The U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) and Princeton University have launched a new graduate research initiative, the Collaborative Research in Plasma Science and Technology (CRPST) program. Beginning July 1, 2026, the two‑year pilot formalizes joint advising and expands opportunities for Princeton University graduate students in engineering, physics and related fields to conduct research at PPPL.
The program is designed to expand collaborations between University faculty and PPPL scientists on student research aligned with the Lab's mission and advancing discoveries in plasma science and technology. The program supports research in fusion energy, plasma science and technology, machine learning applications, microelectronics, quantum materials and devices, electromanufacturing, computational physics and other areas aligned with the DOE's mission and PPPL priorities.
Each student in the program is co‑advised by one PPPL scientist and one Princeton University faculty member. Students will spend at least one day a week at PPPL, working within research groups and accessing Laboratory facilities to support their projects. The pilot is supported through a shared funding model in which CRPST provides half of the funding for graduate student support each year, which is matched by funding from the Princeton faculty adviser's own research funds.
Strengthening and expanding Princeton-PPPL collaboration in mission-driven research
Fatima Ebrahimi, who serves as the program manager for CRPST, has long advocated for expanding collaboration between PPPL and Princeton University and increasing graduate student participation in Laboratory‑based plasma research. She said the launch of the pilot marks a step toward more structured engagement between the two institutions.
"It's exciting to have more students at PPPL," Ebrahimi said. "Deepening ties with the Princeton main campus is really important. We have so many mission‑driven projects, and involving early career scientists is essential. These projects also provide students with valuable interdisciplinary exposure."
She said the program benefits both institutions. "This partnership doesn't just bring more students into PPPL projects, it connects our scientists with Princeton faculty. Their expertise strengthens our research, and our facilities support theirs."
Ebrahimi added that the program fills a long‑standing gap and draws inspiration from a predecessor program, the Program in Plasma Science & Technology, which successfully facilitated graduate student research collaborations in prior decades. She hopes the pilot will demonstrate strong student progress and productive research emphasizing the importance of collaboration across disciplines. Ebrahimi noted that "you can't confine research to one institution or one field. This program fosters the interdisciplinary approaches needed in plasma physics."
2026 CRPST Cohort:
Name: Arunava Das
Home Department: Electrical and Computer Engineering
PPPL Co‑adviser: Alastair Stacey
Princeton Co‑adviser: Julia Mikhailova
Project Title: Ultrafast Dynamics Behind the Laser Writing of Spin Lattice Defects in Wide-bandgap Materials: Toward Scalable Integrated Quantum Photonics
Project Description: Ultrafast laser writing has emerged as a promising route toward the deterministic fabrication of quantum defects such as nitrogen-vacancy centers in diamond. However, the microscopic pathway linking femtosecond laser excitation to defect formation remains poorly understood, limiting defect yield, spatial precision and reproducibility. This project investigates defect generation as a strong-field, nonequilibrium process spanning electronic excitation, transient plasma dynamics and atomic-scale defect formation. Although the initial electronic excitation occurs on femtosecond timescales and the eventual defect forms through a stochastic, irreversible sequence of lattice processes spanning many orders of magnitude in time, the relationship between ultrafast carrier dynamics and the statistics of quantum defect formation has not been quantitatively established.
Name: Katherine Hillis
Home Department: Electrical and Computer Engineering
PPPL Co-adviser: Yevgeny Raitses
Princeton Co-adviser: Barry Rand
Project Title: Plasma-induced Halide Exchange to Stabilize Redox-active Halide Perovskite Semiconductor Surfaces
Project Description: Metal halide perovskites (MHPs) are promising microelectronic semiconductors but are intrinsically redox-reactive. Of the many MHP compositions, formamidinium lead triiodide has become the workhorse of perovskite solar research efforts due to its superior optoelectronic properties. However, halide oxidation, ion migration and interfacial electrochemical reactions greatly limit device stability and stand as major obstacles to their commercialization. Our previously conducted work at Princeton University demonstrates that installing chloride on formamidinium lead triiodide surfaces dramatically enhances thermal stability of the devices. Through this collaboration with PPPL, we aim to leverage controlled plasma-surface interactions to engineer similar halogen-exchanged layers using plasma-generated radicals.
Name: Michelle Hu
Home Department: Department of Physics
PPPL Co-adviser: Alastair Stacey
Princeton Co-adviser: Dane de Quilettes
Project Title: 3D Photoluminescence Tomography of Co-doped Quantum Diamond
Name: Jinsu Kim
Home Department: Mechanical and Aerospace Engineering
PPPL Co-adviser: Timothy Stoltzfus-Dueck
Princeton Co-adviser: Clarence Rowley
Project Title: Structure-preserving Model Reduction for Hamiltonian Systems
Project Description: For complex, high-dimensional systems, reduced-order models can be extremely useful, for instance, to speed up numerical simulations or to use for real-time prediction. However, for Hamiltonian systems, which often arise in plasma physics, most model-reduction methods break the Hamiltonian structure, often resulting in unstable models that are useless for prediction. The project develops improved methods for model reduction that preserve this Hamiltonian structure and applies them to various problems in plasma physics.
Name: Zijian Sun
Home Department: Mechanical and Aerospace Engineering
PPPL Co‑adviser: John Mark Martirez
Princeton Co‑adviser: Yiguang Ju
Project Title: Ab Initio-trained Machine Learning Molecular Dynamics for Surface Nitridation
Project Description: This project develops ab initio-trained machine learning molecular dynamics models to investigate the atomic-scale mechanisms of surface nitridation. By combining first-principles calculations with machine learning interatomic potentials, this work enables efficient simulations of nitrogen adsorption, diffusion and surface reactions relevant to advanced energy materials.
Name: Antoine Voyer
Home Department: Mechanical and Aerospace Engineering
PPPL Co‑adviser: Ammar Hakim
Princeton Co‑adviser: Christine Allen-Blanchette
Project Title: Learning Structure-aware Preconditioners for Implicit Plasma Simulation
Project Description: This project develops adaptive reinforcement learning-based preconditioners for linear systems arising from elliptic partial differential equations in plasma and fusion modeling. In collaboration with PPPL, we integrate scientific machine learning with plasma simulation to improve solver robustness and efficiency in anisotropic, heterogeneous regimes.
