A5005498479- Advanced Condensed Matter Physics
- Magnetic and transport properties of perovskites and related materials
- Multiferroics and related materials
- Ferroelectric and Piezoelectric Materials
- Electronic and Structural Properties of Oxides
- Colorectal Cancer Screening and Detection
- COVID-19 diagnosis using AI
- AI in cancer detection
- Advanced Neural Network Applications
- Anomaly Detection Techniques and Applications
- Advancements in Battery Materials
- Advanced Battery Materials and Technologies
- Advanced Thermoelectric Materials and Devices
- Image Retrieval and Classification Techniques
- Radiomics and Machine Learning in Medical Imaging
- Wireless Signal Modulation Classification
- Neural Networks and Applications
- Adversarial Robustness in Machine Learning
- Chalcogenide Semiconductor Thin Films
- Spatial Cognition and Navigation
- Spacecraft and Cryogenic Technologies
- Human Pose and Action Recognition
- Dielectric materials and actuators
- Geography Education and Pedagogy
- E-commerce and Technology Innovations
Hefei National Center for Physical Sciences at Nanoscale
2020-2025
University of Science and Technology of China
2019-2025
Chinese University of Hong Kong, Shenzhen
2023-2024
Central South University
2024
University of Hong Kong
2024
University of Shanghai for Science and Technology
2024
Yanshan University
2023
Shenzhen Research Institute of Big Data
2023
Anhui University
2023
Shanghai Jiao Tong University
2021-2022
Abstract Controllable engineering of thin lithium (Li) metal is essential for increasing the energy density solid-state batteries and clarifying interfacial evolution mechanisms a negative electrode. However, fabricating electrode faces significant challenges due to fragility high viscosity Li metal. Herein, through facile treatment Ta-doped 7 La 3 Zr 2 O 12 (LLZTO) with trifluoromethanesulfonic acid, its surface CO species converted into lithiophilic layer LiCF SO LiF components. It enables...
Tertiary structure-based RNA design plays a crucial role in synthetic biology and therapeutics. While existing methods have explored structure-to-sequence mappings, they focus solely on structures overlook the of complex-level information, which is for effective design. To address this limitation, we propose Complex-Aware tertiary Design model, CARD, that integrates information to enhance sequence be specific, our method incorporates protein features extracted by language model (e.g.,...
Abstract Topotactic reduction of perovskite oxides offers a powerful approach for discovering novel phenomena, such as superconducting infinite‐layer nickelates and polar metallicity, is commonly accompanied by the emergence multiple valence states and/or complex crystal fields transition metals. However, understanding interplay between chemistry, electronic structure, physical properties at spin‐ orbital‐resolved levels in these reduced systems remains elusive. Here, x‐ray absorption...
A novel route to construct stable anti-adhesion surfaces was explored via click chemistry between the macromolecules and anchoring compound DMA various substrates.
Strongly correlated perovskite oxides exhibit a plethera of intriguing phenomena and stimulate great potential for multifunctional device applications. Utilizing tunable uniaxial strain, rather than biaxial or anisotropic delivered from the crystallography single crystal substrate to modify ground state strongly has rarely been addressed phase-space control. Here, we show that physical properties La2/3Ca1/3MnO3 (LCMO) films are remarkably different depending on crystallographic orientations...
Abstract Tangible cultural heritage is rich in historical, artistic and scientific value, but due to its own characteristics the constraints of museum displays, key issue facing us today how utilize activate enhance experience learning interest audience. Focusing on Chinese treasure, chimes, this article innovatively proposes an interaction system based digital augmented projection somatosensory technology empower aesthetic expression knowledge dissemination chimes. On basis, a series...
(K,Na)NbO3-based lead-free ferroelectric materials are highly desired in modern electronic applications and have long been considered as a strong candidate for replacing (Pb,Zr)TiO3, but most of them deficient large remnant polarization decent thermal stability. Here, unique 0.95(K0.49Na0.49Li0.02)(Nb0.8Ta0.2)O3-0.05CaZrO3 with 2 wt % MnO2 addition (KNNLT-CZ-M) film special nanocomposite structures grown on La0.7Sr0.3MnO3-coated SrTiO3(001) substrate is demonstrated. The KNNLT-CZ-M films...
Abstract Hafnium‐based binary oxides have attracted considerable attention due to their robust ferroelectricity at the nanoscale and compatibility with silicon‐based electronic technologies. To further promote potential of Hafnium for practical device applications, it is essential effectively harness interplay between structural symmetry, domain configuration, ferroelectricity. Here, using Hf 0.5 Zr O 2 /La 0.67 Sr 0.33 MnO 3 (HZO/LSMO) heterostructures as a model system, anisotropic...
Abstract Research has shown that spatial perception is not only one of the essential abilities for success in science, technology, engineering, and mathematics (STEM), but also closely related to quality human existence. However, a variety reasons, many students' skills are less than ideal. In recent years, various video games showing great potential as low‐cost effective training tools improve educational level cognitive skills. This paper presented novel serious strategy game named Magic...
