Multiscale Dynamics Simulations

Nano and Nano-bio Systems in Complex Environments

Dennis R. Salahub (Redaktør) ; Dongqing Wei (Redaktør)

Over the past decade, great strides have been taken in developing methodologies that can treat more and more complex nano- and nano-bio systems embedded in complex environments.


Multiscale Dynamics Simulations covers methods including DFT/MM-MD, DFTB and semi-empirical QM/MM-MD, DFT/MMPOL as well as Machine-learning approaches to all of the above. Les mer
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Legg i
Vår pris: 3021,-

(Innbundet) Fri frakt!
Leveringstid: Sendes innen 21 dager

Om boka

Over the past decade, great strides have been taken in developing methodologies that can treat more and more complex nano- and nano-bio systems embedded in complex environments.


Multiscale Dynamics Simulations covers methods including DFT/MM-MD, DFTB and semi-empirical QM/MM-MD, DFT/MMPOL as well as Machine-learning approaches to all of the above. Focusing on key methodological breakthroughs in the field, this book provides newcomers with a comprehensive menu of multiscale modelling options so that they can better chart their course in the nano/bio world.

Fakta

Innholdsfortegnelse

QM/MM with Auxiliary DFT in deMon2k; Computational Enzymology: A Challenge for Multiscale Approaches; QM/MM Simulations of Proteins: Is Explicit Inclusion of Polarization on the Horizon?; Electron and Molecular Dynamics Simulations with Polarizable Embedding; DFTB and Hybrid-DFTB Schemes: Application to Metal Nanosystems, Isolated and in Environments; From Atomic Orbitals to Nano-scale Charge Transport with Mixed Quantum/Classical Non-adiabatic Dynamics: Method, Implementation and Application; Modeling Nanocatalytic Reactions with DFTB/MM-MD and DFTB/NMD; Hohenberg–Kohn Theorems as a Basis for Multi-scale Simulations: Frozen-density Embedding Theory; 3D-RISM-KH Molecular Solvation Theory; Free Energy Analysis Algorithms along Transition Paths and Transmembrane Ion Permeation; Pathways in Classification Space: Machine Learning as a Route to Predicting Kinetics of Structural Transitions in Atomic Crystals; Machine Learning Algorithms for the Analysis of Molecular Dynamics Trajectories

Om forfatteren

Dennis Salahub is a Professor of Chemistry, Emeritus at the University of Calgary. He is also Vice-President (Research and International) Emeritus following a 5-year term from 2002-2007. Prior to joining the University of Calgary, Dr. Salahub served as the Director General of the Steacie Institute for Molecular Sciences at the National Research Council of Canada in Ottawa from 1999 -2002. From 1976-1999, he was a Professor of Chemistry at the Université de Montréal, holding a McConnell Chair from 1990. A native of Alberta, Dr Salahub’s interests are in the field of theoretical and computational chemistry, especially in the theory and applications of Density Functional Theory. He has published over 330 research papers and four edited books and has delivered more than 500 invited lectures nationally and internationally. His work has been cited over 20 000 times and his World-of-Science H-index is 68. In 1998 he became a Fellow of the Royal Society of Canada, and in 2006 he was named a Fellow of the American Association for the Advancement of Science.


Dongqing Wei is a professor of Bioinformatics at Shanghai Jiaotong University and editor-in-chief of “Interdisciplinary Sciences- Computational Life Sciences”. Over the past three decades he has made many ground-breaking contributions to the development of AI and molecular simulation techniques and their interdisciplinary applications to systems of ever-increasing complexity. Published more than 350 papers, 9 monographs with 8000 SCI citations and an H -index of 55.