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Quantum Chemistry in the Age of Machine Learning by Pavlo O. Dral (Pavlo O. Dral is Full Professor at Xiamen University, PR China.) at Abbey's Bookshop,
Quantum Chemistry in the Age of Machine Learning
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Pavlo O. Dral (Pavlo O. Dral is Full Professor at Xiamen University, PR China.) Pavlo O. Dral (Pavlo O. Dral is Associate Professor at Xiamen University, PR China.)

Quantum Chemistry in the Age of Machine Learning

Pavlo O. Dral (Pavlo O. Dral is Full Professor at Xiamen University, PR China.),  Pavlo O. Dral (Pavlo O. Dral is Associate Professor at Xiamen University, PR China.)

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English
Elsevier - Health Sciences Division
15 September 2022
Quantum & theoretical chemistry
Quantum chemistry is simulating atomistic systems according to the laws of quantum mechanics, and such simulations are essential for our understanding of the world and for technological progress. Machine learning revolutionizes quantum chemistry by increasing simulation speed and accuracy and obtaining new insights. However, for nonspecialists, learning about this vast field is a formidable challenge. Quantum Chemistry in the Age of Machine Learning covers this exciting field in detail, ranging from basic concepts to comprehensive methodological details to providing detailed codes and hands-on tutorials. Such an approach helps readers get a quick overview of existing techniques and provides an opportunity to learn the intricacies and inner workings of state-of-the-art methods. The book describes the underlying concepts of machine learning and quantum chemistry, machine learning potentials and learning of other quantum chemical properties, machine learning-improved quantum chemical methods, analysis of Big Data from simulations, and materials design with machine learning.

Drawing on the expertise of a team of specialist contributors, this book serves as a valuable guide for both aspiring beginners and specialists in this exciting field.
Edited by:   , ,
Imprint:   Elsevier - Health Sciences Division
Country of Publication:   United States
Dimensions:   Height: 229mm,  Width: 152mm, 
Weight:   1.400kg
ISBN:   9780323900492
ISBN 10:   0323900496
Pages:   698
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
1. Very brief introduction to quantum chemistry 2. Density functional theory 3. Semiempirical quantum mechanical methods 4. From small molecules to solid-state materials: A brief discourse on an example of carbon compounds 5. Basics of dynamics 6. Machine learning: An overview 7. Unsupervised learning 8. Neural networks 9. Kernel methods 10. Bayesian inference 11. Potentials based on linear models 12. Neural network potentials 13. Kernel method potentials 14. Constructing machine learning potentials with active learning 15. Excited-state dynamics with machine learning 16. Machine learning for vibrational spectroscopy 17. Molecular structure optimizations with Gaussian process regression 18. Learning electron densities 19. Learning dipole moments and polarizabilities 20. Learning excited-state properties 21. Learning from multiple quantum chemical methods: ?-learning, transfer learning, co-kriging, and beyond 22. Data-driven acceleration of coupled-cluster and perturbation theory methods 23. Redesigning density functional theory with machine learning 24. Improving semiempirical quantum mechanical methods with machine learning 25. Machine learning wavefunction 26. Analysis of nonadiabatic molecular dynamics trajectories 27. Design of organic materials with tailored optical properties: Predicting quantum-chemical polarizabilities and derived Quantities

Pavlo O. Dral is Full Professor at Xiamen University. He is a specialist in accelerating and improving quantum chemistry with artificial intelligence/machine learning. Together with his colleagues, he introduced and continues to develop methods such as ?-learning, AIQM1, fourdimensional spacetime atomistic artificial intelligence models, and artificial intelligence-based quantum dynamics. Pavlo Dral is also a founder of MLatom, a program package for atomistic machine learning, and a co-founder of the Xiamen Atomistic Computing Suite. His more than 40 publications were cited over 2800 times and his h-index is 22 (Google Scholar, Summer 2022). Pavlo O. Dral has won a gold medal in the 36th International Chemistry Olympiad, 2004. He did his PhD with Prof. Tim Clark at the University of Erlangen–Nuremberg in 2010–2013, postdoc with Prof. Walter Thiel at the Max Planck Institute for Coal Research in 2013–2019, and began his independent career at Xiamen University in 2019 first as an Associate Professor and from 2021 as a Full Professor. More information is available on Dral’s group website dr-dral.com.

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