Results 181 to 190 of about 1,835,725 (293)

Evaluation of a Hybrid Neural-Polynomial Deep Q-Network for Switching-Aware Spectrum Selection in a Controlled Radio-Frequency Measurement-Replay Testbed. [PDF]

Sensors (Basel)
Pan Y, Yan Y, Sun D, Li Z, Zhang Z, Cai J, Chen D, Wu Q, Shen Z.   +8 more
europepmc   +1 more source

Self‐Cleaning Sensor Surfaces for Long‐Term Environmental Monitoring

Advanced Engineering Materials, EarlyView.
Long‐term use of unattended outdoor sensors without soiling or biofouling is achieved through generation of a micro‐ and nanorough cuvette surface by combing hydrophobic nanoparticles with fluorinated polymers, crosslinked and surface‐attached through CHic chemistry. The coating demonstrates self‐cleaning behavior and prolonged outdoor stability, which
Sanam Kumari Rajak, Yasmina Frey, Ulrike Wallrabe, Oswald Prucker, Jürgen Rühe   +4 more
wiley   +1 more source

RSMA-enabled satellite-terrestrial communication networks: Performance analysis. [PDF]

PLoS One
Nguyen HN, Nguyen QS, Nguyen TN.
europepmc   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Code-multiplexed multi-frequency impedance cytometry with a unified deep-unfolding network. [PDF]

Microsyst Nanoeng
Lee W, Tang SKY.
europepmc   +1 more source

FastNano Liquid: An Automated Platform for Small‐Angle X‐ray Scattering‐Based Materials Discovery

Advanced Engineering Materials, EarlyView.
We present FastNano Liquid, an automated small‐ and wide‐angle X‐ray scattering platform for the combined synthesis and characterization of (nano)materials. The platform is coupled to varied reactor workflows for both in situ studies of reaction kinetics and ex situ screening of synthesis conditions to support machine learning‐guided exploration ...
Pierre‐Baptiste Flandrin, Émeline Cournède, Jens Krarup, Michael Lesa, Foyzul Hasan, Amandine Séné, Arnaud Lahouati, David Benhaiem, Jérémie‐Luc Sanchez, Simon Delacroix, Thierry Gacoin, Fabienne Testard, Damien Faivre, David Carriere, Corinne Chevallard, Olivier Taché, Mark A. Levenstein   +16 more
wiley   +1 more source

Enhancing Shadow Fading Mitigation with RIS Using Two-Dimensional Orthogonal Pattern Division Multiple Access. [PDF]

Sensors (Basel)
Yang Z, Yao J, Liu Z, Shi Y, Bai X.
europepmc   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Microwave diffractive neural network chips for sensing and computing. [PDF]

Sci Adv
Chen L, Wu QW, Gu Z, Ma Q, Xiao L, Tian Z, Su WQ, Cui HY, You JW, Cui TJ.   +9 more
europepmc   +1 more source

Biomass Native Structure Into Functional Carbon‐Based Catalysts for Fenton‐Like Reactions

Advanced Functional Materials, EarlyView.
This study indicates that eight biomasses with 2D flaky and 1D acicular structures influence surface O types, morphology, defects, N doping, sp2 C, and Co nanoparticles loading in three series of carbon, N‐doped carbon, and cobalt/graphitic carbon. This work identifies how these structural factors impact catalytic pathways, enhancing selective electron
Wenjie Tian, Jingkai Lin, Zhihao Tian, Selusiwe Ncube, Huayang Zhang, Emiliano Cortés, Hongqi Sun, Shaobin Wang   +7 more
wiley   +1 more source