDLINE | ID: mdl-36750410
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Annu Rev Phys Chem Year: 2023 Document type: Article Affiliation country: United States Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Annu Rev Phys Chem Year: 2023 Document type: Article Affiliation country: United States Country of publication: United States