4.5 Article

Untrained Physically Informed Neural Network for Image Reconstruction of Magnetic Field Sources

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Physics, Multidisciplinary

Imaging phonon-mediated hydrodynamic flow in WTe2

Uri Vool et al.

Summary: In this study, current flow in the layered semimetal tungsten ditelluride was investigated by imaging the local magnetic field, revealing non-uniform current density indicative of hydrodynamic flow, with the strongest effects observed around 20 K. Ab initio calculations suggest that electron-electron interactions are predominantly mediated by phonons rather than solely the Coulomb interaction, offering a promising avenue for the search for hydrodynamic flow and prominent electron interactions in high-carrier-density materials.

NATURE PHYSICS (2021)

Article Computer Science, Interdisciplinary Applications

Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis

Mohammad Amin Nabian et al.

JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING (2020)

Article Chemistry, Multidisciplinary

Imaging Domain Reversal in an Ultrathin Van der Waals Ferromagnet

David A. Broadway et al.

ADVANCED MATERIALS (2020)

Article Multidisciplinary Sciences

Imaging viscous flow of the Dirac fluid in graphene

Mark J. H. Ku et al.

NATURE (2020)

Article Optics

DeepCGH: 3D computer-generated holography using deep learning

M. Hossein Eybposh et al.

OPTICS EXPRESS (2020)

Article Computer Science, Interdisciplinary Applications

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

M. Raissi et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2019)

Article Multidisciplinary Sciences

Probing magnetism in 2D materials at the nanoscale with single-spin microscopy

L. Thiel et al.

SCIENCE (2019)

Article Mathematics

Solving inverse problems using data-driven models

Simon Arridge et al.

ACTA NUMERICA (2019)

Article Mathematics, Applied

SWITCHNET: A NEURAL NETWORK MODEL FOR FORWARD AND INVERSE SCATTERING PROBLEMS

Yuehaw Khoo et al.

SIAM JOURNAL ON SCIENTIFIC COMPUTING (2019)

Article Engineering, Electrical & Electronic

Using Deep Neural Networks for Inverse Problems in Imaging Beyond analytical methods

Alice Lucas et al.

IEEE SIGNAL PROCESSING MAGAZINE (2018)

Review Nanoscience & Nanotechnology

Probing condensed matter physics with magnetometry based on nitrogen-vacancy centres in diamond

Francesco Casola et al.

NATURE REVIEWS MATERIALS (2018)

Review Multidisciplinary Sciences

Magnetism in two-dimensional van der Waals materials

Kenneth S. Burch et al.

NATURE (2018)

Article Multidisciplinary Sciences

Three-dimensional magnetization structures revealed with X-ray vector nanotomography

Claire Donnelly et al.

NATURE (2017)

Article Multidisciplinary Sciences

Quantum imaging of current flow in graphene

Jean-Philippe Tetienne et al.

SCIENCE ADVANCES (2017)

Review Nanoscience & Nanotechnology

Nanoscale magnetic skyrmions in metallic films and multilayers: a new twist for spintronics

Roland Wiesendanger

NATURE REVIEWS MATERIALS (2016)

Article Nanoscience & Nanotechnology

A scanning superconducting quantum interference device with single electron spin sensitivity

Denis Vasyukov et al.

NATURE NANOTECHNOLOGY (2013)

Article Chemistry, Multidisciplinary

Varied Magnetic Phases in a van der Waals Easy-Plane Antiferromagnet Revealed by Nitrogen-Vacancy Center Microscopy

Alexander J. Healey et al.

Summary: This study utilized widefield nitrogen vacancy (NV) center magnetic imaging to measure the properties of individual flakes of CuCrP2S6, showing the behavior crossover between in-plane ferromagnetism in thin flakes and bulk behavior dominated by a low-field spin-flop transition. The presence of surface anisotropies in van der Waals magnets is attributed to the sample preparation process or exposure to the ambient environment.