| The high-throughput highway to computational materials design S Curtarolo, GLW Hart, MB Nardelli, N Mingo, S Sanvito, O Levy Nature materials 12 (3), 191-201, 2013 | 2010 | 2013 |
| AFLOW: An automatic framework for high-throughput materials discovery S Curtarolo, W Setyawan, GLW Hart, M Jahnatek, RV Chepulskii, ... Computational Materials Science 58, 218-226, 2012 | 1273 | 2012 |
| AFLOWLIB. ORG: A distributed materials properties repository from high-throughput ab initio calculations S Curtarolo, W Setyawan, S Wang, J Xue, K Yang, RH Taylor, LJ Nelson, ... Computational Materials Science 58, 227-235, 2012 | 1130 | 2012 |
| First-principles elastic constants and electronic structure of and PtSi O Beckstein, JE Klepeis, GLW Hart, O Pankratov Physical Review B 63 (13), 134112, 2001 | 495 | 2001 |
| Algorithm for generating derivative structures GLW Hart, RW Forcade Physical Review B—Condensed Matter and Materials Physics 77 (22), 224115, 2008 | 432 | 2008 |
| Evolutionary approach for determining first-principles hamiltonians GLW Hart, V Blum, MJ Walorski, A Zunger Nature materials 4 (5), 391-394, 2005 | 372 | 2005 |
| Machine learning for alloys GLW Hart, T Mueller, C Toher, S Curtarolo Nature Reviews Materials 6 (8), 730-755, 2021 | 349 | 2021 |
| The AFLOW standard for high-throughput materials science calculations CE Calderon, JJ Plata, C Toher, C Oses, O Levy, M Fornari, A Natan, ... Computational Materials Science 108, 233-238, 2015 | 305 | 2015 |
| Accelerating high-throughput searches for new alloys with active learning of interatomic potentials K Gubaev, EV Podryabinkin, GLW Hart, AV Shapeev Computational Materials Science 156, 148-156, 2019 | 293 | 2019 |
| Compressive sensing as a paradigm for building physics models LJ Nelson, GLW Hart, F Zhou, V Ozoliņš Physical Review B—Condensed Matter and Materials Physics 87 (3), 035125, 2013 | 256 | 2013 |
| The AFLOW library of crystallographic prototypes: part 1 MJ Mehl, D Hicks, C Toher, O Levy, RM Hanson, G Hart, S Curtarolo Computational Materials Science 136, S1-S828, 2017 | 233 | 2017 |
| Using genetic algorithms to map first-principles results to model Hamiltonians: Application to the generalized Ising model for alloys V Blum, GLW Hart, MJ Walorski, A Zunger Physical Review B—Condensed Matter and Materials Physics 72 (16), 165113, 2005 | 198 | 2005 |
| UNCLE: a code for constructing cluster expansions for arbitrary lattices with minimal user-input D Lerch, O Wieckhorst, GLW Hart, RW Forcade, S Müller Modelling and Simulation in Materials Science and Engineering 17 (5), 055003, 2009 | 182 | 2009 |
| Generating derivative structures from multilattices: Algorithm and application to hcp alloys GLW Hart, RW Forcade Physical Review B—Condensed Matter and Materials Physics 80 (1), 014120, 2009 | 168 | 2009 |
| Generating derivative structures at a fixed concentration GLW Hart, LJ Nelson, RW Forcade Computational Materials Science 59, 101-107, 2012 | 131 | 2012 |
| Electronic structure of BAs and boride III-V alloys GLW Hart, A Zunger Physical Review B 62 (20), 13522, 2000 | 130 | 2000 |
| Comprehensive search for new phases and compounds in binary alloy systems based on platinum-group metals, using a computational first-principles approach GLW Hart, S Curtarolo, TB Massalski, O Levy Physical Review X 3 (4), 041035, 2013 | 126 | 2013 |
| Machine-learned multi-system surrogate models for materials prediction C Nyshadham, M Rupp, B Bekker, AV Shapeev, T Mueller, ... npj Computational Materials 5 (1), 51, 2019 | 122 | 2019 |
| Hafnium binary alloys from experiments and first principles O Levy, GLW Hart, S Curtarolo Acta Materialia 58 (8), 2887-2897, 2010 | 121 | 2010 |
| The AFLOW library of crystallographic prototypes: part 2 D Hicks, MJ Mehl, E Gossett, C Toher, O Levy, RM Hanson, G Hart, ... Computational Materials Science 161, S1-S1011, 2019 | 120 | 2019 |
Curtarolo, StefanoDuke University在 nietzsche.mems.duke.edu 的电子邮件经过验证
