Machines for Materials and Materials for Machines: Metal-Insulator Transitions and Artificial Intelligence
In this perspective, we discuss the current and future impact of artificial intelligence and machine learning for the purposes of better understanding phase transitions, particularly in correlated electron materials. We take as a model system the rare-earth nickelates, famous for their thermally-dri...
Main Authors: | del Valle, J. (Author), Fowlie, J. (Author), Georgescu, A.B (Author), Mundet, B. (Author), Tückmantel, P. (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2021
|
Subjects: | |
Online Access: | View Fulltext in Publisher |
Similar Items
-
THE SURFACE RELIEF ANALISIS OF Sm(Co, Cu)5 SINGLE CRYSTALS BY ATOMIC–FORCE MYCROSCOPY
by: Yu.V. Kuznetsova, et al.
Published: (2012-12-01) -
STM probe on the surface electronic states of spin-orbit coupled materials
by: Zhou, Wenwen
Published: (2014) -
Spectroscopy of the Temperature and Current Driven Metal-Insulator Transition in Ca₂RuO₄
by: Cheng, Minghao
Published: (2020) -
Slowly folding surface extension in the prototypic avian hepatitis B virus capsid governs stability
by: Cihan Makbul, et al.
Published: (2020-08-01) -
High temperature machine: Characterization of materials for the electrical insulation
by: Lecointe Jean-Philippe, et al.
Published: (2020-10-01)