Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Aria Mansouri Tehrani"'
Autor:
Aria Mansouri Tehrani, Jian-Rui Soh, Jana Pásztorová, Maximilian E. Merkel, Ivica Živković, Henrik M. Rønnow, Nicola A. Spaldin
Publikováno v:
Physical Review Research, Vol 5, Iss 1, p L012010 (2023)
We examine the role of charge, structural, and spin degrees of freedom in the previously poorly understood phase transition in the 5d^{1} transition-metal double perovskite Cs_{2}TaCl_{6} using a combination of computational and experimental techniqu
Externí odkaz:
https://doaj.org/article/8f0f42a43a2f4b538bf0d497e3200a31
Autor:
Luca Schaufelberger, Maximilian E. Merkel, Aria Mansouri Tehrani, Nicola A. Spaldin, Claude Ederer
Publikováno v:
Physical Review Research, Vol 5, Iss 3, p 033172 (2023)
We present a method to constrain local charge multipoles within density-functional theory. Such multipoles quantify the anisotropy of the local charge distribution around atomic sites and can indicate potential hidden orders. Our method allows select
Externí odkaz:
https://doaj.org/article/c404c5ee3d674b57987dcc4ec1e46416
Autor:
Ramon Frey, Bastien F. Grosso, Pascal Fandré, Benjamin Mächler, Nicola A. Spaldin, Aria Mansouri Tehrani
Publikováno v:
Physical Review Research, Vol 5, Iss 2, p 023122 (2023)
We report the development of a combined machine learning and high-throughput density functional theory (DFT) framework to accelerate the search for new ferroelectric materials. The framework can predict potential ferroelectric compounds using only el
Externí odkaz:
https://doaj.org/article/7620cd2470574b9fa6cbde8cb3d5f70d
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-10 (2018)
Identifying phosphors with good thermal stability and quantum efficiency is a prerequisite to improve the performance of white LED light sources. Here, a combined machine learning and density functional theory method is introduced to identify next ge
Externí odkaz:
https://doaj.org/article/3702a80a2f9b445381a72ddd2dbb5fc9
Autor:
Marcus E. Parry, Jackson Hendry, Samantha Couper, Aria Mansouri Tehrani, Anton O. Oliynyk, Jakoah Brgoch, Lowell Miyagi, Taylor D. Sparks
Publikováno v:
Chemistry of Materials. 34:2569-2575
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eec73fac5e056c213160ac1637268130
https://doi.org/10.1021/acs.chemmater.1c03501
https://doi.org/10.1021/acs.chemmater.1c03501
Publikováno v:
Journal of Physics: Condensed Matter, 35 (24)
We address the degeneracy of the ground state multiplet on the 5d 1 Re6+ ion in double perovskite Ba2MgReO6 using a combination of specific heat measurements and density functional calculations. For Ba2MgReO6, two different ground state multiplets ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3961174f0fbf120922c9cb3fd10c116c
http://arxiv.org/abs/2210.13616
http://arxiv.org/abs/2210.13616
Publikováno v:
Annual Review of Materials Research. 50:27-48
The development of structural materials with outstanding mechanical response has long been sought for innumerable industrial, technological, and even biomedical applications. However, these compounds tend to derive their fascinating properties from a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::131a0f64b0e7ada671129962085b71a4
https://doi.org/10.1146/annurev-matsci-110519-094700
https://doi.org/10.1146/annurev-matsci-110519-094700
Autor:
Ziyan Zhang, Jakoah Brgoch, Gayatri Viswanathan, Sogol Lotfi, Aria Mansouri Tehrani, Kaitlyn Fortenberry
Publikováno v:
Matter. 3:261-272
Summary This work presents an approach to aid the discovery of inorganic solids by highlighting regions of underexplored yet likely productive composition space using machine learning. A support vector regression algorithm was constructed to determin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c6f7b8d82c2861599c2f27d30fb8b0c
https://doi.org/10.1016/j.matt.2020.05.002
https://doi.org/10.1016/j.matt.2020.05.002
Publikováno v:
The Journal of Physical Chemistry C. 124:4430-4437
Borides containing 4d or 5d transition metals are among the most common types of high hardness materials because of the high valence electron density of the metals combined with short, covalent mai...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa584f2147e5ec396362d1a1a7312c7c
https://doi.org/10.1021/acs.jpcc.9b11240
https://doi.org/10.1021/acs.jpcc.9b11240
Autor:
Ramon Frey, Bastien F. Grosso, Pascal Fandré, Benjamin Mächler, Nicola A. Spaldin, Aria Mansouri Tehrani
Publikováno v:
Physical Review Research, 5 (2)
We report the development of a combined machine learning and high-throughput density functional theory (DFT) framework to accelerate the search for new ferroelectric materials. The framework can predict potential ferroelectric compounds using only el
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::07f25b83c9742cd6c9f29c271cc5e231
http://arxiv.org/abs/2201.05668
http://arxiv.org/abs/2201.05668