Syllabus

Module 1

Background concept: Brief overview of thermodynamic equilibrium state, laws of thermodynamics, thermodynamic potentials, stability criteria, phase equilibria 3 hrs

Module 2

Probability: combinatorial problems, basic probability theory, variables, Stirling approximation, distributions. 5 hrs

Module 3

Non-interacting particles: Distribution laws, partition functions, thermodynamics quantities in terms of partition functions, quantum correlations, collective modes, fermions, bosons, photons, factorization of the molecular partition function. 10 hrs

Module 4

Ensembles in Statistical Mechanics: Ensemble postulate and ergodicity, microcanonical, canonical and grand canonical ensembles, phase space, fluctuations. 6 hrs

Module 5

Application to chemical systems (interacting particles): Ideal gases residual entropy, the liquid states interparticle potentials, configurational partition functions, pair correlation function, neutron scattering experiments, virial equation, solutions lattice model, ideal and non-ideal solutions, solutions of electrolytes Debye-Huckel theory and its modifications, Computer simulations ensemble averages, random numbers, Introduction to Molecular dynamics. 12 hrs

To enable students to acquire basic knowledge of statistical mechanics.

1. To acquire specialised understanding of the concept of entropy and thereby bridge the opposition between a microscopic approach (statistical mechanics) and a macroscopic one (thermodynamics).

Understanding and deriving macroscopic (thermodynamic) properties, such as pressure and phase behaviour, based on the atomic/microscopic properties of a large number of molecules, using statistical mechanics or statistical thermodynamics.

4. Students also acquire a basic and rigorous understanding of entropy, free energy and temperature. In the course you learn more about the principles of molecular dynamics and Monte Carlo simulations and how they are used in modern chemistry research

CO1: The course aims to focus on the details of microscopic picture of thermodynamics heavily relying on concepts from probability theory to model the distribution of particle states
CO2: Understanding the relationship between microscopic and macroscopic properties and the ability to understand the association between statistical mechanics and thermodynamics.
CO3: Students will learn to use concepts like the partition function to derive thermodynamic quantities
CO4: Applying statistical ensembles to analyze thermodynamic behavior.
CO5: Solving complex problems using the application of statistical mechanics and computer simulations

Peter Atkins, Julio De Paula, 2. Physical Chemistry: Quantum Chemistry, Spectroscopy, And Statistical Thermodynamics: 2, Oxford , Indian ninth edition.

K. L. Kapoor, 1. A Textbook of Physical Chemistry (Vol. 5), Volume 5, Macmillan, 2004

T. Engel and P. Reid, 2. Thermodynamics, Statistical Thermodynamics and Kinetics, Pearson 2013

Donald McQuarrie, John Simon, Heather Cox, Physical Chemistry: A molecular approach, VIVA student Edition