Stefano Curtarolo

Professor in the Department 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

• 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

• Office Location: 144 Hudson Hall, Box 90300, Durham, NC 27708
• Office Phone: (919) 660-5506
• Email Address:
• Websites:
  • http://materials.duke.edu

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

• 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 555: Advanced Topics in Mechanical Engineering

In the News

• Disordered Materials Could Be Hardest, Most Heat-Tolerant Ever (Nov 26, 2018 | Pratt School of Engineering)
• D.I.Y. Crystal-Makers Get Refurbished Online Cookbook (Jun 2, 2017 | Pratt School of Engineering)
• Can artificial intelligence create the next wonder material? (May 5, 2016 | Nature)
• Engineering Researchers Reveal New Class of Stable Oxides Based on Five or More Elements (Oct 1, 2015)
• Researchers Aim to Develop New Techniques for Creating High-Temperature Alloys (Aug 25, 2015)
• A Made-to-Order Materials Menu (Nov 17, 2014 | Duke Research Blog)
• Duke Engineers Use Brute Force Computing to Find New Materials (Jan 5, 2014)
• How supercomputers will yield a golden age of materials science (Nov 22, 2013 | Scientific American)
• Pratt Engineers Awarded Four Department of Defense Grants (Jun 18, 2013)

Representative Publications

• Hong, QJ; Schroers, J; Hofmann, D; Curtarolo, S; Asta, M; van de Walle, A, Theoretical prediction of high melting temperature for a Mo–Ru–Ta–W HCP multiprincipal element alloy, Npj Computational Materials, vol 7 no. 1 (2021) [10.1038/s41524-020-00473-6] [abs].
• Wang, H; Gopal, P; Picozzi, S; Curtarolo, S; Buongiorno Nardelli, M; Sławińska, J, Spin Hall effect in prototype Rashba ferroelectrics GeTe and SnTe, Npj Computational Materials, vol 6 no. 1 (2020) [10.1038/s41524-020-0274-0] [abs].
• Kaufmann, K; Maryanovsky, D; Mellor, WM; Zhu, C; Rosengarten, AS; Harrington, TJ; Oses, C; Toher, C; Curtarolo, S; Vecchio, KS, Discovery of high-entropy ceramics via machine learning, Npj Computational Materials, vol 6 no. 1 (2020) [10.1038/s41524-020-0317-6] [abs].
• Kusne, AG; Yu, H; Wu, C; Zhang, H; Hattrick-Simpers, J; DeCost, B; Sarker, S; Oses, C; Toher, C; Curtarolo, S; Davydov, AV; Agarwal, R; Bendersky, LA; Li, M; Mehta, A; Takeuchi, I, On-the-fly closed-loop materials discovery via Bayesian active learning., Nature Communications, vol 11 no. 1 (2020) [10.1038/s41467-020-19597-w] [abs].
• Van Roekeghem, A; Carrete, J; Curtarolo, S; Mingo, N, High-throughput study of the static dielectric constant at high temperatures in oxide and fluoride cubic perovskites, Physical Review Materials, vol 4 no. 11 (2020) [10.1103/PhysRevMaterials.4.113804] [abs].