7,258 research outputs found
Independent tuning of electronic properties and induced ferromagnetism in topological insulators with heterostructure approach
The quantum anomalous Hall effect (QAHE) has been recently demonstrated in
Cr- and V-doped three-dimensional topological insulators (TIs) at temperatures
below 100 mK. In those materials, the spins of unfilled d-electrons in the
transition metal dopants are exchange coupled to develop a long-range
ferromagnetic order, which is essential for realizing QAHE. However, the
addition of random dopants does not only introduce excess charge carriers that
require readjusting the Bi/Sb ratio, but also unavoidably introduces
paramagnetic spins that can adversely affect the chiral edge transport in QAHE.
In this work, we show a heterostructure approach to independently tune the
electronic and magnetic properties of the topological surface states in
(BixSb1-x)2Te3 without resorting to random doping of transition metal elements.
In heterostructures consisting of a thin (BixSb1-x)2Te3 TI film and yttrium
iron garnet (YIG), a high Curie temperature (~ 550 K) magnetic insulator, we
find that the TI surface in contact with YIG becomes ferromagnetic via
proximity coupling which is revealed by the anomalous Hall effect (AHE). The
Curie temperature of the magnetized TI surface ranges from 20 to 150 K but is
uncorrelated with the Bi fraction x in (BixSb1-x)2Te3. In contrast, as x is
varied, the AHE resistivity scales with the longitudinal resistivity. In this
approach, we decouple the electronic properties from the induced ferromagnetism
in TI. The independent optimization provides a pathway for realizing QAHE at
higher temperatures, which is important for novel spintronic device
applications.Comment: Accepted by Nano Letter
Similarities and differences of functional connectivity in drug-naïve, first-episode adolescent and young adult with major depressive disorder and schizophrenia
Major depressive disorder (MDD) and schizophrenia (SZ) are considered two distinct psychiatric disorders. Yet, they have considerable overlap in symptomatology and clinical features, particularly in the initial phases of illness. The amygdala and prefrontal cortex (PFC) appear to have critical roles in these disorders; however, abnormalities appear to manifest differently. In our study forty-nine drug-naïve, first-episode MDD, 45 drug-naïve, first-episode SZ, and 50 healthy control (HC) participants from 13 to 30 years old underwent resting-state functional magnetic resonance imaging. Functional connectivity (FC) between the amygdala and PFC was compared among the three groups. Significant differences in FC were observed between the amygdala and ventral PFC (VPFC), dorsolateral PFC (DLPFC), and dorsal anterior cingulated cortex (dACC) among the three groups. Further analyses demonstrated that MDD showed decreased amygdala-VPFC FC and SZ had reductions in amygdala-dACC FC. Both the diagnostic groups had significantly decreased amygdala-DLPFC FC. These indicate abnormalities in amygdala-PFC FC and further support the importance of the interaction between the amygdala and PFC in adolescents and young adults with these disorders. Additionally, the alterations in amygdala-PFC FC may underlie the initial similarities observed between MDD and SZ and suggest potential markers of differentiation between the disorders at first onset
Dirac-Surface-State Modulated Spin Dynamics in a Ferrimagnetic Insulator at Room Temperature
This work demonstrates dramatically modified spin dynamics of magnetic
insulator (MI) by the spin-momentum locked Dirac surface states of the adjacent
topological insulator (TI) which can be harnessed for spintronic applications.
As the Bi-concentration x is systematically tuned in 5 nm thick (BixSb1-x)2Te3
TI film, the weight of the surface relative to bulk states peaks at x = 0.32
when the chemical potential approaches the Dirac point. At this concentration,
the Gilbert damping constant of the precessing magnetization in 10 nm thick
Y3Fe5O12 MI film in the MI/TI heterostructures is enhanced by an order of
magnitude, the largest among all concentrations. In addition, the MI acquires
additional strong magnetic anisotropy that favors the in-plane orientation with
similar Bi-concentration dependence. These extraordinary effects of the Dirac
surface states distinguish TI from other materials such as heavy metals in
modulating spin dynamics of the neighboring magnetic layer
Object Detection in Hyperspectral Image via Unified Spectral-Spatial Feature Aggregation
Deep learning-based hyperspectral image (HSI) classification and object
detection techniques have gained significant attention due to their vital role
in image content analysis, interpretation, and wider HSI applications. However,
current hyperspectral object detection approaches predominantly emphasize
either spectral or spatial information, overlooking the valuable complementary
relationship between these two aspects. In this study, we present a novel
\textbf{S}pectral-\textbf{S}patial \textbf{A}ggregation (S2ADet) object
detector that effectively harnesses the rich spectral and spatial complementary
information inherent in hyperspectral images. S2ADet comprises a hyperspectral
information decoupling (HID) module, a two-stream feature extraction network,
and a one-stage detection head. The HID module processes hyperspectral images
by aggregating spectral and spatial information via band selection and
principal components analysis, consequently reducing redundancy. Based on the
acquired spatial and spectral aggregation information, we propose a feature
aggregation two-stream network for interacting spectral-spatial features.
Furthermore, to address the limitations of existing databases, we annotate an
extensive dataset, designated as HOD3K, containing 3,242 hyperspectral images
captured across diverse real-world scenes and encompassing three object
classes. These images possess a resolution of 512x256 pixels and cover 16 bands
ranging from 470 nm to 620 nm. Comprehensive experiments on two datasets
demonstrate that S2ADet surpasses existing state-of-the-art methods, achieving
robust and reliable results. The demo code and dataset of this work are
publicly available at \url{https://github.com/hexiao-cs/S2ADet}
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