Curtarolo, Stefano
Curtarolo, Stefano
E-mailová adresa ověřena na: - Domovská stránka
Entropy-stabilized oxides
CM Rost, E Sachet, T Borman, A Moballegh, EC Dickey, D Hou, JL Jones, ...
Nature communications 6 (1), 8485, 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
High-throughput electronic band structure calculations: Challenges and tools
W Setyawan, S Curtarolo
Computational materials science 49 (2), 299-312, 2010
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
High-entropy ceramics
C Oses, C Toher, S Curtarolo
Nature Reviews Materials 5 (4), 295-309, 2020
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
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
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
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
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
QSAR without borders
EN Muratov, J Bajorath, RP Sheridan, IV Tetko, D Filimonov, V Poroikov, ...
Chemical Society Reviews 49 (11), 3525-3564, 2020
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
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
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
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
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
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
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
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
Machine learning for alloys
GLW Hart, T Mueller, C Toher, S Curtarolo
Nature Reviews Materials 6 (8), 730-755, 2021
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Články 1–20