MBN310

School of Engineering \ Material Science and Nanotechnology Engineering

3

6

Compulsory

English

-

Can be taken as faculty elective course by the other engineering departments

Computational materials science is one of the fastest-growing disciplines today. The simulation of materials at various scales, from molecular to macroscopic structures, enables significant scientific and technological advancements. The MBN 310 course covers theoretical and numerical studies in materials science and nanotechnology. In this course, students will generally learn numerical methods and algorithms. It will provide knowledge about diffusion, kinetics, molecular dynamics, and quantum chemistry, as well as introduce state-of-the-art computer software to help students adapt to this rapidly evolving field.

• Advanced Engineering Mathematics, P. V. O'Neil, PWS Publishing Company, 2002.
• Numerical Solution of Partial Differential Equations: An Introduction, K. W. Morton and D. F. Mayers, Cambridge University Press, 2005.
• Ashby, M. F. , Ferreira P. J. , Schodek D. L. , Nanomaterials, Nanotechnologies and design, Elsevier Academic Press, 2009.
• Current articles and topics

The aim of this course is to provide knowledge on the fundamental principles of numerical methods in materials science and nanotechnology and to offer experience in applying this knowledge to solve engineering problems.

1. Gain a general understanding of computational materials science;
2. Develop an understanding of the assumptions and approaches used in numerical modeling across different time and length scales;
3. Learn how to use numerical analysis and modeling, as well as how to present and interpret simulation results.

Week 1: Basic Programming and Algorithms
Week 2: Matrix Operations, Root Finding of Functions, and Numerical Integration
Week 3: Random Numbers and Monte Carlo Methods
Week 4: Computational Solutions of Differential Equations / Euler and Heun Methods
Week 5: Computational Solutions of Differential Equations and Applications
Week 6: Computational Solutions of Partial Differential Equations / 1D Diffusion
Week 7: Computational Solutions of Partial Differential Equations / 2D Diffusion
Week 8: Computational Solutions of Partial Differential Equations / Wave Equation
Week 9: Molecular Dynamics
Week 10: Molecular Dynamics
Week 11: Molecular Dynamics / Quantum Chemistry
Week 12: Quantum Chemistry / Project Presentations

Projects: 15 %
Midterms: 25 %
Quiz: 25 %
Final: 35 %