Results 171 to 180 of about 656,169 (307)

Chemical AI in the Limelight: The Contribution of Photochromic Materials and Oscillatory Chemical Reactions

open access: yesAdvanced Optical Materials, EarlyView.
Photochromic compounds are versatile ingredients for the development of Chemical AI. When they are embedded in a tight microenvironment, they become Markov blankets. They are also valuable for processing Boolean and Fuzzy logic. They contribute to neuromorphic engineering in wetware based on opto‐chemical signals exchanged with oscillatory chemical ...
Pier Luigi Gentili
wiley   +1 more source

Self‐Assembled Physical Unclonable Function Labels Based on Plasmonic Coupling

open access: yesAdvanced Optical Materials, EarlyView.
This article introduces advanced anti‐counterfeit labels crafted through DNA‐guided self‐assembly of plasmonic nanoparticles. Utilizing nanosphere lithography for dense and precise nanoparticle placement, these labels feature unique, unclonable optical signatures achieved through plasmonic coupling, detectable by an economical 3D‐printed dark field ...
Mihir Dass   +9 more
wiley   +1 more source

Carbonized Polymer Dots‐Based Spectrally Adaptable Photonic Microbarcodes

open access: yesAdvanced Optical Materials, EarlyView.
This study explores spectrally tunable photonics barcodes using carbonized polymer dots (CPDs) based on whispering gallery mode (WGM) photoluminescence. CPDs offer wavelength‐dependent emission from visible to near‐infrared (NIR), thereby enabling variable WGM emissions.
Barun Kumar Barman   +2 more
wiley   +1 more source

Digitized Phase‐Change Material Heterostack for Transmissive Diffractive Optical Neural Network

open access: yesAdvanced Photonics Research, EarlyView.
A phase‐change‐material‐based digitized heterostack is experimentally demonstrated and theoretically analyzed for future energy‐efficient, fast reconfigured, and compact transmissive diffractive optical neural networks. All‐optical and fully reconfigurable transmissive diffractive optical neural network (DONN) architectures emerge as high‐throughput ...
Ruiyang Chen   +3 more
wiley   +1 more source

A reinforcement learning approach for reducing traffic congestion using deep Q learning. [PDF]

open access: yesSci Rep
Swapno SMMR   +6 more
europepmc   +1 more source

Research Progress on Atmospheric Turbulence Perception and Correction Based on Adaptive Optics and Deep Learning

open access: yesAdvanced Photonics Research, EarlyView.
This work presents a systematic review of atmospheric turbulence fundamentals, including theoretical formulations and adaptive optics‐based mitigation strategies. This includes an in‐depth examination of the devices, theories, and methodologies associated with traditional correction approaches.
Qinghui Liu   +5 more
wiley   +1 more source

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