Computational Materials & Modeling

Students who finished all junior level courses of the following majors are eligible to enroll in this concentration:

Physics

Mechanical Engineering

Chemistry

A student of other majors can enroll in this concentration if he is able to fulfill the prerequisite requirements of all concentration courses.

For the concentration to be registered in the students’ records, the student should finish all the concentration courses successfully.

Simulations are nowadays regarded as the third pillar of the scientific method, complementing theory and experiment. Materials play an essential role in modern technology, industry, and everyday life. Having the proper materials is the key for any technological development. The often competing, complex mechanisms take place on a range of different length and time scales, requiring the development of new simulation methods suitable for each scale and scale bridging. Modeling, simulation, big data, and informatics tools are thus finding increasing applications not only in fundamental materials-science research, but also in real-world design and optimization of new materials. Graduates in the field of Computational Materials and Material Informatics will find excellent job opportunities in academia and corporate research and development.

Provide students with basic knowledge in materials science and engineering

Provide students with good understanding of the methods in numerical modeling and simulations

By the end of this concentration, the students will be able to:

Describe the most important features of various materials

Use common programs in computational materials science

Structural, mechanical, thermal, and electrical properties and processing of ceramics, polymers, and composites. Non-metallic materials for applications related to energy, desalination, aerospace, civil infrastructure, and industrial applications

Pre-requisites ME 205 or ME 216, ME 217 or consent of the instructor

Review of pertinent topics in classical and quantum physics. Gibb’s statistical ensembles, MB, BE, and FD statistics with simple applications to solids. Theoretical foundations of Monte Carlo simulation, Markov chains, random walks. Study of phase transitions in the 2D and 3D Ising models as well as in the Landau Ginsburg Model using Monte Carlo simulations. Selected Topics in Kinetic Monte Carlo Simulations.

Pre-requisite: Senior Standing

Classical and quantum mechanics techniques for atomistic simulations, Essentials of statistical thermodynamics and quantum mechanics concepts, Classical molecular dynamics, Density functional theory. Materials properties: Band structure, elastic constant, thermal conductivity, Phonons and vibrational spectroscopies, free-energy calculations, diffusion coefficients, viscosity, surface chemistry, Transition State Theory.

Pre-requisite: Senior Standing

The course introduces materials informatics, which is an intersection between materials science, computational methods, and big-data sciences. While the field methods and tools are heavily statistical, the focus in the course is on concepts more than mathematics and on materials science applications. At the beginning, the basics of statistical learning are introduced. Then, a selected set of applications in materials science are presented in a case study approach