| Entropy-stabilized oxides CM Rost, E Sachet, T Borman, A Moballegh, EC Dickey, D Hou, JL Jones, ... Nature communications 6 (1), 8485, 2015 | 2537 | 2015 |
| 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 | 2118 | 2013 |
| High-throughput electronic band structure calculations: Challenges and tools W Setyawan, S Curtarolo Computational materials science 49 (2), 299-312, 2010 | 1788 | 2010 |
| High-entropy ceramics C Oses, C Toher, S Curtarolo Nature Reviews Materials 5 (4), 295-309, 2020 | 1503 | 2020 |
| 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 | 1401 | 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 | 1209 | 2012 |
| Charting the complete elastic properties of inorganic crystalline compounds M De Jong, W Chen, T Angsten, A Jain, R Notestine, A Gamst, M Sluiter, ... Scientific data 2 (1), 1-13, 2015 | 1066 | 2015 |
| High-entropy high-hardness metal carbides discovered by entropy descriptors P Sarker, T Harrington, C Toher, C Oses, M Samiee, JP Maria, ... Nature communications 9 (1), 4980, 2018 | 906 | 2018 |
| All The Catalytic Active Sites of MoS2 for Hydrogen Evolution G Li, D Zhang, Q Qiao, Y Yu, D Peterson, A Zafar, R Kumar, S Curtarolo, ... Journal of the American Chemical Society 138 (51), 16632-16638, 2016 | 824 | 2016 |
| QSAR without borders EN Muratov, J Bajorath, RP Sheridan, IV Tetko, D Filimonov, V Poroikov, ... Chemical Society Reviews 49 (11), 3525-3564, 2020 | 764 | 2020 |
| Convergence of multi-valley bands as the electronic origin of high thermoelectric performance in CoSb3 skutterudites Y Tang, ZM Gibbs, LA Agapito, G Li, HS Kim, MB Nardelli, S Curtarolo, ... Nature materials 14 (12), 1223-1228, 2015 | 759 | 2015 |
| SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates R Ouyang, S Curtarolo, E Ahmetcik, M Scheffler, LM Ghiringhelli Physical Review Materials 2 (8), 083802, 2018 | 750 | 2018 |
| Universal fragment descriptors for predicting properties of inorganic crystals O Isayev, C Oses, C Toher, E Gossett, S Curtarolo, A Tropsha Nature communications 8 (1), 15679, 2017 | 668 | 2017 |
| Phase stability and mechanical properties of novel high entropy transition metal carbides TJ Harrington, J Gild, P Sarker, C Toher, CM Rost, OF Dippo, C McElfresh, ... Acta Materialia 166, 271-280, 2019 | 624 | 2019 |
| Finding unprecedentedly low-thermal-conductivity half-Heusler semiconductors via high-throughput materials modeling J Carrete, W Li, N Mingo, S Wang, S Curtarolo Physical Review X 4 (1), 011019, 2014 | 602 | 2014 |
| Predicting crystal structures with data mining of quantum calculations S Curtarolo, D Morgan, K Persson, J Rodgers, G Ceder Physical review letters 91 (13), 135503, 2003 | 521 | 2003 |
| Machine learning for alloys GLW Hart, T Mueller, C Toher, S Curtarolo Nature Reviews Materials 6 (8), 730-755, 2021 | 479 | 2021 |
| Ab initio lattice stability in comparison with CALPHAD lattice stability Y Wang, S Curtarolo, C Jiang, R Arroyave, T Wang, G Ceder, LQ Chen, ... Calphad 28 (1), 79-90, 2004 | 459 | 2004 |
| Machine learning modeling of superconducting critical temperature V Stanev, C Oses, AG Kusne, E Rodriguez, J Paglione, S Curtarolo, ... npj Computational Materials 4 (1), 29, 2018 | 458 | 2018 |
| Accuracy of ab initio methods in predicting the crystal structures of metals: A review of 80 binary alloys S Curtarolo, D Morgan, G Ceder Calphad 29 (3), 163-211, 2005 | 405 | 2005 |
Cormac ToherAssistant ProfessorEmail yang diverifikasi di utdallas.edu