Results 181 to 190 of about 1,053,925 (307)

Tuning the Electronic Structure and Spin State of Fe─N─C Catalysts Using an Axial Oxygen Ligand and Fe Clusters for High‐Efficiency Rechargeable Zinc–Air Batteries

Advanced Functional Materials, EarlyView.
A FeN4─O/Clu@NC‐0.1Ac catalyst containing atomically‐dispersed FeN4─O sites (medium‐spin Fe2+) and Fe clusters delivered a half‐wave potential of 0.89 V for ORR and an overpotential of 330 mV at 10 mA cm−2 for OER in 0.1 m KOH. When the catalyst was used in a rechargeable Zn–air battery, a power density of 284.5 mW cm−2 was achieved with excellent ...
Yongfang Zhou, Yu Mao, Mengyao Chang, Ziyun Wang, Wenke Xie, Cuizhu Ye, Shanghai Wei, Lars Thomsen, Geoffrey I. N. Waterhouse   +8 more
wiley   +1 more source

Single Solid‐State Ion Channels as Potentiometric Nanosensors

Advanced Functional Materials, EarlyView.
Single gold nanopores functionalized with mixed self‐assembled monolayers act as solid‐state ion channels for direct, selective potentiometric sensing of inorganic ions (Ag⁺). The design overcomes key miniaturization barriers of conventional ion‐selective electrodes by combining low resistivity with suppressed loss of active components, enabling robust
Gergely T. Solymosi, Gyula Jágerszki, Levente Illés, Péter Fürjes, Róbert E. Gyurcsányi   +4 more
wiley   +1 more source

Saliency-enhanced infrared and visible image fusion via sub-window variance filter and weighted least squares optimization. [PDF]

PLoS One
Wang P, Li T, Li P.
europepmc   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

ADMM-EM Method for L₁-Norm Regularized Weighted Least Squares PET Reconstruction. [PDF]

Comput Math Methods Med, 2016
Teng Y, Sun H, Guo C, Kang Y.
europepmc   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source

Geometric weighted least squares estimation

Statistics, Optimization & Information Computing
Optimal efficiency of least squares (LS) estimation requires that the error variables (residuals) have equal variance (homoscedasticity). In LS applications with multiple output variables, heteroscedasticity can even cause bias. In weighted LS, weights are chosen to compensate for differences in variance.
openaire   +1 more source

Oral Dosed Organo‐Silica Nanoparticles Restore Glucose Homeostasis and β‐Cell Function in Diabetes Rats

Advanced Functional Materials, EarlyView.
An oral nanoplatform, MOP@T@D, which can maintain glucose homeostasis and restore islet β cells in diabetic rats is developed. It achieves efficient intestinal absorption and liver‐targeted delivery. The nanoparticle disintegrates only in response to hyperglycemia to release insulin on demand and provides antioxidant protection through selenoprotein ...
Chenxiao Chu, Mingli Wei, Che Bian, Xiaoshuang Bi, Yaxin Deng, Peifu Xiao, Jiansong Zhao, Yuying Wang, Haibing He, Jingxin Gou, Tian Yin, Xing Tang, Li Yang, Hongbo Zhang, Yu Zhang   +14 more
wiley   +1 more source

Comparison of SIRT and SQS for Regularized Weighted Least Squares Image Reconstruction. [PDF]

IEEE Trans Comput Imaging, 2015
Gregor J, Fessler JA.
europepmc   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source