Publications of Stefano Curtarolo

Alberi, K.; Nardelli, M. B.; Zakutayev, A.; Mitas, L.; Curtarolo, S.; Jain, A.; Fornari, M.; Marzari, N.; Takeuchi, I.; Green, M. L. et al.; Kanatzidis, M.; Toney, M. F.; Butenko, S.; Meredig, B.; Lany, S.; Kattner, U. R.; Davydov, A.; Toberer, E. S.; Stevanovic, V.; Walsh, A.; Park, N.-G.; Aspuru-Guzik, A.; Tabor, D. P.; Nelson, J.; Murphy, J.; Setlur, A.; Gregoire, J.; Li, H.; Xiao, R.; Ludwig, A.; Martin, L. W.; Rappe, A. M.; Wei, S.-H.; Perkins, J.: The 2019 materials by design roadmap. Journal of Physics D: Applied Physics 52 (1), 013001 (2019)

Friedrich, R.; Usanmaz, D.; Oses, C.; Supka, A.; Fornari, M.; Nardelli, M. B.; Toher, C.; Curtarolo, S.: Coordination corrected ab initio formation enthalpies. npj Computational Materials 5, 59 (2019)

Hicks, D.; Mehl, M. J.; Gossett, E.; Toher, C.; Levy, O.; Hanson, R. M.; Hart, G.; Curtarolo, S.: The AFLOW Library of Crystallographic Prototypes: Part 2. Computational Materials Science 161 (Suppl.), pp. S1 - S1011 (2019)

Nath, P.; Usanmaz, D.; Hicks, D.; Oses, C.; Fornari, M.; Buongiorno Nardelli, M.; Toher, C.; Curtarolo, S.: AFLOW-QHA3P: Robust and automated method to compute thermodynamic properties of solids. Physical Review Materials 3 (7), 073801 (2019)

Gossett, E.; Toher, C.; Oses, C.; Isayev, O.; Legrain, F.; Rose, F.; Zurek, E.; Carrete, J.; Mingo, N.; Tropsha, A. et al.; Curtarolo, S.: AFLOW-ML: A RESTful API for machine-learning predictions of materials properties. Computational Materials Science 152, pp. 134 - 145 (2018)

Hever, A.; Oses, C.; Curtarolo, S.; Levy, O.; Natan, A.: The Structure and Composition Statistics of 6A Binary and Ternary Crystalline Materials. Inorganic Chemistry 57 (2), pp. 653 - 667 (2018)

Hicks, D.; Oses, C.; Gossett, E.; Gomez, G.; Taylor, R. H.; Toher, C.; Mehl, M. J.; Levy, O.; Curtarolo, S.: AFLOW-SYM: platform for the complete, automatic and self-consistent symmetry analysis of crystals. Acta Crystallographica A 74 (3), pp. 184 - 203 (2018)

Lederer, Y.; Toher, C.; Vecchio, K. S.; Curtarolo, S.: The search for high entropy alloys: A high-throughput ab-initio approach. Acta Materialia 159, pp. 364 - 383 (2018)

Legrain, F.; Roekeghem, A. v.; Curtarolo, S.; Carrete, J.; Madsen, G. K. H.; Mingo, N.: Vibrational Properties of Metastable Polymorph Structures by Machine Learning. Journal of Chemical Information and Modeling 58 (12), pp. 2460 - 2466 (2018)

Nardelli, M. B.; Cerasoli, F. T.; Costa, M.; Curtarolo, S.; De Gennaro, R.; Fornari, M.; Liyanage, L.; Supka, A. R.; Wang, H.: PAOFLOW: A utility to construct and operate on ab initio Hamiltonians from the projections of electronic wavefunctions on atomic orbital bases, including characterization of topological materials. Computational Materials Science 143, pp. 462 - 472 (2018)

Oses, C.; Gossett, E.; Hicks, D.; Rose, F.; Mehl, M. J.; Perim, E.; Takeuchi, I.; Sanvito, S.; Scheffler, M.; Lederer, Y. et al.; Levy, O.; Toher, C.; Curtarolo, S.: AFLOW-CHULL: Cloud-Oriented Platform for Autonomous Phase Stability Analysis. Journal of Chemical Information and Modeling 58 (12), pp. 2477 - 2490 (2018)

Ouyang, R.; Curtarolo, S.; Ahmetcik, E.; Scheffler, M.; Ghiringhelli, L. M.: SISSO: a compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates. Physical Review Materials 2 (08), 083802 (2018)

Sarker, P.; Harrington, T.; Toher, C.; Oses, C.; Samiee, M.; Maria, J.-P.; Brenner, D. W.; Vecchio, K. S.; Curtarolo, S.: High-entropy high-hardness metal carbides discovered by entropy descriptors. Nature Communications 9 (1), 4980 (2018)

Stanev, V.; Oses, C.; Kusne, A. G.; Rodriguez, E.; Paglione, J.; Curtarolo, S.; Takeuchi, I.: Machine learning modeling of superconducting critical temperature. npj Computational Materials 4, 29 (2018)

Usanmaz, D.; Nath, P.; Toher, C.; Plata, J. J.; Friedrich, R.; Fornari, M.; Nardelli, M. B.; Curtarolo, S.: Spinodal Superlattices of Topological Insulators. Chemistry of Materials 30 (7), pp. 2331 - 2340 (2018)