Results 191 to 200 of about 3,367,707 (346)

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

open access: yesAdvanced 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   +18 more
wiley   +1 more source

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

open access: yesAdvanced 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   +3 more
wiley   +1 more source

Quantitative magnetic resonance angiography for early identification of in-stent stenosis post-flow diverter aneurysm embolization. [PDF]

open access: yesInterv Neuroradiol
Werner C   +9 more
europepmc   +1 more source

Photo‐Switching Thermal and Lithium‐Ion Conductivity in Azobenzene Polymers

open access: yesAdvanced Functional Materials, EarlyView.
Light‐responsive azobenzene polymers control thermal and ionic transport simultaneously through structural transitions. UV illumination disrupts π–π stacking, converting crystalline trans states to amorphous cis configurations. Thermal conductivity drops from 0.45 to 0.15 W·m−1·K−1 while Li+ diffusivity increases 100 fold. This dual transport switching
Jaeuk Sung   +7 more
wiley   +1 more source

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

open access: yesAdvanced 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   +17 more
wiley   +1 more source

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