Rate My Professor Donald Brenner

Donald Brenner is the Kobe Steel Distinguished Professor and Head of the Department of Materials Science and Engineering at North Carolina State University. He earned his B.S. in Chemistry from the State University of New York in 1982 and his Ph.D. in Chemistry from Pennsylvania State University in 1987. After completing postdoctoral research at the U.S. Naval Research Laboratory in the Theoretical Chemistry Section, Brenner joined the NC State faculty in 1994.

Brenner's research specializes in computational materials science, focusing on atomistic modeling and simulation techniques, including molecular dynamics and quantum-based methods. He is globally recognized for developing the Brenner Potential, introduced in his seminal 1990 paper "Empirical potential for hydrocarbons for use in simulating the chemical vapor deposition of diamond films" (Physical Review B), which has become a cornerstone for simulating carbon nanostructures and hydrocarbon systems. He also advanced the field with the second-generation reactive empirical bond order (REBO) potential energy expression for hydrocarbons (2002). His recent work includes co-authoring "Disordered enthalpy–entropy descriptor for high-entropy ceramics discovery" in Nature (2024) and "Interfacial defect properties of high-entropy carbides" in Physical Review Materials (2025), contributing to the discovery and understanding of advanced high-entropy materials.

Brenner has received numerous honors, including election as a 2024 Materials Research Society Fellow for pioneering contributions to materials modeling, the Alexander Quarles Holladay Medal for Excellence (NC State's highest faculty award), the R.J. Reynolds Awards for Excellence in Research, Teaching, and Extension, the 2002 Foresight Institute Feynman Prize in Nanotechnology (theory), and the Alcoa Foundation Distinguished Engineering Achievement Award. He currently chairs the NC State University Materials Council for the 2025–2026 term and leads the Brenner Research Lab, which develops multiscale modeling tools to predict material properties for applications in energy, electronics, and structural materials. His work has significantly influenced the direction of materials research, particularly in atomistic simulations and nanomaterials.