Results 71 to 80 of about 1,492,451 (279)

Optimizing NiMo Electrocatalyst Coatings for Hydrogen Evolution in Alkaline Electrolysis With The Machine Learning‐Guided Autonomous Platform CatBot

Advanced Functional Materials, EarlyView.
This work presents a closed‐loop optimization workflow integrating CatBot, an automated synthesis and testing system, to discover NiMo hydrogen‐evolution catalysts. CatBot synthesised and evaluated 228 unique samples, identifying the best performing catalysts for transfer to nickel‐foam electrodes. The best candidate is highly active, reaching 1 Acm−2${
Paolo Vincenzo Freiesleben de Blasio, Jonas Elsborg, Elif Coşkun, Andreas Burger, Pradipkumar Manubhai Leuaa, Thu Pham Anh Phan, Jin Hyun Chang, Christodoulos Chatzichristodoulou   +7 more
wiley   +1 more source

Grayscale Photomasks Enable Noncontact Optical Patterning of Hydroxypropyl Cellulose Gels for Dynamic Art

Advanced Functional Materials, EarlyView.
Mask‐encoded UV exposure translates digital color information into pixel‐resolved structural‐color patterns in hydroxypropyl cellulose gels. Gaussian‐process‐guided calibration links UV processing conditions, wavelength, and mask opacity, enabling parallel fabrication of multicolor images in a single 10 s exposure.
Mengting Ye, Yunyi Zhu, Sai Sabareesh KS, Md Ashiqur Rahman Alif, Yichen Wan, Ruobing Bai, Narges Pourjafarian, Stefanie Mueller, Hongli Zhu   +8 more
wiley   +1 more source

MT-BCS-Based DoA and Bandwidth Estimation of Unknown Signals through Multiple Snapshots Data

International Journal of Antennas and Propagation, 2020
The Direction-of-Arrival (DoA) and bandwidth (BW) estimation strategy impinging on a linear array using multiple snapshots data is addressed within the multitask Bayesian Compressive Sensing (MT-BCS).
Shi Hui Zhang, Qing He Zhang, Li Ping Shi, Chao Yi, Guang Xu Liu   +4 more
doaj   +1 more source

Achievable performance of Bayesian compressive sensing based spectrum sensing

2014 IEEE International Conference on Ultra-WideBand (ICUWB), 2014
In wideband spectrum sensing compressive sensing approaches have been used at the receiver side to decrease the sampling rate if the wideband signal can be represented as sparse in a given domain. While most studies consider the reconstruction of primary user's signal accurately it is indeed more important to analyze the presence or absence of the ...
Başaran, Mehmet, Erküçük, Serhat, Erküçük, Serhat, Çırpan, Hakan Ali   +3 more
openaire   +3 more sources

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing

Sensors, 2014
We address the problem of data acquisition in large distributed wireless sensor networks (WSNs). We propose a method for data acquisition using the hierarchical routing method and compressive sensing for WSNs. Only a few samples are needed to recover the
Zhiqiang Zou, Cunchen Hu, Fei Zhang, Hao Zhao, Shu Shen   +4 more
doaj   +1 more source

Bayesian compressed sensing with unknown measurement noise level [PDF]

2013 Asilomar Conference on Signals, Systems and Computers, 2013
In sparse Bayesian learning (SBL) approximate Bayesian inference is applied to find sparse estimates from observations corrupted by additive noise. Current literature only vaguely considers the case where the noise level is unknown a priori. We show that for most state-of-the-art reconstruction algorithms based on the fast inference scheme noise ...
Thomas L. Hansen, Peter Bjørn Jørgensen, Niels Lovmand Pedersen, Carles Navarro i Manchon, Bernard H. Fleury   +4 more
openaire   +1 more source

Fast Monostatic Scattering Analysis Based on Bayesian Compressive Sensing [PDF]

, 2016
The Bayesian compressive sensing algorithm is utilized together with the method of moments to fast analyze the monostatic electromagnetic scattering problem. Different from the traditional compressive sensing based fast monostatic scattering analysis
Sha, WEI, Lin, Z-C, Zhao, X-W, Zhang, H-H   +3 more
core  

Energy-efficient sensing in wireless sensor networks using compressed sensing [PDF]

, 2014
Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission ...
Razzaque, Mohammad Abdur, Razzaque, Mohammad A.; id_orcid, Dobson, Simon Andrew, Mohammad Razzaque, Simon Dobson, Dobson, Simon, Dobson, Simon Andrew; id_orcid   +6 more
core   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source