## Statistical mechanics: fundamentals and modern applicationsThis book examines the latest developments in statistical mechanics, a branch of physical chemistry and physics that uses statistical techniques to predict the properties and the behavior of chemical and physical systems. It begins with a review of some of the essential concepts and then discusses recent developments in both equilibrium and nonequilibrium statistical mechanics. It covers liquids, phase transitions, renormalization theory, Monte Carlo techniques, and chaos. |

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Page 213

9.2 NATURE OF BROWNIAN MOTION In the case of pollen grains suspended in

water, the water molecules are ... way, it should be possible to relate macroscopic

properties such as viscosity to random displacements of a

9.2 NATURE OF BROWNIAN MOTION In the case of pollen grains suspended in

water, the water molecules are ... way, it should be possible to relate macroscopic

properties such as viscosity to random displacements of a

**Brownian particle**.Page 218

It is this requirement on the motion of the

process irreversible. The assumption that there exist space and time intervals £

and t small enough for the derivatives to exist and large enough for the validity of

...

It is this requirement on the motion of the

**Brownian particle**that renders theprocess irreversible. The assumption that there exist space and time intervals £

and t small enough for the derivatives to exist and large enough for the validity of

...

Page 220

To answer these questions, we turn to diffusion or Brownian motion under gravity,

just as Einstein did in his 1906 paper (Einstein, 1956, p. 19). 9.4.3

To answer these questions, we turn to diffusion or Brownian motion under gravity,

just as Einstein did in his 1906 paper (Einstein, 1956, p. 19). 9.4.3

**Brownian****Particle**in a Gravitational Field Consider a particle of mass m suspended in a ...### What people are saying - Write a review

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### Contents

Classical Statistical Mechanics | 3 |

Quantum Statistical Mechanics | 45 |

Phase Transitions and Critical Phenomena | 83 |

Copyright | |

14 other sections not shown

### Common terms and phrases

attractor automata average behavior bifurcation Boltzmann Boltzmann equation Brownian motion Brownian particle BZ reaction calculate called canonical ensemble cell cellular automaton chaos Chapter coefficient collisions configuration consider coordinates correlation functions coupling constants critical exponents critical point defined depends derivation dimension discussed distribution function dynamics eigenvalues entropy equilibrium evaluated example ferromagnetic fixed point fluctuations fluid FORTRAN FORTRAN program fractal free energy frequency Gaussian Hamiltonian initial integral interactions Ising model iterations Kramers Langevin equation lattice limit cycle linear magnetization Markovian matrix method microcanonical ensemble microstates molecular nonequilibrium nonlinear number of particles obtained one-dimensional order parameter oscillations partition function Pathria phase space phase transition polymer potential power spectrum probability density problem protein quantities quantum mechanics RANDOM NUMBER random walk scaling Section shown in Figure simulation solution spin glass statistical mechanics steps stochastic temperature theorem thermodynamic limit total number values vector velocity zero