Book contents
- Frontmatter
- Contents
- Preface
- 1 Stochastic Simulation of Chemical Reactions
- 2 Deterministic versus Stochastic Modelling
- 3 Stochastic Differential Equations
- 4 Diffusion
- 5 Efficient Stochastic Modelling of Chemical Reactions
- 6 Stochastic Reaction–Diffusion Models
- 7 SSAs for Reaction–Diffusion–Advection Processes
- 8 Microscopic Models of Brownian Motion
- 9 Multiscale and Multi-Resolution Methods
- Appendix
- References
- Index
8 - Microscopic Models of Brownian Motion
Published online by Cambridge University Press: 04 November 2019
- Frontmatter
- Contents
- Preface
- 1 Stochastic Simulation of Chemical Reactions
- 2 Deterministic versus Stochastic Modelling
- 3 Stochastic Differential Equations
- 4 Diffusion
- 5 Efficient Stochastic Modelling of Chemical Reactions
- 6 Stochastic Reaction–Diffusion Models
- 7 SSAs for Reaction–Diffusion–Advection Processes
- 8 Microscopic Models of Brownian Motion
- 9 Multiscale and Multi-Resolution Methods
- Appendix
- References
- Index
Summary
This chapter presents microscopic models of diffusion (Brownian motion). The discussed diffusion models explicitly describe the dynamics of solvent molecules. Such molecular dynamics models provide many more details than the models discussed in Chapter 4 (which simply postulate that the diffusing molecule is subject to a random force) and can be used to assess the accuracy of the stochastic diffusion models from Chapter 4. The analysis starts with theoretical solvent models, including a simple “one-particle” description of the solvent (heat bath), which is used to introduce the generalized Langevin equation and the generalized fluctuation–dissipation theorem. Analytical insights are provided by theoretical models with short- and long-range interactions. The chapter concludes with less analytically tractable, but more realistic, computational models, introducing molecular dynamics (molecular mechanics) and applying it to the Lennard-Jones fluid and to simulations of ions in aquatic solutions.
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- Information
- Stochastic Modelling of Reaction–Diffusion Processes , pp. 226 - 267Publisher: Cambridge University PressPrint publication year: 2020