Essential principles of statistical mechanics: statistical ensembles, thermodynamic averages, fluctuations, structrual quantities, time correlation functions and transport coefficients [8 Lectures]
Monte Carlo simulations: Metropolis algorithm in various ensembles, free energy calculations, configuration bias MC, reverse Monte Carlo, lattice Monte Carlo simulations [10 Lectures]
Molecular Dynamics: numerical algorithms to solve equation of motion, unconstraint and constrained dynamics (GROMACS package) [10 Lectures]
Brownian dynamics: over-damped dynamics (no hydrodynamics) [3 Lectures]
Applications: case studies on phase-equilibria, adsorption of polymers and surfactants of surfaces/interfaces, transport property calculations (diffusivity, viscosity), phase-behavior of self-propelling colloids, self-assembly of surfactants and patchy colloids. [7 Lectures]
Computer Simulation of Liquids, M. P. Allen., D. J. Tildesley, Oxford University Press, 1989.
Understanding Molecular Simulation, D. Frankel, B. Smit, Academic Press, 2001.
Molecular Modeling: Principles and Applications, 2nd Ed., A. Leach, Prentice Hall, 2001.
The Art of Molecular Dynamic Simulation, 2nd Ed., D. C. Rapaport, Cambridge University Press, 2004.
Introduction to Modern Statistical Mechanics, D. Chandler, Oxford University Press, 1987.
Introduction to Computational Chemistry, 2nd Ed., F. Jensen, Wiley, 2007.
Molecular Modeling Basics, J. H. Jensen, CRC Press, 2010.