Stefano Curtarolo

Stefano Curtarolo

Professor in the Department of Mechanical Engineering and Materials Science

Professor in the Department of Physics (Secondary)

Professor in the Department of Electrical and Computer Engineering (Secondary)

Faculty Network Member of The Energy Initiative

Office Location: 
301 Hudson Hall, Box 90300, Durham, NC 27708
Front Office Address: 
301 Hudson Hall, Box 90300, Durham, NC 27708-0300
Phone: 
(919) 660-5506

Overview

RESEARCH FIELDS

  • 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.

Education & Training

  • Ph.D., Massachusetts Institute of Technology 2003

  • M.S., Pennsylvania State University 1999

  • M.S., University of Padua (Italy) 1995

Selected Grants

Autonomous materials discovery models and algorithms for the AFLOW framework and database awarded by Office of Naval Research (Principal Investigator). 2020 to 2024

Development of Cloud-Oriented Materials Discovery Services (AFLOW-Cloud) awarded by Office of Naval Research (Principal Investigator). 2020 to 2021

Materials-similarity metrics for the AFLOW data repository awarded by Office of Naval Research (Principal Investigator). 2018 to 2021

Synergetic Efforts in Automatic Accelerated Materials Design awarded by Office of Naval Research (Principal Investigator). 2016 to 2021

The Science of Entropy Stabilized Ultra-High Temperature Materials awarded by North Carolina State University (Principal Investigator). 2015 to 2020

Automated Characterization of Chemical Bonding in Inorganic Crystals awarded by Office of Naval Research (Principal Investigator). 2018 to 2019

Disorder as the discovery enabler for transition-metal mixed-anion materials awarded by Office of Naval Research (Co-Principal Investigator). 2017 to 2019

High-throughput Prediction of High-pressure Materials Properties for the AFLOWLIB Database awarded by Office of Naval Research (Principal Investigator). 2016 to 2019

Topological decompositions and spectral sampling algorithms for element substitution in critical technologies awarded by Office of Naval Research (Principal Investigator). 2013 to 2019

Pages

Hosseinian, S., et al. “The maximum edge weight clique problem: Formulations and solution approaches.” Springer Optimization and Its Applications, vol. 130, 2017, pp. 217–37. Scopus, doi:10.1007/978-3-319-68640-0_10. Full Text

Kaufmann, K., et al. “Discovery of high-entropy ceramics via machine learning.” Npj Computational Materials, vol. 6, no. 1, Dec. 2020. Scopus, doi:10.1038/s41524-020-0317-6. Full Text

Muratov, Eugene N., et al. “Correction: QSAR without borders.Chemical Society Reviews, vol. 49, no. 11, June 2020, p. 3716. Epmc, doi:10.1039/d0cs90041a. Full Text

Liyanage, Laalitha S. I., et al. “High-Throughput Computational Search for Half-Metallic Oxides.Molecules (Basel, Switzerland), vol. 25, no. 9, Apr. 2020. Epmc, doi:10.3390/molecules25092010. Full Text

Oses, C., et al. “High-entropy ceramics.” Nature Reviews Materials, vol. 5, no. 4, Apr. 2020, pp. 295–309. Scopus, doi:10.1038/s41578-019-0170-8. Full Text

Calzolari, Arrigo, et al. “Vibrational spectral fingerprinting for chemical recognition of biominerals.Chemphyschem : A European Journal of Chemical Physics and Physical Chemistry, Feb. 2020. Epmc, doi:10.1002/cphc.202000016. Full Text

Sławińska, J., et al. “Ultrathin SnTe films as a route towards all-in-one spintronics devices.” 2d Materials, vol. 7, no. 2, Jan. 2020. Scopus, doi:10.1088/2053-1583/ab6f7a. Full Text

Avery, P., et al. “Predicting superhard materials via a machine learning informed evolutionary structure search.” Npj Computational Materials, vol. 5, no. 1, Dec. 2019. Scopus, doi:10.1038/s41524-019-0226-8. Full Text

Friedrich, R., et al. “Coordination corrected ab initio formation enthalpies.” Npj Computational Materials, vol. 5, no. 1, Dec. 2019. Scopus, doi:10.1038/s41524-019-0192-1. Full Text

Lenz, M. O., et al. “Parametrically constrained geometry relaxations for high-throughput materials science.” Npj Computational Materials, vol. 5, no. 1, Dec. 2019. Scopus, doi:10.1038/s41524-019-0254-4. Full Text

Toher, C., et al. “Unavoidable disorder and entropy in multi-component systems.” Npj Computational Materials, vol. 5, no. 1, Dec. 2019. Scopus, doi:10.1038/s41524-019-0206-z. Full Text

Pages

Isayev, Olexandr, et al. “Quantitative materials structure-property relationships (QMSPR) modeling using novel electronic and structural descriptors.” Abstracts of Papers of the American Chemical Society, vol. 248, AMER CHEMICAL SOC, 2014.

Isayev, Olexandr, et al. “Materials cartography: Navigating through chemical space using structural and electronic fingerprints.” Abstracts of Papers of the American Chemical Society, vol. 248, AMER CHEMICAL SOC, 2014.

Curtarolo, Stefano. “Distributed synergies for materials development: The aflowlib.org consortium.” Abstracts of Papers of the American Chemical Society, vol. 243, AMER CHEMICAL SOC, 2012.

Ceder, G., et al. “First principles calculated databases for the prediction of intermetallic structure.Abstracts of Papers of the American Chemical Society, vol. 226, 2003, pp. U303–U303.