Course Description: Various phenomena involved in materials processing and design will be modeled using software packages based on differential equations and the finite element method. Examples will include aspects of solid state diffusion, structural stress, heat transfer, fluid flow and chemical reactions. The problems will involve unsteady state as well as 3 dimensional systems. Multi-physics phenomena will also be introduced. The main objective of this course is to introduce students to the use of commercial software packages to solve fairly common but complex physical and chemical phenomena related to the materials industry.

Softwares Packages and Topics Covered: MATLAB and ANSYS are two of the most commonly utilized softwares in materials science industry and research. Therefore, we provide exposure to both of them, as planned below:

MATLAB: Most common ODEs/PDEs used in engineering problems; numerical analysis; methods of solving ODEs/PDEs (Runge-Kutta method); Poissons equation, Laplace equation, applications to electrostatics, diffusion and heat transfer.

ANSYS: Basic concepts behind finite element method, structural analysis (statics/dynamics), vibrational analysis, heat transfer, fluid flow, thermomechanical coupling.

Course Description: Fundamentals of fracture mechanics and failure analysis, including Griffith theory, establishment of stress field at crack tip, stress intensity factor, fracture toughness, J-integral, R-curve and their measurements, fatigue and fatigue crack propagation, da/dn vs ΔK relationship, micro-mechanisms of fracture process and failure analysis as well as case studies; computational modeling of fracture.

Prescribed Text: Deformation and Fracture Mechanics of Engineering Materials by Richard W. Hertzberg, 5th edition.

Course Description: In this course, graduate students are taught the theory and application of computer modeling of materials at the atomic scale. Specific topics include: classical and modern first principles atomistic modeling approaches, statistical mechanics, molecular statics and dynamics, density functional theory and kinetic Monte Carlo sampling. The approximations, advantages and limitations involved with each approach are highlighted. A significant focus of the course is to provide a hands-on training in these computational techniques. To achieve this, a number of practical case studies from advanced materials and nanotechnology are presented in detail. The course includes an individual or group project. Another important focus is the computer modeling of material failure at the atomic scale. Towards the later portion of the course, some advanced topics, such as accelerated molecular dynamics, multiscale modeling, and coarse-graining approaches, are covered.

Students from diverse fields of study are welcome to attend the course. Although emphasis is on hard materials, a number of approaches and case studies from polymers and biological systems are also covered. Projects from diverse research areas are also encouraged.

Prerequisite: Graduate-level understanding of Materials Science \& Engineering; basic knowledge of coding/computer languages (e.g. Fortran / C).

Softwares: Hands-on training is be provided on state-of-the-art atomistic modeling techniques, specifically molecular dynamics (MD) and density functional theory (DFT). For MD, students are exposed to LAMMPS, whereas for DFT they learn Quantum-Espresso.