Statistical Thermodynamics and Stochastic Kinetics
An Introduction for Engineers
$76.00 ( ) USD
- Author: Yiannis N. Kaznessis, University of Minnesota
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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 concepts of entropy and free energy, emphasizing key ideas used in equilibrium applications, whilst stochastic processes, such as stochastic reaction kinetics, are also covered. It provides a classical microscopic interpretation of thermodynamic properties, which is key for engineers, rather than focusing on more esoteric concepts of statistical mechanics 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.Read more
- Provides engineers with the knowledge they need to apply thermodynamics and solve engineering challenges
- Covers entropy and free energy, focusing on key concepts used in applications
- Includes many worked examples and over 100 end-of-chapter exercises
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"Incorporating many worked examples and more than 100 end-of-chapter exercises, the book should be valuable for classroom learning as well as for self-study" - Chemical Engineering Progress, April 2012
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- Date Published: March 2012
- format: Adobe eBook Reader
- isbn: 9781139180542
- contains: 79 b/w illus. 6 tables 106 exercises
- availability: This item is not supplied by Cambridge University Press in your region. Please contact eBooks.com for availability.
Table of Contents
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
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.
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