Publications of Stefano Curtarolo

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

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

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

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

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

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

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

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

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

Nardelli, M.B., F.T. Cerasoli, M. Costa, S. Curtarolo, R. De Gennaro, M. Fornari, L. Liyanage, A.R. Supka and H. Wang: 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, 462–472 (2018).

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

Ouyang, R., S. Curtarolo, E. Ahmetcik, M. Scheffler and L.M. Ghiringhelli: 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., T. Harrington, C. Toher, C. Oses, M. Samiee, J.-P. Maria, D.W. Brenner, K.S. Vecchio and S. Curtarolo: High-entropy high-hardness metal carbides discovered by entropy descriptors. Nature Communications 9 (1), 4980 (2018).

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

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