Stefano Curtarolo

Curtarolo

Edmund T. Pratt Jr. School Distinguished Professor of Mechanical Engineering and Materials Science

RESEARCH FIELDS

  • Artificial Intelligence Materials Science
  • Autonomous Materials Design
  • Computational Materials Science
  • High-Entropy Disordered and Amorphous Systems
  • Materials for Energy Applications
  • Materials for Aerospace Applications
  • Materials for Deep Space Exploration

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

  • Edmund T. Pratt Jr. School Distinguished Professor of Mechanical Engineering and Materials Science
  • Professor in the Department of Mechanical Engineering and Materials Science
  • Director of the Center for Autonomous Materials Design
  • Professor in the Department of Electrical and Computer Engineering
  • Professor in the Department of Physics
  • Faculty Network Member of The Energy Initiative

Contact Information

Education

  • Ph.D. Massachusetts Institute of Technology, 2003
  • M.S. Pennsylvania State University, 1999
  • M.S. University of Padua (Italy), 1998
  • M.S. University of Padua (Italy), 1995

Research Interests

Artificial Intelligence Materials Science; Autonomous Materials Design; Computational materials science; High-Entropy Disordered Systems; Materials for Energy Applications; Materials for Aerospace Applications. Prof. Curtarolo multidisciplinary research makes use of state-of-the-art techniques from fields like materials science, chemistry, physics, quantum mechanics, mathematics and computer science.

Awards, Honors, and Distinctions

  • Clarivate Analytics Highly Cited Researcher. Clarivate Analytics. 2021
  • High Performance, Computing Modernization Program Flagship Award. DOD-HPC. 2021
  • Distinguished Visiting Professorship. Max-Plank Society, Fritz-Haber Instittue, Berlin. 2018
  • Friedrich Wilhelm Bessel Research Award. Alexander von Humboldt-Foundation. 2016
  • DOD-MURI Award, The Science of Entropy Stabilized Ultra-High Temperature Materials. Duke University, NCSU, UCSD, UVA. 2015
  • DOD-MURI Award, Topological decompositions and spectral sampling algorithms for elements substitution in critical technologies. Duke University, UMD, UNT, CMU, BYU. 2013
  • Fellow. American Physical Society. 2013
  • Stansell Distinguished Research Award. Duke University. 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 221L: Structure and Properties of Solids
  • ME 555: Advanced Topics in Mechanical Engineering
  • ME 592: Research Independent Study in Mechanical Engineering or Material Science

In the News

Representative Publications

  • Esters, M; Oses, C; Divilov, S; Eckert, H; Friedrich, R; Hicks, D; Mehl, MJ; Rose, F; Smolyanyuk, A; Calzolari, A; Campilongo, X; Toher, C; Curtarolo, S, aflow.org: A web ecosystem of databases, software and tools, Computational Materials Science, vol 216 (2023) [10.1016/j.commatsci.2022.111808] [abs].
  • Calzolari, A; Oses, C; Toher, C; Esters, M; Campilongo, X; Stepanoff, SP; Wolfe, DE; Curtarolo, S, Plasmonic high-entropy carbides., Nature Communications, vol 13 no. 1 (2022) [10.1038/s41467-022-33497-1] [abs].
  • Wang, X; Proserpio, DM; Oses, C; Toher, C; Curtarolo, S; Zurek, E, The Microscopic Diamond Anvil Cell: Stabilization of Superhard, Superconducting Carbon Allotropes at Ambient Pressure., Angewandte Chemie International Edition, vol 61 no. 32 (2022) [10.1002/anie.202205129] [abs].
  • Kulik, HJ; Hammerschmidt, T; Schmidt, J; Botti, S; Marques, MAL; Boley, M; Scheffler, M; Todorović, M; Rinke, P; Oses, C; Smolyanyuk, A; Curtarolo, S; Tkatchenko, A; Bartók, AP; Manzhos, S; Ihara, M; Carrington, T; Behler, J; Isayev, O; Veit, M; Grisafi, A; Nigam, J; Ceriotti, M; Schütt, KT; Westermayr, J; Gastegger, M; Maurer, RJ; Kalita, B; Burke, K; Nagai, R; Akashi, R; Sugino, O; Hermann, J; Noé, F; Pilati, S; Draxl, C; Kuban, M; Rigamonti, S; Scheidgen, M; Esters, M; Hicks, D; Toher, C; Balachandran, PV; Tamblyn, I; Whitelam, S; Bellinger, C; Ghiringhelli, LM, Roadmap on Machine learning in electronic structure, Electronic Structure, vol 4 no. 2 (2022) [10.1088/2516-1075/ac572f] [abs].
  • Supka, A; Mecholsky, NA; Buongiorno Nardelli, M; Curtarolo, S; Fornari, M, Two-Layer High-Throughput: Effective Mass Calculations Including Warping, Engineering, vol 10 (2022), pp. 74-80 [10.1016/j.eng.2021.03.031] [abs].