Laboratory for Nuclear and Disordered Materials
We use computational, experimental and data-driven methods to understand and design disordered, high-entropy, and radiation-tolerant materials for nuclear and high temperature environments. Based in the Department of Mechanical Engineering and the School of Energy Resources, University of Wyoming.
👥 Team
Graduate Students
The lab is currently recruiting its first PhD and MS students. See "Join Us" below for details.
Undergraduate Researchers
Opportunities available for motivated undergraduates interested in computational materials research.
📩 Join Us
The lab is actively recruiting motivated PhD and MS students interested in computational materials science, nuclear materials, and disordered/high-entropy systems. A background in materials science, mechanical engineering, physics, or a related field is welcome; prior coding or DFT/MD experience is a plus but not required.
To apply, please email psharma3@uwyo.edu with:
- Your BS (and MS, if applicable) transcripts
- A short motivation letter describing your research interests and why you'd like to join the lab
- Your CV/resume
- Preference will be giving to students with Bachelors and Masters in Mechanical Engineering with a GPA > 3.0
🖥️ Facilities and Codes
Computing Resources
- University of Wyoming Advanced Research Computing Center (ARCC) — allocation details to be added
- Frontera (Texas Advanced Computing Center) — prior allocation of over 500,000 node hours supporting high-entropy alloy and phonon transport studies
Experimental Resources
- Glove box, mini arc melter, box furnace and ball mill
Codes and Methods
- Density Functional Theory: VASP, Quantum ESPRESSO
- Molecular Dynamics: LAMMPS
- Machine learning interatomic potentials and data-driven property prediction (in-house and open-source tools)
- In-house scripts for high-throughput workflows and phonon/lattice dynamics analysis
🌱 Mentorship
The lab is committed to mentoring students as independent researchers, not just project executors. This includes regular one-on-one meetings, co-development of research questions rather than top-down assignment, encouragement to present at conferences and pursue first-author publications early, and support in developing computational and coding skills alongside domain knowledge. Students are encouraged to explore ideas adjacent to their core project and to build a professional network through collaborations and internships.
🤝 Collaborations
The lab builds on an active network of collaborators across academia and national laboratories, spanning computational and experimental materials science:
New collaborations — particularly with national laboratories and industry partners working on nuclear materials — are welcome. Please reach out via email below.