Skip to content

Booksellers & Trade Customers: Sign up for online bulk buying at trade.atlanticbooks.com for wholesale discounts

Booksellers: Create Account on our B2B Portal for wholesale discounts

Neural Networks in Chemical Reaction Dynamics

by Lionel Raff , Ranga Komanduri , Martin Hagan
Save 17% Save 17%
Current price ₹16,419.00
Original price ₹19,703.00
Original price ₹19,703.00
Original price ₹19,703.00
(-17%)
₹16,419.00
Current price ₹16,419.00

Imported Edition - Ships in 18-21 Days

Free Shipping in India on orders above Rs. 500

Request Bulk Quantity Quote
+91
Book cover type: Hardcover
  • ISBN13: 9780199765652
  • Binding: Hardcover
  • Subject: N/A
  • Publisher: Oxford University Press
  • Publisher Imprint: Oxford University Press
  • Publication Date:
  • Pages: 312
  • Original Price: GBP 115.0
  • Language: English
  • Edition: N/A
  • Item Weight: 567 grams
  • BISAC Subject(s): Chemistry / Physical & Theoretical

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

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.

Trusted for over 49 years

Family Owned Company

Secure Payment

All Major Credit Cards/Debit Cards/UPI & More Accepted

New & Authentic Products

India's Largest Distributor

Need Support?

Whatsapp Us