PCH235 MOLECULAR MODELING AND
SIMULATION 


L 
T 
P 
Cr 

3 
1 
0 
3.5 
Course Objective:
To
learn to mimic the real system and phenomena in virtual world using molecular
level information and computational resources and to develop and design the
novel performance chemicals and materials.
Introduction: Need
of molecular modelling and simulation, Postulates of
statistical mechanics, Ergodic hypothesis.
Statistical Ensembles and Partition Functions: System and particle partition function and relation to
thermodynamics, Microcanonical ensemble, Canonical ensemble,
Isothermalisobaric ensemble, Grandcanonical ensemble, Gibbs ensemble,
Thermodynamic equivalence of ensembles, Ensemble average and time average
equivalence.
Empirical Force Field Models: General features of
molecular mechanics force fields, Bond stretching, Bond bending, Dihedrals and
torsion, Nonbonded interactions, Hard and soft interactions, Electrostatic
interactions, Combination/mixing rules, Standard force fields.
Simulation of Ensembles Using Monte Carlo and
Molecular Dynamics Methods: Introduction to MonteCarlo simulation, Importance
sampling and the metropolis algorithm, Implementation of metropolis Monte Carlo
algorithm, Simulation cell and periodic boundary conditions, Moves and
acceptance criteria, Simulations in different ensembles, Multicanonical Monte
Carlo and the transition matrix, Configurational bias
Monte Carlo, Calculation of thermodynamic properties, Introduction to molecular
dynamics simulation, Initialization and force calculation, Algorithms to
integrate the equations of motion, Thermostats and barostats,
Autocorrelation functions, Free energy calculations, Molecular dynamics
packages, Design and development of novel performance chemicals and materials
for applications in polymers, catalysts, pharmaceuticals and solvents.
Course
learning outcomes (CLOs):
The
students will be able to:
1. apply
the principles of molecular mechanics in molecular modeling
2. apply
various simulation techniques for model solutions
3. use
molecular modeling software
4. design and develop novel performance chemicals
and materials for applications in polymers, catalysts, pharmaceuticals
Recommended Books:
1.
McQuarrie, D.A.,Statistical Mechanics, University Science Books
(2000).
2.
Frenkel, D.,andSmit, B.,Understanding
Molecular Simulation: From Algorithms to
3.
Applications, Academic Press, (2002).
4.
Leach,
A.R., Molecular Modeling: Principles and Applications, Pearson Education Ltd. (2001).