The effects of epitaxial strain on the properties 0.95(K0.49Na0.49Li0.02)(Ta0.2Nb0.8)O3-0.05CaZrO3 (KNNLT-CZ) thin films are investigated. La0.07Sr0.93SnO3 and SrRuO3 used as bottom electrodes to provide in-plane tensile compressive stress, respectively. Our results show that La0.07Sr0.93SnO3-buffered KNNLT-CZ mostly strain-relaxed with an orthorhombic (O) tetragonal (T) mixed phase a tetragonality 1.002, which have twice remnant polarization (2Pr) 14.29 μC/cm2, effective piezoelectric...
Here, using various substrates, we demonstrate that the in-plane uniaxial strain engineering can enhance Jahn-Teller distortions and promote selective orbital occupancy to induce an emergent antiferromagnetic insulating (AFI) phase at x = 1/3 of La1-xCaxMnO3. Such AFI depends not only on magnitude epitaxial but also symmetry substrates. Using large imparted by DyScO3(001) substrate, ground state is achieved in a wide range doping levels (0 ≤ 1/2), leaving extended diagram. Moreover, it found...
Despite simplicity, stochastic gradient descent (SGD)-like algorithms are successful in training deep neural networks (DNNs). Among various attempts to improve SGD, weight averaging (WA), which averages the weights of multiple models, has recently received much attention literature. Broadly, WA falls into two categories: 1) online WA, models trained parallel, is designed for reducing communication overhead parallel mini-batch SGD and 2) offline one model at different checkpoints, typically...
Abstract The electronic structure of constituent layers and the spin channel propagating electrons are critical factors that affect magnitude sign magnetoresistance (MR) in synthetic antiferromagnets (SAFMs), which important for spintronic applications. However, all‐oxide‐based SAFMs, where there is strong coupling between multiple degrees freedom, transport becomes more complex remains elusive. Here, using ultrathin half‐metallic manganite/doped ruthenate SAFMs as a model system, three...
Accurate polyp detection is critical for early colorectal cancer diagnosis. Although remarkable progress has been achieved in recent years, the complex colon environment and concealed polyps with unclear boundaries still pose severe challenges this area. Existing methods either involve computationally expensive context aggregation or lack prior modeling of polyps, resulting poor performance challenging cases. In paper, we propose Enhanced CenterNet Contrastive Learning (ECC-PolypDet), a...
Network pruning is an architecture search process to determine the state (remove/remain) of neurons in network. It a com- binatorial optimization problem, and this combinatorial optimiza- tion problem NP-hard. Most existing methods prune channels/neurons based on assumption that they are indepen- dent However, there exists dependency among chan- nels/neurons. We try solve by evolutionary algorithm (EA). traditional EA can't be used directly into deep neural networks (DNNs) because dimension...
Time Series Classification (TSC) received wide attention in machine learning and data mining, arise a range of fields, such as scheduling, logistics, medical health etc. How to overcome the noise time series datasets is one key challenges TSC. In this paper, we propose hybrid Residual Network (ResNet) with genetic algorithm-based network structure optimization for robust TSC, which named GA-ResNet. Although ways obtain an effective deep neural model, but NP-hard problem. We design algorithm...
With the improvement of human requirements for quality life, economic development and urbanization, automatic pricing replenishment decisions vegetable categories single products in supermarkets have more reasonable planning. To optimize profitability supermarkets, help them expand their market share, determine position, this paper aims to explore correlation between products, set a strategy supermarkets. Firstly, according distribution law interrelationship sales volume various vegetables,...
AI-assisted lesion detection models play a crucial role in the early screening of cancer. However, previous image-based ignore inter-frame contextual information present videos. On other hand, video-based capture context but are computationally expensive. To mitigate this contradiction, we delve into Video-to-Image knowledge distillation leveraging DEtection TRansformer (V2I-DETR) for task medical video detection. V2I-DETR adopts teacher-student network paradigm. The teacher aims at...
Ultrasound imaging is widely used in clinical diagnosis due to its non-invasive nature and real-time capabilities. However, conventional ultrasound diagnostics face several limitations, including high dependence on physician expertise suboptimal image quality, which complicates interpretation increases the likelihood of diagnostic errors. Artificial intelligence (AI) has emerged as a promising solution enhance diagnosis, particularly detecting abnormalities across various biomedical...
Accurate polyp detection is critical for early colorectal cancer diagnosis. Although remarkable progress has been achieved in recent years, the complex colon environment and concealed polyps with unclear boundaries still pose severe challenges this area. Existing methods either involve computationally expensive context aggregation or lack prior modeling of polyps, resulting poor performance challenging cases. In paper, we propose Enhanced CenterNet Contrastive Learning (ECC-PolypDet), a...