Neural Networks In Chemical Reaction Dynamics Hardcover 1st
Recommend
Sort by
Rating
Date
Specifications
Author 1
Lionel Raff
Book Description
This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic potential functions using NNs; (v) self-starting methods for obtaining analytic PES from ab inito electronic structure calculations using direct dynamics; (vi) development of a novel method, namely, combined function derivative approximation (CFDA) for simultaneous fitting of a PES and its corresponding force fields using feedforward neural networks; (vii) development of generalized PES using many-body expansions, NNs, and moiety energy approximations; (viii) NN methods for data analysis, reaction probabilities, and statistical error reduction in chemical reaction dynamics; (ix) accurate prediction of higher-level electronic structure energies (e.g. MP4 or higher) for large databases using NNs, lower-level (Hartree-Fock) energies, and small subsets of the higher-energy database; and finally (x) illustrative examples of NN applications to chemical reaction dynamics of increasing complexity starting from simple near equilibrium structures (vibrational state studies) to more complex non-adiabatic reactions. The monograph is prepared by an interdisciplinary group of researchers working as a team for nearly two decades at Oklahoma State University, Stillwater, OK with expertise in gas phase reaction dynamics; neural networks; various aspects of MD and Monte Carlo (MC) simulations of nanometric cutting, tribology, and material properties at nanoscale; sc
ISBN-10
0199765650
ISBN-13
9780199765652
Language
English
Publisher
Oxford University Press
Publication Date
1-Jan-2012
Number of Pages
300
About the Author
Lionel Raff is Regents Professor in the Department of Chemistry at Oklahoma State University. Ranga Komanduri is Professor & A. H. Nelson, Jr. Endowed Chair in Engineering in the School of Mechanical and Aerospace Engineering at Oklahoma State University. Martin Hagan is Professor in the School of Electrical and Computer Engineering, Oklahoma State University Satish Bukkapatnam is Assistant Professor in the School of Industrial Engineering and Management at Oklahoma State University.
Edition Number
1st