Results 121 to 130 of about 392,009 (311)

Universal Neuromorphic Element: NbOx Memristor with Co‐Existing Volatile, Non‐Volatile, and Threshold Switching

open access: yesAdvanced Functional Materials, EarlyView.
A W/NbOx/Pt memristor demonstrates the coexistence of volatile, non‐volatile, and threshold switching characteristics. Volatile switching serves as a reservoir computing layer, providing dynamic short‐term processing. Non‐volatile switching, stabilized through ISPVA, improves reliable long‐term readout. Threshold switching operates as a leaky integrate
Ungbin Byun, Hyesung Na, Sungjun Kim
wiley   +1 more source

Hiding Information in Retransmissions

open access: yes, 2009
12 pages, 12 figures, 6 ...
Mazurczyk, Wojciech   +2 more
openaire   +2 more sources

A Van der Waals Optoelectronic Synapse with Tunable Positive and Negative Post‐Synaptic Current for Highly Accurate Spiking Neural Networks

open access: yesAdvanced Functional Materials, EarlyView.
A van der Waals optoelectronic synaptic device based on a ReS2/WSe2 heterostructure and oxygen‐treated h‐BN is presented, which enables both positive and negative PSCs through photocarrier polarity reversal. Bidirectional plasticity arises from gate‐tunable band bending and charge trapping‐induced quasi‐doping.
Hyejin Yoon   +9 more
wiley   +1 more source

Effective Sliding Motions of Vibration‐Induced Emission Stoppers in Mechanically Interlocked Molecules as Artificial Muscle Tougheners and In Situ Molecular Shuttling Sensors for Self‐Healable Mechano‐Fluorescent Polyurethane Organogels

open access: yesAdvanced Functional Materials, EarlyView.
The self‐healable ratiometric mechano‐fluorescent polyurethane (PU) organogel is constructed by incorporating a minor amount (ca. 1.5 wt.%) of the unconventional daisy chain rotaxane (as an artificial molecular muscle toughener) with specific sliding motions and ratiometric emission behaviors into the PU skeleton, which reveals the progressed intrinsic
Tu Thi Kim Cuc   +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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