Zobrazeno 1 - 10
of 163
pro vyhledávání: '"Jesús Carrete"'
Autor:
Xiaoqi Zhou, Zhisen Meng, Sylvain Picaud, Michel Devel, Jesús Carrete, Georg K. H. Madsen, Yulu Zhou, Zhao Wang
Publikováno v:
ACS Omega, Vol 6, Iss 42, Pp 27898-27904 (2021)
Externí odkaz:
https://doaj.org/article/eeb9541ff5824f5a852205acebdb9477
Autor:
Mauro Fava, Nakib Haider Protik, Chunhua Li, Navaneetha Krishnan Ravichandran, Jesús Carrete, Ambroise van Roekeghem, Georg K. H. Madsen, Natalio Mingo, David Broido
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-7 (2021)
Abstract The promise enabled by boron arsenide’s (BAs) high thermal conductivity (κ) in power electronics cannot be assessed without taking into account the reduction incurred when doping the material. Using first principles calculations, we deter
Externí odkaz:
https://doaj.org/article/987984f27ecc4eb2844b7fc366b127b9
Autor:
JESÚS CARRETE MONTAÑA
Publikováno v:
Revista Galega de Economía, Vol 21, Iss 1, Pp 1-31 (2012)
This work contains a brief outline of the history of physics, starting from the little that can be speculated about the proto-scientific attitudes of prehistoric men and ending with the most important developments experienced by the field in the 20th
Externí odkaz:
https://doaj.org/article/36a8352055c64001ba2d3657c3b85f48
Publikováno v:
Physical Review X, Vol 6, Iss 4, p 041061 (2016)
Using finite-temperature phonon calculations and machine-learning methods, we assess the mechanical stability of about 400 semiconducting oxides and fluorides with cubic perovskite structures at 0, 300, and 1000 K. We find 92 mechanically stable comp
Externí odkaz:
https://doaj.org/article/a9b8a120f4ab4c04ba2d4161fbbe0508
Publikováno v:
Physical Review X, Vol 4, Iss 1, p 011019 (2014)
The lattice thermal conductivity (κ_{ω}) is a key property for many potential applications of compounds. Discovery of materials with very low or high κ_{ω} remains an experimental challenge due to high costs and time-consuming synthesis procedure
Externí odkaz:
https://doaj.org/article/1fa9bf1a1bc04cee988eaf84865527fa
Publikováno v:
ACS Applied Energy Materials. 6:3944-3952
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2097e05ba956c73e41c2809d188c4bfb
https://doi.org/10.1021/acsaem.3c00110
https://doi.org/10.1021/acsaem.3c00110
Publikováno v:
The Journal of Chemical Physics. 158
A reliable uncertainty estimator is a key ingredient in the successful use of machine-learning force fields for predictive calculations. Important considerations are correlation with error, overhead during training and inference, and efficient workfl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e618196c35c7df1bbc4a05f3331506c5
https://doi.org/10.1063/5.0146905
https://doi.org/10.1063/5.0146905
Publikováno v:
Physical Review B. 107
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2cadd82b6671db4e0f0701d266a5a4ad
https://doi.org/10.1103/physrevb.107.184111
https://doi.org/10.1103/physrevb.107.184111
Autor:
Ralf Wanzenböck, Marco Arrigoni, Sebastian Bichelmaier, Florian Buchner, Jesús Carrete, Georg K. H. Madsen
Publikováno v:
Digital Discovery. 1:703-710
The covariance matrix adaptation evolution strategy (CMA-ES) and a fully automatically differentiable, transferable neural-network force field are combined to explore TiOx overlayer structures on SrTiO3(110) 3×1, 4×1 and 5×1 surfaces.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e3b8466bc950da85c068b4e65b2114f
https://doi.org/10.1039/d2dd00072e
https://doi.org/10.1039/d2dd00072e