Results 141 to 150 of about 341,830 (324)

Innovative Metasurface Colorimetric Cell‐on‐a‐Chip Sensor for Continuous, Label‐Free, Non‐Destructive Assessment of Intestinal Barrier Dynamics

Advanced Science, EarlyView.
We developed a real‐time, label‐free, high‐throughput cell‐on‐a‐chip system based on a metasurface plasmon resonance colorimetric sensor (MetaSPRCS) to evaluate intestinal barrier function. This platform enables continuous monitoring of cell adhesion, proliferation, and barrier layer formation, disruption, and repair.
Youqian Chen, Wen Li, Jiaying Feng, Yue Shu, Yihui Yang, Yuyan Wang, Rui Li, Hanlin Zhou, Xinfan Yang, Yuxue Guo, Mingqian Chen, Wenjun Hu, Gang Logan Liu, Liping Huang, Yanan Li   +14 more
wiley   +1 more source

Design and Optimization of Full‐Stokes Hyperspectro‐Polarimetric Encoding Metasurfaces Based on Conditional Multi‐Task Deep Learning

Advanced Science, EarlyView.
A conditional multi‐task deep learning framework is developed for designing and optimizing Full‐Stokes Hyperspectro‐Polarimetric Encoding Metasurfaces (FHPEMs). This framework achieves joint spectro‐polarimetric learning and unified forward–inverse design.
Chenjie Gong, Haodong Shi, Qi Wang, Yingchao Li, Hongyu Sun, Jiayu Wang, Guanlin Li, Jian Zhang, Qiang Fu, Huilin Jiang   +9 more
wiley   +1 more source

RGB-W Dataset

, 2015
Alexandre Alahi, Albert Haque, Li Fei-Fei   +2 more
openalex   +1 more source

Prediction Model of Live Weight Using Deep Regression RGB-D Images

, 2023
Alexey Ruchay
openalex   +2 more sources

Large‐Scale Synthesis of Monodispersed Perovskite Nanocrystals via Autonomous Continuous Droplet Microfluidics

Advanced Science, EarlyView.
In this work, we propose a novel on‐chip microscale continuous droplet‐in‐flow synthesis (μ‐CDFS) that utilizes zwitterionic ligands to enable large‐scale preparation of perovskite nanocrystals (PNCs) with high emission efficiency and monodispersity.
Guangguang Huang, Xiangyu Liu, Long Song, Hailong Feng, Zuliang Du   +4 more
wiley   +1 more source

Toward Prostate Cancer Early Warning with a Self‐Powered Wearable Biosensing Platform Integrated with Machine Learning

Advanced Science, EarlyView.
ABSTRACT Current prostate cancer detection methods remain limited in non‐invasiveness and specificity, prompting interest in urinary biomarkers such as sarcosine. Here, we report a urine‐powered wearable platform for non‐invasive sarcosine detection as a proof‐of‐concept for decentralized early warning.
Jing Xu, Hanxiao Chen, Qichen Yuan, Liucun Yin, Yifang Tao, Hong Wang, Yuquan Xue, Delai Fu, Huan Pang, Tie Chong, Li Xue   +10 more
wiley   +1 more source

Polymorphic Superparaelectric Engineering Boosting Energy Storage Capacity in BaTiO3‐Based Ceramics

Advanced Science, EarlyView.
Herein, Ca2+ incorporation promotes the coexistence of CaTiO3‐/BaTiO3‐derived paraferroelectric states, stabilizing cubic‐orthorhombic‐tetragonal polymorphic superparaelectric phases. This minimizes polarization energy barriers, facilitating full polarization saturation without compromising efficiency.
Pan Liu, Xiang Ren, Jin Qian, Haihua Huang, Peng Li, Peng Fu, Jigong Hao, Huarong Zeng, Wei Li, Zhenxiang Cheng   +9 more
wiley   +1 more source

AN APPROACH TO CLASSIFICATION AND EVALUATION OF GEOMETRIC PARAMETERS OF COMPLEX SURFACES BASED ON RGB-D IMAGES

, 2022
Julia Rubtsova, Roman Iakovlev
openalex   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source