Statistical Thermodynamics and Stochastic Kinetics

Statistical Thermodynamics and Stochastic Kinetics : An Introduction for Engineers

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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 more

Product details

  • Electronic book text
  • Cambridge University Press (Virtual Publishing)
  • Cambridge, United Kingdom
  • English
  • 79 b/w illus. 6 tables 106 exercises
  • 1139015559
  • 9781139015554

Review quote

"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 2012show more

Table of contents

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 more