Results 151 to 160 of about 9,663 (287)

Broadband and Broad-angle Polarization-independent Metasurface for Radar Cross Section Reduction. [PDF]

Sci Rep, 2017
Sun H, Gu C, Chen X, Li Z, Liu L, Xu B, Zhou Z.   +6 more
europepmc   +1 more source

Ultrastable Self‐Cross‐linkable Electro‐Optic Materials Based on a Bisanthracene Scaffold

Advanced Electronic Materials, EarlyView.
A novel bisanthracene‐based self‐cross‐linkable electro‐optic chromophore (TD2) is developed. TD2 exhibits a high r33 of 141 pm/V and a cross‐linked Tg up to 195 °C, retaining 99.75% of its initial EO response after 500 h at 85 °C, showing record‐high thermal stability for single‐molecule self‐cross‐linking EO materials.
Xingtao Wang, Zhifan Liu, Qinghua Yang, Jiayan Xu, Lin Li, Fenggang Liu, Shengyu Cong   +6 more
wiley   +1 more source

Deep Learning-Based Inverse Design of Stochastic-Topology Metamaterials for Radar Cross Section Reduction. [PDF]

Materials (Basel)
Zhang C, Zou C, Guo S, Zhao Y, Shen T.
europepmc   +1 more source

Smart Flexible Tactile Sensors: Recent Progress in Device Designs, Intelligent Algorithms, and Multidisciplinary Applications

Advanced Intelligent Discovery, EarlyView.
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang, Ming Dong, Rongrong Bao, Caofeng Pan   +3 more
wiley   +1 more source

Ultra-Wideband Passive Polarization Conversion Metasurface for Radar Cross-Section Reduction Across C-, X-, Ku-, and K-Bands. [PDF]

Micromachines (Basel)
Ren X, Liu Y, Ji Z, Zhang Q, Cao W.
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

Lidar‐Based Object Tracking of Traffic Participants with Sensor Nodes in Existing Urban Infrastructure

Advanced Intelligent Systems, EarlyView.
This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer, Bassam Alrifaee, Ehsan Hashemi   +2 more
wiley   +1 more source

Concentric Rheostat Decoupled 3D Force‐Sensing Module for Smart Table Tennis Training

Advanced Intelligent Systems, EarlyView.
A 3D‐printed sensor array intrinsically decouples normal and shear forces through a unique concentric structural design. By integrating piezoresistive, sliding area‐varying capacitive, and concentric rheostat mechanisms, the 12‐sensor module achieves high‐resolution 3D force mapping without complex algorithms.
Zhe Liu, Kunlin Wu, Bingrui Sim, Wenjie Lai, Xingyu Chen, Jiajun Liu, Yifan Wang, Soo Jay Phee   +7 more
wiley   +1 more source

ParamNet: A Physics‐Guided Deep Learning Framework for Intelligent Self‐Inversion of Vacuum Optical Levitation Systems

Advanced Intelligent Systems, EarlyView.
A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng, Wenfeng Fan, Feng Li, Jian Wu, Wei Quan   +4 more
wiley   +1 more source