arXiv subjects

Guanghui Han

Publications and source records attributed to Guanghui Han.

4 recordsLinked to original sources

arXiv2025

Layer-dependent field-free switching of N\'eel vector in a van der Waals antiferromagnet

Two-dimensional antiferromagnets, combining the dual advantages of van der Waals (vdW) and antiferromagnetic materials, provide an unprecedented platform for exploring emergent spin-related phenomena. However, electrical manipulation of N\'eel vectors in vdW antiferromagnets - the cornerstone of antiferromagnetic spintronics - remains challenging. Here, we report layer-dependent electrical switching of the N\'eel vector in an A-type vdW antiferromagnet $(Fe,Co)_3$$GaTe_2$ (FCGT) with perpendicular magnetic anisotropy. The N\'eel vector of FCGT with odd-number vdW layers can be 180{\deg} reversed via spin-orbit torques. Furthermore, we achieve field-free switching in an all-vdW, all-antiferromagnet heterostructure of FCGT/CrSBr in which the noncollinear interfacial spin texture breaks the mirror symmetry. Our results establish layer-controlled spin symmetries and interfacial spin engineering as universal paradigms for manipulating antiferromagnetic order, paving the way for realising reliable and efficient vdW antiferromagnetic devices.

cond-mat.mes-hall↗

arXiv2025

Semiconducting behaviors at epitaxial Ca0.5TaO3 interfaces

Emergent phenomena take place in symmetry-breaking systems, notably the recently discovered two-dimensional electron gas and its tunable superconductivities near the KTaO3 interfaces. Here, we synthesized perovskite Ca0.5TaO3 films along both [001] and [111] orientations. Different from the KTaO3 system, Ca0.5TaO3 films show semiconducting behaviors when capped with LaAlO3 films in both [001] and [111] orientations. By growing films at higher temperatures, more oxygen vacancies can be introduced, and the carrier density can be tuned from ~ 1014 cm-2 to ~ 1016 cm-2. Another difference is that the superconducting transition temperature Tc in KTaO3 (111) increases linearly along with its carrier density, while the Ca0.5TaO3 (111) remains semiconducting when carrier density ranges from ~ 1014 cm-2 to ~ 1016 cm-2. Based on the density function theory calculation, Ca0.5TaO3 and KTaO3 show similar electronic band structures. According to the energy-dispersive X-ray spectroscopy, we found heavy Sr diffusion from the substrate to the Ca0.5TaO3 layer, which may destroy the interfacial conductivity. Our work demonstrates that besides the oxygen vacancies, electronic transport is sensitive to the atomic intermixing near the interface in tantulates.

cond-mat.mtrl-sci↗

arXiv2024

Ferromagnetism and structural phase transition in monoclinic FeGe film

Binary compound FeGe hosts multiple structures, from cubic and hexagonal to monoclinic. Compared to the well-known skyrmion lattice in the cubic phase and the antiferromagnetic charge-density wave in the hexagonal phase, the monoclinic FeGe is less explored. Here, we synthesized the monoclinic FeGe films on Al2O3 (001) and studied their structural, magnetic, and transport properties. X-ray diffraction and transmission electron microscopy characterizations indicate that the FeGe films are epitaxial to the substrate. Unlike the antiferromagnetic bulk, the monoclinic FeGe films are ferromagnetic with Curie-temperature as high as ~ 800 K, contributing to the anomalous Hall effect in the transport measurements. Similar to the hexagonal FeGe, we captured a structural phase transition in the monoclinic FeGe films at ~ 100 K in real and reciprocal spaces by transmission electron microscope. Our work enriches the phase diagram of the FeGe family and suggests that FeGe offers an ideal platform for studying multiphase transitions and related device applications.

cond-mat.mtrl-sci↗

arXiv2020

PiaNet: A pyramid input augmented convolutional neural network for GGO detection in 3D lung CT scans

This paper proposes a new convolutional neural network with multiscale processing for detecting ground-glass opacity (GGO) nodules in 3D computed tomography (CT) images, which is referred to as PiaNet for short. PiaNet consists of a feature-extraction module and a prediction module. The former module is constructed by introducing pyramid multiscale source connections into a contracting-expanding structure. The latter module includes a bounding-box regressor and a classifier that are employed to simultaneously recognize GGO nodules and estimate bounding boxes at multiple scales. To train the proposed PiaNet, a two-stage transfer learning strategy is developed. In the first stage, the feature-extraction module is embedded into a classifier network that is trained on a large data set of GGO and non-GGO patches, which are generated by performing data augmentation from a small number of annotated CT scans. In the second stage, the pretrained feature-extraction module is loaded into PiaNet, and then PiaNet is fine-tuned using the annotated CT scans. We evaluate the proposed PiaNet on the LIDC-IDRI data set. The experimental results demonstrate that our method outperforms state-of-the-art counterparts, including the Subsolid CAD and Aidence systems and S4ND and GA-SSD methods. PiaNet achieves a sensitivity of 91.75% with only one false positive per scan

cs.CV↗