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The 2024 Nobel Prize in chemistry has been awarded to a trio of scientists who used artificial intelligence to “crack the code” of almost all known proteins, the “chemical tools of life.”
Peter V. Coveney is a British chemist who is Professor of Physical Chemistry, Honorary Professor of Computer Science, and the Director of the Centre for Computational Science (CCS) [2] and Associate Director of the Advanced Research Computing Centre at University College London (UCL).
Physical chemistry is the study of macroscopic and microscopic phenomena in chemical systems in terms of the principles, practices, and concepts of physics such as motion, energy, force, time, thermodynamics, quantum chemistry, statistical mechanics, analytical dynamics and chemical equilibria.
Computational chemistry is a branch of chemistry that uses computer simulations to assist in solving chemical problems. [1] It uses methods of theoretical chemistry incorporated into computer programs to calculate the structures and properties of molecules , groups of molecules, and solids. [ 2 ]
Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).
Alán Aspuru-Guzik is a professor of chemistry, computer science, chemical engineering and materials science at the University of Toronto. [1] His research group, the matter lab, studies quantum chemistry, AI for chemical and materials discovery, quantum computing and self-driving chemical. [2]
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