Results 251 to 260 of about 1,620,823 (329)

Integrative Approaches for DNA Sequence‐Controlled Functional Materials

open access: yesAdvanced Functional Materials, EarlyView.
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo   +4 more
wiley   +1 more source

Trap‐Modified Inverted Organic Photodetectors via Layer‐by‐Layer Processing with Poly(N‐vinylcarbazole) Additives

open access: yesAdvanced Functional Materials, EarlyView.
Trap state engineering in inverted organic photodetectors (OPDs) is achieved via combined layer‐by‐layer (LbL) processing and poly(N‐vinylcarbazole) (PVK) incorporation. LbL reduces the trap density while PVK additives gradually shift trap states from shallow band‐edge to deep mid‐gap levels, tailoring the energy distribution.
Jingwei Yi   +10 more
wiley   +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

Signal-to-Noise Ratio

Field Guide to Optical Biosensing, 2021
R. Martín-Palma
openaire   +2 more sources

Improving the Signal‐to‐Noise Ratio of Seismological Datasets by Unsupervised Machine Learning

Seismological Research Letters, 2019
Seismic waves that are recorded by near-surface sensors are usually disturbed by strong noise. Hence, the recorded seismic data are sometimes of poor quality; this phenomenon can be characterized as a low signal-to-noise ratio (SNR).
Yangkang Chen   +3 more
semanticscholar   +1 more source

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