Electronic Structure of Rare-Earth Nickelates from First-Principles



de

Éditeur :

Springer


Paru le : 2024-09-26



eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
160,49

Téléchargement immédiat
Dès validation de votre commande
Ajouter à ma liste d'envies
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

Description

This thesis demonstrates the value of theoretical approaches in the discovery of new superconducting materials. It reports a detailed study of the recently discovered nickel-oxide (nickelate) superconductors using multiple first-principles computational tools, from density functional theory to dynamical mean field theory. In the context of superconductivity, discoveries have generally been linked to serendipitous experimental discovery; this thesis reports some of the few examples of predictions of new superconductors that have later been realized in practice, a prime example of the significance of the methodology it expounds. Overall, it represents a seminal systematic work in the electronic structure theory of the emergent field of nickelate superconductivity.
Pages
102 pages
Collection
n.c
Parution
2024-09-26
Marque
Springer
EAN papier
9783031715471
EAN PDF
9783031715488

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
10
Taille du fichier
16271 Ko
Prix
160,49 €
EAN EPUB
9783031715488

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
10
Taille du fichier
24648 Ko
Prix
160,49 €

Harrison LaBollita is a computational condensed matter physicist whose research focuses on the electronic structure of strongly correlated materials. He obtained his PhD in Physics at Arizona State University under the supervision of Prof. Antia S. Botana, where he focused on superconductivity in nickel-oxides (nickelates). Harrison will continue researching strongly correlated materials as a postdoctoral fellow at the Flatiron Institute, a division of the Simons Foundation, in the fall of 2024.

Suggestions personnalisées