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Experimental results on the metal-insulator transition and related phenomena in strongly interacting two-dimensional electron systems are discussed. Special attention is given to recent results for the strongly enhanced spin susceptibility,…

Strongly Correlated Electrons · Physics 2016-11-18 A. A. Shashkin , S. V. Kravchenko

Metal additive manufacturing enables unprecedented design freedom and the production of customized, complex components. However, the rapid melting and solidification dynamics inherent to metal AM processes generate heterogeneous,…

Machine Learning · Computer Science 2025-05-05 D. Patel , R. Sharma , Y. B. Guo

We present a theory of the metal-insulator transition in a disordered two-dimensional electron gas. A quantum critical point, separating the metallic phase which is stabilized by electronic interactions, from the insulating phase where…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alexander Punnoose , Alexander M. Finkel'stein

Correlated electron systems are among the centerpieces of modern condensed matter sciences, where many interesting physical phenomena, such as metal-insulator transition and high-Tc superconductivity appear. Recent efforts have been focused…

Strongly Correlated Electrons · Physics 2013-08-05 You Zhou , Shriram Ramanathan

The dominant majority of the hundreds of available spin-crossover compounds, including the technologically most promising ones, are based on the Earth-abundant metal iron, making these switches particularly appealing in terms of sustainable…

Other Condensed Matter · Physics 2020-07-24 Latévi Max Lawson Daku , Mark Earl Casida

Due the alarming rate of climate change, the implementation of efficient CO$_2$ capture has become crucial. This project aims to create an algorithm that predicts the uptake of CO$_2$ adsorbing Metal-Organic Frameworks (MOFs) by using…

Machine Learning · Computer Science 2021-10-13 Mahati Manda

Metal-insulator transition (MIT) is one of the most conspicuous phenomena in correlated electron systems. However such transition has rarely been induced by an external magnetic field as the field scale is normally too small compared with…

Strongly Correlated Electrons · Physics 2020-12-02 Guangqiang Wang , Guoqing Chang , Huibin Zhou , Wenlong Ma , Hsin Lin , M. Zahid Hasan , Su-Yang Xu , Shuang Jia

The calculation of electronic properties of materials is an important task of solid state theory, albeit particularly difficult if electronic correlations are strong, for example in transition metals, their oxides and in f-electron systems.…

Strongly Correlated Electrons · Physics 2009-09-29 K. Held

We use density functional theory plus dynamical mean-field theory (DFT+DMFT) to study multiple control parameters for tuning the metal-insulator transition (MIT) in CaVO$_3$ thin films. We focus on separating the effects resulting from…

Strongly Correlated Electrons · Physics 2018-02-14 Sophie Beck , Gabriele Sclauzero , Uday Chopra , Claude Ederer

The discovery of the metal-insulator transition (MIT) in two-dimensional (2D) electron systems challenged the veracity of one of the most influential conjectures in the physics of disordered electrons, which states that `in two dimensions,…

Strongly Correlated Electrons · Physics 2017-12-06 S. Anissimova , S. V. Kravchenko , A. Punnoose , A. M. Finkel'stein , T. M. Klapwijk

We present the results of numerical studies for selected materials with strongly correlated electrons using a combination of the local-density approximation and dynamical mean-field theory (DMFT). For the solution of the DMFT equations a…

Strongly Correlated Electrons · Physics 2011-02-11 Arno P. Kampf , Marcus Kollar , Jan Kunes , Michael Sentef , Dieter Vollhardt

Metal-to-insulator transitions (MITs), particularly near room temperature, have been extensively studied in nonmagnetic and conventional ferromagnetic and antiferromagnetic systems, yet the co-emergence of MIT and altermagnetism (AM)…

The metal-insulator transition (MIT) remains among the most thoroughly studied phenomena in solid state physics, but the complexity of the phenomena, which usually involves cooperation of many degrees of freedom including orbitals,…

Strongly Correlated Electrons · Physics 2019-01-29 Kristjan Haule , Gheorghe L. Pascut

We search for new superhard B-N-O compounds with an iterative machine learning (ML) procedure, where ML models are trained using sample crystal structures from evolutionary algorithm. We first use cohesive energy to evaluate the…

Materials Science · Physics 2022-06-22 Wei-Chih Chen , Yogesh K. Vohra , Cheng-Chien Chen

On demand current-driven insulator-to-metal transition (IMT) is pivotal for the next generation of energy-efficient and scalable microelectronics. IMT is a key phenomenon observed in various quantum materials, and it is enabled by the…

We present a model for the metal-insulator transition in 2D, observed in the recent years. Our starting point consists of two ingredients only, which are ubiquitous in the experiments: Coulomb interactions and weak disorder spin-orbit…

Disordered Systems and Neural Networks · Physics 2015-06-24 George Kastrinakis

Machine learning has revolutionized many fields, including materials science. However, predicting properties of crystalline materials using machine learning faces challenges in input encoding, output versatility, and interpretability. We…

Materials Science · Physics 2025-05-22 Haosheng Xu , Dongheng Qian , Jing Wang

We investigated the interdependence of the effects of disorder and carrier correlations on the metal-insulator transition in two-dimensional electronic systems. We present a quantitative metal-insulator phase diagram. Depending on the…

Strongly Correlated Electrons · Physics 2009-10-31 J. S. Thakur , D. Neilson

Electronic and structural degrees of freedom are often intimately coupled in strongly correlated systems, which result in intriguing macroscopic and microscopic phenomena. Using the well-studied material VO$_2$ as a prototype, here we…

Diffusion models promise to accelerate material design by directly generating novel structures with desired properties, but existing approaches typically require expensive and substantial labeled data ($>$10,000) and lack adaptability. Here…

Chemical Physics · Physics 2025-11-06 Junwu Chen , Jeff Guo , Edvin Fako , Philippe Schwaller
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