Statistical thermodynamics and stochastic kinetics
Subtitle: an introduction for engineers
By: Yiannis Nikolaos Kaznessis
Publisher: Cambridge University Press
Published: 2012
Place of publication: Cambridge; New York
Language: eng
ISBN-13: 9780521765619
Subjects: Stochastic processes; Simulation methods; Statistical thermodynamics; Molucular dynamics; TECHNOLOGY & ENGINEERING / Chemical & Biochemical
Description: "Presenting the key principles of thermodynamics from a microscopic point of view, this book provides engineers with the knowledge they need to apply thermodynamics and solve engineering challenges at the molecular level. It clearly explains the concerns of entropy and free energy, emphasising key concepts used in equilibrium applications, whilst stochastic processes, such as stochastic reaction kinetics, are also covered. It provides a classical microscopic interpretation of thermodynamic concepts which is key for engineers, rather than focusing on more esoteric concepts of statistical thermodynamics and quantum mechanics. Coverage of molecular dynamics and Monte Carlo simulations as natural extensions of the theoretical treatment of statistical thermodynamics is also included, teaching readers how to use computer simulations and thus enabling them to understand and engineer the microcosm. Featuring many worked examples and over 100 end-of-chapter exercises, it is ideal for use in the classroom as well as for self-study"--
Notes: Includes index.
Table of contents: title: Machine generated contents note: 1. Introduction; 2. Elements of probability and combinatorial theory; 3. From classical to quantum mechanics, and back; 4. Ensemble theory; 5. Canonical ensemble; 6. Fluctuations and other ensembles; 7. Molecules; 8. Non-ideal gases; 9. Liquids and crystals; 10. Beyond pure, single-component systems; 11. Polymers - Brownian dynamics; 12. Non-equilibrium thermodynamics; 13. Stochastic processes; 14. Molecular simulations; 15. Monte Carlo simulations; 16. Molecular dynamics simulations; 17. Analyzing simulation results; 18. Simulations of stochastic reaction kinetics.