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Two dimensional (2D) materials have emerged as promising functional materials with many applications such as semiconductors and photovoltaics because of their unique optoelectronic properties. While several thousand 2D materials have been…

Materials Science · Physics 2020-12-18 Yuqi Song , Edirisuriya M. Dilanga Siriwardane , Yong Zhao , Jianjun Hu

Superconductivity has been the focus of enormous research effort since its discovery more than a century ago. Yet, some features of this unique phenomenon remain poorly understood; prime among these is the connection between…

Topological insulators are new quantum states with helical gapless edge or surface states inside the bulk band gap.These topological surface states are robust against the weak time-reversal invariant perturbations, such as lattice…

Mesoscale and Nanoscale Physics · Physics 2013-08-07 Haijun Zhang , Shou-Cheng Zhang

Crystal-graph attention networks have emerged recently as remarkable tools for the prediction of thermodynamic stability and materials properties from unrelaxed crystal structures. Previous networks trained on two million materials…

The first-principles band theory paradigm has been a key player not only in the process of discovering new classes of topologically interesting materials, but also for identifying salient characteristics of topological states, enabling…

Mesoscale and Nanoscale Physics · Physics 2016-08-03 Arun Bansil , Hsin Lin , Tanmoy Das

We perform a computational screening for two-dimensional magnetic materials based on experimental bulk compounds present in the Inorganic Crystal Structure Database and Crystallography Open Database. A recently proposed geometric descriptor…

Materials Science · Physics 2020-12-04 Daniele Torelli , Hadeel Moustafa , Karsten W. Jacobsen , Thomas Olsen

The search for large band gap systems with dissipationless edge states is essential to developing materials that function under a wide range of temperatures. Two-dimensional (2D) topological insulators (TIs) have recently attracted…

Mesoscale and Nanoscale Physics · Physics 2018-10-10 Lauryn Wu , Kunming Gu , Qiliang Li

In this work we design and train deep neural networks to predict topological invariants for one-dimensional four-band insulators in AIII class whose topological invariant is the winding number, and two-dimensional two-band insulators in A…

Strongly Correlated Electrons · Physics 2018-08-07 Ning Sun , Jinmin Yi , Pengfei Zhang , Huitao Shen , Hui Zhai

Topological insulators [1-6] is a new quantum phase of matter with exotic properties such as dissipationless transport and protection against Anderson localization [7]. These new states of quantum matter could be one of the missing links…

Materials Science · Physics 2010-07-29 M. Klintenberg

The unusual electronic states found in topological materials can enable a new generation of devices and technologies, yet a long-standing challenge has been finding materials without deleterious parallel bulk conduction. This can arise…

Materials Science · Physics 2020-11-05 Matthew Brahlek

Significant advances have been made in predicting new topological materials using high-throughput empirical descriptors or symmetry-based indicators. To date, these approaches have been applied to materials in existing databases, and are…

We demonstrate the realization of topological band structures by exploiting the intrinsic spin-orbit coupling of dipolar interactions in combination with broken time-reversal symmetry. The system is based on polar molecules trapped in a…

To realize novel topological phases and to pursue potential applications in low-energy consumption spintronics, the study of magnetic topological materials is of great interest. Starting from the theory of nonmagnetic topological quantum…

Materials Science · Physics 2022-08-03 Jiacheng Gao , Zhaopeng Guo , Hongming Weng , Zhijun Wang

"Topological Quantum Chemistry (TQC) links the chemical and symmetry structure of a given material with its topological properties. This field tabulates the data of the 10398 real-space atomic limits of materials, and solves the…

Materials Science · Physics 2019-11-15 M. G. Vergniory , L. Elcoro , C. Felser , N. Regnault , B. A. Bernevig , Z. Wang

Topological insulator(TI) is a phase of matter discovered recently. Kane and Mele proposed this phase is distinguished from the ordinary band insulator by a Z2 topological invariant.2 Several authors have try to related this Z2 invariant to…

Materials Science · Physics 2011-03-01 Yidong Wu

The properties of electrons in magnetically ordered crystals are of interest both from the viewpoint of realizing novel topological phases, such as magnetic Weyl semimetals, and from the applications perspective of creating energy-efficient…

Strongly Correlated Electrons · Physics 2018-08-07 Haruki Watanabe , Hoi Chun Po , Ashvin Vishwanath

Two-dimensional 2-bands insulators breaking time reversal symmetry can present topological phases indexed by a topological invariant called the Chern number. Here we first propose an efficient procedure to determine this topological index.…

Mesoscale and Nanoscale Physics · Physics 2012-05-28 Doru Sticlet , Frederic Piéchon , Jean-Noël Fuchs , Pavel Kalugin , Pascal Simon

This work explores the topological properties of altermagnets, a novel class of collinear magnetic materials. We employ equivariant K-theory of magnetic groups and Hamiltonian models to formulate a robust $C^z_4 \mathbb{T}$ topological…

Materials Science · Physics 2025-03-03 Rafael Gonzalez-Hernandez , Higinio Serrano , Bernardo Uribe

Crystalline symmetries play an important role in the classification of band structures, and the rich variety of spatial symmetries in solids leads to various topological crystalline phases (TCPs). However, compared with topological…

Mesoscale and Nanoscale Physics · Physics 2019-03-12 Feng Tang , Hoi Chun Po , Ashvin Vishwanath , Xiangang Wan

The continuous effort towards topological quantum devices calls for an efficient and non-invasive method to assess the conformity of components in different topological phases. Here, we show that machine learning paves the way towards…

Disordered Systems and Neural Networks · Physics 2019-01-24 Marcello D. Caio , Marco Caccin , Paul Baireuther , Timo Hyart , Michel Fruchart