Gus L. W. Hart

Cytowane przez

	Wszystkie	Od 2020
Cytowania	11517	6452
h-indeks	41	31
i10-indeks	73	53

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Curtarolo, StefanoDuke UniversityZweryfikowany adres z nietzsche.mems.duke.edu
Lance J. NelsonBrigham Young University - IdahoZweryfikowany adres z byui.edu
Alex ZungerUniversity of Colorado ,Boulder,Colorado.Renewable and Sustainable Energy InstituteZweryfikowany adres z colorado.edu
Michael MehlDuke UniversityZweryfikowany adres z duke.edu
Conrad RosenbrockBrigham Young UniversityZweryfikowany adres z byu.edu
Marco Buongiorno NardelliRegents Professor of Physics and Composition, UNTZweryfikowany adres z unt.edu
Cormac ToherAssistant ProfessorZweryfikowany adres z utdallas.edu
wahyu setyawanPacific Northwest National LaboratoryZweryfikowany adres z pnnl.gov
Stefano SanvitoTrinity College DublinZweryfikowany adres z tcd.ie
Oliver BecksteinCenter for Biological Physics, Department of Physics, Arizona State UniversityZweryfikowany adres z asu.edu
Wiley S MorganGraduate Student Brigham Young UniversityZweryfikowany adres z byu.edu
Kesong YangProfessor, University of California San DiegoZweryfikowany adres z ucsd.edu
Alexander ShapeevSkolkovo Institute of Science and TechnologyZweryfikowany adres z shapeev.com
Natalio MingoCEA-GrenobleZweryfikowany adres z cea.fr
Brayden BekkerBYU, Brigham Young University, PhysicsZweryfikowany adres z byu.edu
Gabor CsanyiProfessor of Molecular Modelling, Engineering Laboratory, University of CambridgeZweryfikowany adres z cam.ac.uk
Volker BlumAssociate Professor, MEMS Department - Duke University, Durham, NCZweryfikowany adres z duke.edu
David HicksDuke UniversityZweryfikowany adres z duke.edu
Vidvuds OzolinsProfessor of Applied Physics, Yale UniversityZweryfikowany adres z yale.edu
Corey OsesJohns Hopkins UniversityZweryfikowany adres z jhu.edu

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Gus L. W. Hart

Brigham Young University, Physics and Astronomy

Zweryfikowany adres z byu.edu - Strona główna

Biophysics algorithm development applied linear algebra machine learning computational science


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
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	2134	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	1411	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	1215	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	514	2001
Machine learning for alloys GLW Hart, T Mueller, C Toher, S Curtarolo Nature Reviews Materials 6 (8), 730-755, 2021	484	2021
Algorithm for generating derivative structures GLW Hart, RW Forcade Physical Review B—Condensed Matter and Materials Physics 77 (22), 224115, 2008	453	2008
Evolutionary approach for determining first-principles hamiltonians GLW Hart, V Blum, MJ Walorski, A Zunger Nature materials 4 (5), 391-394, 2005	375	2005
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	332	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	329	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	275	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	259	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	205	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	194	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	179	2009
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	142	2019
Generating derivative structures at a fixed concentration GLW Hart, LJ Nelson, RW Forcade Computational Materials Science 59, 101-107, 2012	138	2012
Electronic structure of BAs and boride III-V alloys GLW Hart, A Zunger Physical Review B 62 (20), 13522, 2000	136	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	130	2013
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	128	2019
Hafnium binary alloys from experiments and first principles O Levy, GLW Hart, S Curtarolo Acta Materialia 58 (8), 2887-2897, 2010	124	2010

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