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Stefano Curtarolo


Professor in the Department of Mechanical Engineering and Materials Science


  • Nanoscale Science of Energy
  • Computational materials science
  • Nanotube growth characterization
  • Alloy theory
  • Superlubricity on quasicrystals
  • Superconductivity in Metal borides
  • Genetic Approaches to QM Predictions of Materials Structures
  • Materials for Nuclear Detection

The research is multidisciplinary and makes use of state of the art techniques from fields like materials science, chemistry, physics, quantum mechanics, mathematics and computer science.

Appointments and Affiliations

  • Professor in the Department of Mechanical Engineering and Materials Science
  • Professor in the Department of Electrical and Computer Engineering
  • Professor in the Department of Physics
  • Professor in the Department of Chemistry
  • Faculty Network Member of The Energy Initiative

Contact Information:

  • Office Location: 301 Hudson Hall, Box 90300, Durham, NC 27708
  • Office Phone: (919) 660-5506
  • Websites:


  • Ph.D. Massachusetts Institute of Technology, 2003
  • M.S. Pennsylvania State University, 1999
  • M.S. University of Padua (Italy), 1995

Awards, Honors, and Distinctions:

  • Fellow. American Physical Society. 2013
  • Best Paper Award. CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry). 2008
  • MRS Silver Medal Graduate Student Award. Materials Research Society. 2008
  • NSF Early CAREER Award. National Science Foundation. 2008
  • ONR Young Investigator Program Award. Office of Naval Research. 2008
  • Faculty Early Career Development (CAREER) Program. National Science Foundation. 2007
  • Presidential Early Career Awards for Scientists and Engineers. President of the United States of America. 2007

Courses Taught:

  • ME 555: Advanced Topics in Mechanical Engineering

In the News:

Representative Publications:

  • Stanev, V; Oses, C; Kusne, AG; Rodriguez, E; Paglione, J; Curtarolo, S; Takeuchi, I, Machine learning modeling of superconducting critical temperature, Npj Computational Materials, vol 4 no. 1 (2018) [10.1038/s41524-018-0085-8] [abs].
  • Oses, C; Toher, C; Curtarolo, S, Data-driven design of inorganic materials with the Automatic Flow Framework for Materials Discovery, Mrs Bulletin, vol 43 no. 9 (2018), pp. 670-675 [10.1557/mrs.2018.207] [abs].
  • Gossett, E; Toher, C; Oses, C; Isayev, O; Legrain, F; Rose, F; Zurek, E; Carrete, J; Mingo, N; Tropsha, A; Curtarolo, S, AFLOW-ML: A RESTful API for machine-learning predictions of materials properties, Computational Materials Science, vol 152 (2018), pp. 134-145 [10.1016/j.commatsci.2018.03.075] [abs].
  • Hicks, D; Oses, C; Gossett, E; Gomez, G; Taylor, RH; Toher, C; Mehl, MJ; Levy, O; Curtarolo, S, AFLOW-SYM: platform for the complete, automatic and self-consistent symmetry analysis of crystals., Acta Crystallographica. Section A, Foundations and Advances, vol 74 no. Pt 3 (2018), pp. 184-203 [10.1107/s2053273318003066] [abs].
  • Usanmaz, D; Nath, P; Toher, C; Plata, JJ; Friedrich, R; Fornari, M; Buongiorno Nardelli, M; Curtarolo, S, Spinodal Superlattices of Topological Insulators, Chemistry of Materials, vol 30 no. 7 (2018), pp. 2331-2340 [10.1021/acs.chemmater.7b05299] [abs].

Affiliate Topics in Materials Research: