Syllabus

1. Basic ideas and techniques of mathematical modelling.
2. Runge-Kutta method for solving ODEs.
3. Programming using Matlab.
4. Developing models using Simulink.
5. Molecular Dynamics
6. First-principles methods
7. Density functional theory
8. Random walk
9. Artificial neural networks (ANN)
10. Numerical methods

To make the student aware of mathematical modelling and its applications.

To make models of metallurgical systems.

To make the students aware of numerical techniques and learn how to use them for solving problems using these techniques.

To make models of metallurgical systems, To solve ODEs using Simulink.

1. Students will know techniques for making mathematical models of metallurgical systems.
2. Students will be aware of molecular dynamics and how molecular dynamics can be used to predict properties of materials.
3. Students will gain knowledge about quantum mechanics.
4. Students will learn about Hartree-Fock approximation and density functional theory (DFT).
5. The students will learn numerical techniques and how to solve problems using these techniuqes.
6. The students will be taught artificial neural networks (ANN)

Ruben Santamaria, Molecular Dynamics, Springer

Richard Lesar, Introduction to Computation Materials Science, Materials Research Society and Cambridge University Press

J. G. Lee, Computational Material Science-An Introduction, CRC Press

D. Marx, Ab Intito Molecualr Dynamics-Basic Theory and Advanced Methods, Cambridge University Press