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.

Automated summary

This article outlines methods to eliminate the barriers preventing the wider chemistry community from performing quantum chemistry calculations. These methods include GPU-accelerated quantum chemistry in the cloud, AI-driven natural molecule input methods, and extended reality visualization. The article also highlights the exciting applications of these methods in computing and visualizing spectra, 3D structures, molecular orbitals, and other chemical properties.