The BS degree program is designed to train students in data science methods, and to apply these methods to the study of material structure and behavior.
The material science and engineering degree program offers a materials informatics foundation together with a “wet lab-dry lab” paradigm for integrating experimental and computational training in materials research. By offering a strong materials core integrated into the use of data science techniques, graduates of the program will be a position to collaborate and communicate with practicing scientists from many fields.
The overall objective of the material science and engineering program is to expose students to an innovative program in which data intensive research support the translation of fundamental materials science and engineering into the fields of materials discovery, manufacturing, and engineering systems. We expect our graduates to achieve the following skills and capabilities within a short time after graduation:
Student outcomes describe what students are expected to know and be able to do by the time they graduate. They relate to the knowledge, skills and behaviors students acquire as they progress through the materials science and engineering program. They include:
The Data-drive Materials Design Research Experience for Undergraduates (REU) offers students in materials design an opportunity to use an interdisciplinary, data-driven approach to create novel materials with the potential to impact society.
REU students will be introduced to the field of Materials Informatics and learn how to apply the tools of artificial intelligence to create novel materials with preferred characteristics. Our program offers a combination of formal education based on a cutting edge curriculum developed by faculty in the department.
The internship also includes a scientific communications workshop, educational seminars and social activities. At the end of the 10-week program, students present their research results to the group. Summer 2022 internships will run from May 31 to August 5.
In the event that we are unable to host an on-site program, we are prepared to hold a virtual internship. This will include remote training and individualized research projects.
To be considered for the Summer 2021 NSF REU program (May 31 to August 5), please apply online by Feb. 7, 2022.
MDI 201, Introduction to Material Design & Informatics
MDI 210, Chemical Design of Materials
MDI 311, Electronic, Optical, and Magnetic Properties of Materials
MDI 312, Multiscale Design of Materials
MDI 321, Quantitative Methods in Materials Characterization
MDI 322, Materials Characterization and Synthesis Lab
MDI 332, Foundations of Materials Thermodynamics and Structure
MDI 336, Kinetics, Defects, and Transport
MDI 404, Statistical Principles of Materials Informatics
MDI 440, Design and Function of Soft Matter
MDI 450, Machine Learning in Materials Design
MDI 471, Materials for a Regenerative Economy
MDI 493, Materials Design Laboratory I
MDI 494, Materials Design Laboratory II
MDI 401, Special Topics
MDI 481, Thin Films, Surfaces, and Interfaces
MDI 483, Functional Materials
MDI 484, Computational Materials Design
MDI 485, Polymers, Colloids, Gels, and Active Matter
Note: All courses are 3 credits each.