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Flexible infrared image fiber bundles (FBs) are capable of delivering thermal images of areas that are difficult for ordinary thermal cameras to access while making the imaging systems compact and lightweight. Thus, FB-based thermal imaging systems show great potential in some important applications, such as infrared endoscopy, aircraft infrared warning, and satellite remote sensing. In most applications, FBs are required to have high overall transmittance (OT) and high spatial resolution (), but the fabrication of such high-performance FBs is still a challenge.
View Article and Find Full Text PDFSuperstrong Lightweight Aerogel with Supercontinuous Layer by Surface Reaction.
Adv Mater
January 2025
Key Laboratory of Precision and Intelligent Chemistry, CAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Precision Machinery and Precision Instrumentation, National Synchrotron Radiation Laboratory, Center for Micro and Nanoscale Research and Fabrication, Institute of Advanced Technology, University of Science and Technology of China, Hefei, 230026, P. R. China.
Breaking the thermal, mechanical and lightweight performance limit of aerogels has pivotal significance on thermal protection, new energy utilization, high-temperature catalysis, structural engineering, and physics, but is severely limited by the serious discrete characteristics between grain boundary and nano-units interfaces. Herein, a thermodynamically driven surface reaction and confined crystallization process is reported to synthesize a centimeter-scale supercontinuous ZrO nanolayer on ZrO-SiO fiber aerogel surface, which significantly improved its thermal and mechanical properties with density almost unchanged (≈26 mg cm). Systematic structure analysis confirms that the supercontinuous layer achieves a close connection between grains and fibers through Zr─O─Si bonds.
View Article and Find Full Text PDFIntermetallic Layers with Tuned Na Nucleation and Transport for Anode-Free Sodium Metal Batteries.
Nano Lett
January 2025
Department of Applied Physics and Research Institute for Advanced Manufacturing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong 999077, China.
Sodium metal batteries without pre-deposited Na (anode-free) and with a limited amount of Na metal (anode-less) have attracted increasing attention due to their competitive energy density and the high abundance of sodium. However, severe interfacial issues result in poor cycling stability and low Coulombic efficiency. Here, the lightweight interphase layers composed of intermetallic nanoparticles (Sn-Cu and Sn-Ni) are applied to improve Na plating/stripping behaviors.
View Article and Find Full Text PDFNH-Modulated Cathodic Interfacial Spatial Charge Redistribution for High-Performance Dual-Ion Capacitors.
Nanomicro Lett
January 2025
Shanghai Key Lab of Chemical Assessment and Sustainability, School of Chemical Science and Engineering, Tongji University, Shanghai, 200092, People's Republic of China.
Compared with Zn, the current mainly reported charge carrier for zinc hybrid capacitors, small-hydrated-sized and light-weight NH is expected as a better one to mediate cathodic interfacial electrochemical behaviors, yet has not been unraveled. Here we propose an NH-modulated cationic solvation strategy to optimize cathodic spatial charge distribution and achieve dynamic Zn/NH co-storage for boosting Zinc hybrid capacitors. Owing to the hierarchical cationic solvated structure in hybrid Zn(CFSO)-NHCFSO electrolyte, high-reactive Zn and small-hydrate-sized NH(HO) induce cathodic interfacial Helmholtz plane reconfiguration, thus effectively enhancing the spatial charge density to activate 20% capacity enhancement.
View Article and Find Full Text PDFLiteMamba-Bound: A Lightweight Mamba-based Model with Boundary-Aware and Normalized Active Contour Loss for Skin Lesion Segmentation.
Methods
January 2025
School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, Viet Nam. Electronic address:
In the field of medical science, skin segmentation has gained significant importance, particularly in dermatology and skin cancer research. This domain demands high precision in distinguishing critical regions (such as lesions or moles) from healthy skin in medical images. With growing technological advancements, deep learning models have emerged as indispensable tools in addressing these challenges.
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