Use theory and application of computer simulations to model, understand, and predict the properties of real materials. Introduction to materials modeling and simulation: Modeling and simulation, What is meant by computational materials science and engineering, Scales in materials structure and behavior, How to develop models Simulation of finite systems: Sums of interacting pairs of objects, Perfect crystals, Cutoffs, Periodic boundary conditions, Implementation, long-ranged potentials, Interatomic potentials, Perview of molecular dynamics, Density functional theory, TheMany-Body Schrödinger Equation, Kohn–Sham Equation, Applications of these methods in modeling of mechanical, electronic, magnetic, optical, and dielectric properties of materials, (10 hours)

Sums of interacting pairs of objects, Perfect crystals, Cutoffs, Periodic boundary conditions, Implementation, long-ranged potentials, Interatomic potentials. The cohesive energy, Interatomic potentials, Pair potentials, Ionic materials, Metals, Covalent solids, Systems with mixed bonding, What we can simulate, Determining parameters in potentials, Molecular dynamics: Basics of molecular dynamics for atomic systems, An example calculation, Velocity rescaling, Molecular dynamics in other ensembles, Accelerated dynamics, Limitations of molecular dynamics, Molecular dynamics in materials research Molecular and macromolecular systems: Random-walk models of polymers, Atomistic simulations of macromolecules, Coarse-grained methods, Lattice models for polymers and biomolecules, Simulations of molecular and macromolecular materials. (10 hours)

Finite element methods, Monte Carlo methods, Markov Chain, Random Walking (8 hours)

Phase field modelling, Definition of Terms Used in Computational Design of Materials, Design principles of novel materials (8 hours)

To provide an understanding on the basics of modeling and simulation of materials. The course aims to introduce students to a variety of methods used in modelling and simulation to predict the properties of materials.

To provide insights into the length scale of modeling of materials

To provide conceptual knowledge on molecular dynamics simulations: boundary conditions ensembles, etc. The studnets will gain knowledge on description of atomic interaction, density functional theory (DFT) and Hartree-Fock.

To provide the student knowledge on modeling of macromolecular systems

To proved the students knowledge of real problems and how to apply the knowledge gained from the course in research in practical applications. The students are expected to be able to design, perform and analyze computer experiments using electronic and atomistic simulation techniques appropriate for the problem at hand.

To give the studnets the knowledge of phase field modelling which would be high beneficial in understanding the micorstructural evolution.

Understand the principles of modelling at different length scales

Compute properties of materials

Understand the principles of phase field modelling which is a mathematical method to simulate how boundaries and structures change inside materials over. time.

Write codes for predicting the properties of materials

Validate the material properties

Develop materials with better physical and mechanical properties.

Yip, S., Handbook of materials modeling, Springer Science & Business Media. USA , 2007

LeSar, R, Introduction to computational materials science: fundamentals to applications, Cambridge University Press. , 2013.

Lee, J. G, Computational materials science: an introduction., CRC press , 2016

Ohno, K., Esfarjani, K., & Kawazoe, Y, Computational materials science: from ab initio to Monte Carlo methods., Springer , 2018