Strengthening High-Tech Marketable Skills for Undergraduates through a Computational Materials Science Course

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this project seeks to establish an introductory course and several modules in computational material science (CPMS). These educational materials will be developed in close collaboration with industry, advanced research institutions, and undergraduate student researchers.

Computational materials science has gained prominence of late, utilizing supercomputing and machine learning methods to design novel materials. Its applications span fields of interest to industry and scientific researchers, including energy storage, drug delivery, and extreme conditions. The project team is designing the course to be accessible to all students, including the significant Hispanic student population in the College of Engineering at the investigating team's institution.

The course will be the initial step in introducing undergraduate students to modern, interdisciplinary subjects within STEM, aiming to promote equity among graduating students and develop a diverse STEM workforce. The project will engage over 200 students annually through the course and modules integrated into other existing courses. The aim is to not only provide students with skills relevant to the high-tech workforce, but also to inspire interest in research and future graduate education.

This project aims to enhance the capacity for students to engage in high-tech engineering practices by introducing them to state-of-the-art methods in CPMS at the nanoscale. The course will be designed to be introductory and multidisciplinary, with no specific prerequisites, making it accessible to a wide audience. To facilitate this aim, students will gain hands on experiences with (1) open-source simulation and visualization packages that are used for research as well as (2) commercial packages used in industry.

The project will also provide access to facilities, supercomputers, and 3D visualization equipment to enhance the learning experience. Additionally, the project will utilize peer mentoring, invite diverse guest lecturers from academia, industry, and national laboratories, and employ other practices that have an evidence base to support their effectiveness.

Students who successfully complete the project course and modules will be better prepared to pursue internships, which can lead to careers in either industry or higher education. Course materials, modules, and outcomes from program evaluation will be shared with the wider STEM education and HSI communities. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and increase institutional capacity to improve STEM learning and teaching at HSIs.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.