Statistical Thermodynamics and Stochastic Kinetics: An Introduction for Engineers

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.

[1]  J. Rawlings,et al.  Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics , 2002 .

[2]  Yiannis N Kaznessis,et al.  An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks. , 2005, The Journal of chemical physics.

[3]  W. Mendenhall,et al.  Statistics for engineering and the sciences , 1984 .

[4]  D. Gillespie.  Markov Processes: An Introduction for Physical Scientists , 1991 .

[5]  S. Edwards,et al.  The Theory of Polymer Dynamics , 1986 .

[6]  D. Chandler,et al.  Introduction To Modern Statistical Mechanics , 1987 .

[7]  J. Hammersley,et al.  Monte Carlo Methods , 1965 .

[8]  J. Gibbs.  Elementary Principles in Statistical Mechanics , 1902 .

[9]  J. Hildebrand,et al.  The Distribution of Molecules in a Model Liquid , 1936 .

[10]  C. W. Gardiner,et al.  Handbook of stochastic methods - for physics, chemistry and the natural sciences, Second Edition , 1986, Springer series in synergetics.

[11]  J. Smith,et al.  Introduction to chemical engineering thermodynamics , 1949 .

[12]  I. Z. Fisher,et al.  Statistical theory of liquids , 1964 .

[13]  N. Kampen,et al.  Stochastic processes in physics and chemistry , 1981 .

[14]  H. Risken.  Fokker-Planck Equation , 1984 .

[15]  Dirk P. Kroese,et al.  Simulation and the Monte Carlo method , 1981, Wiley series in probability and mathematical statistics.

[16]  Horia Metiu.  Physical Chemistry: Thermodynamics , 2006 .

[17]  J. McConnell,et al.  Rotational Brownian motion and dielectric theory , 1980 .

[18]  Hong Li,et al.  Efficient formulation of the stochastic simulation algorithm for chemically reacting systems. , 2004, The Journal of chemical physics.

[19]  T. Kawakatsu,et al.  Statistical Physics of Polymers , 2004 .

[20]  H. Ted Davis,et al.  Statistical Mechanics of Phases, Interfaces and Thin Films , 1996 .

[21]  John D. Simon,et al.  Physical chemistry : a molecular approach , 1997 .

[22]  Vassilios Sotiropoulos,et al.  Multiscale Hy3S: Hybrid stochastic simulation for supercomputers , 2006, BMC Bioinformatics.

[23]  Daniel T Gillespie,et al.  Stochastic simulation of chemical kinetics. , 2007, Annual review of physical chemistry.

[24]  P. Gennes.  Scaling Concepts in Polymer Physics , 1979 .

[25]  K. Binder,et al.  The Monte Carlo Method in Condensed Matter Physics , 1992 .

[26]  A. Kierzek,et al.  Bridging the gap between stochastic and deterministic regimes in the kinetic simulations of the biochemical reaction networks. , 2004, Biophysical journal.

[27]  D. Ter Haar,et al.  Elements of Statistical Mechanics , 1954 .

[28]  Howard M. Salis,et al.  Numerical simulation of stochastic gene circuits , 2005, Comput. Chem. Eng..

[29]  Berend Smit,et al.  Understanding molecular simulation: from algorithms to applications , 1996 .

[30]  Frank C. Andrews,et al.  Equilibrium Statistical Mechanics , 1963 .

[31]  C. W. Gear,et al.  Numerical initial value problem~ in ordinary differential eqttations , 1971 .

[32]  S. Sandler.  Chemical and engineering thermodynamics , 1977 .

[33]  Horia Metiu.  Physical Chemistry: Statistical Mechanics , 2006 .

[34]  D. Griffiths,et al.  Introduction to Quantum Mechanics , 1960 .

[35]  C. Smyth.  LVI. A table of the beats, on Mr. William Hawkes's patent organs and piano-fortes, calculated by the Rev. C. J. Smyth; and communicated, with some remarks, by Mr. John Farey , 1811 .

[36]  D. Gillespie.  The chemical Langevin equation , 2000 .

[37]  L. Rayleigh.  XXXI. On the problem of random vibrations, and of random flights in one, two, or three dimensions , 1919 .

[38]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[39]  Ilya Prigogine,et al.  Non-equilibrium statistical mechanics , 1962 .

[40]  J. W. Humberston.  Classical mechanics , 1980, Nature.

[41]  A. Messiah.  Quantum Mechanics , 1961 .

[42]  Christophe Chipot,et al.  Free Energy Calculations , 2008 .

[43]  D. Gillespie.  A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions , 1976 .

[44]  P. Kloeden,et al.  Numerical Solution of Stochastic Differential Equations , 1992 .

[45]  M. Khammash,et al.  The finite state projection algorithm for the solution of the chemical master equation. , 2006, The Journal of chemical physics.

[46]  Berend Smit,et al.  Understanding Molecular Simulation , 2001 .

[47]  L. Girifalco.  Statistical mechanics of solids , 2000 .

[48]  J. Kirkwood,et al.  Theory of liquids , 1968 .

[49]  J. Banavar,et al.  Computer Simulation of Liquids , 1988 .

[50]  Michael A. Gibson,et al.  Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels , 2000 .

[51]  C. Rao,et al.  Stochastic chemical kinetics and the quasi-steady-state assumption: Application to the Gillespie algorithm , 2003 .

[52]  T. Ackermann.  Regular and Related Solutions , 1973 .

[53]  Ioannis G Kevrekidis,et al.  Gene regulatory networks: a coarse-grained, equation-free approach to multiscale computation. , 2005, The Journal of chemical physics.

[54]  R. Larson.  The Structure and Rheology of Complex Fluids , 1998 .

[55]  Richard L. Tweedie,et al.  Markov Chains and Stochastic Stability , 1993, Communications and Control Engineering Series.

[56]  J. Neumann.  Mathematical Foundations of Quantum Mechanics , 1955 .

[57]  Taro Yamane.  Statistics: An Introductory Analysis , 1965 .

[58]  Harvey Gould,et al.  Statistical and Thermal Physics , 2010 .