Pursuing PhD in Computational Materials Science

[Norfonz]

Hi all,

I'm currently a senior studying chemical engineering. I'll be graduating this December. I am greatly interested in pursuing a PhD in materials science, and I am looking for programs that include an emphasis in computational materials (e.g. simulation of atomic structures). I am self-studying quantum mechanics from Griffiths, and I am loving every minute of it. I bring this up as quantum mechanics supplies the groundwork in modeling atomic structures (as in density functional theory).

My questions are as follows:

1) Does anyone have some good resources on learning more about the field of computational materials? A list of topics for me to research perhaps?

2) What schools have notable materials science programs that emphasize mathematical modeling of materials?

3) What sort of coding ability would I need to pursue this field? I have a basic proficiency in using Python, and I am looking into Fortran 90. I am experienced in Matlab and Comsol as well. I've dabbled in Mathematica.

I appreciate the help.

 

[TonyG]

Dear senior studying chemical engineering,

Congratulations on your upcoming graduation and your interest in pursuing a PhD in materials science with a focus on computational materials! This is a rapidly growing and exciting field that combines both chemistry and engineering principles.

To answer your questions:

1) There are many resources available for learning more about computational materials. Some good places to start are the Materials Project (materialsproject.org), which provides open-access data and tools for materials research, and the Center for Hierarchical Materials Design (chimad.northwestern.edu), which offers online tutorials and workshops on computational materials. Other topics you may want to research include density functional theory, molecular dynamics simulations, and machine learning in materials science.

2) Some notable schools with strong materials science programs that emphasize mathematical modeling of materials include MIT, Stanford, University of California-Berkeley, and University of Illinois at Urbana-Champaign. However, many other universities also have excellent programs in this field, so it's important to do some research and find a program that aligns with your specific interests and goals.

3) In terms of coding ability, it is important to have a strong foundation in programming languages such as Python, Fortran, and Matlab, as well as experience with computational tools like Mathematica and Comsol. However, it is also important to be open to learning new languages and tools as the field of computational materials is constantly evolving. Depending on your specific research interests, you may also need to develop skills in data analysis and machine learning.

I hope this information is helpful in your pursuit of a PhD in computational materials. Best of luck in your academic and career endeavors!