Results 231 to 240 of about 248,172 (367)

Powering the Future: A Cobalt‐Based Catalyst for Longer‐Lasting Zinc–Air Batteries

open access: yesAdvanced Functional Materials, EarlyView.
A novel N‐doped graphitic shell‐encapsulated Co catalyst reveals superior bifunctional ORR/OER activity in alkaline media, empowering outstanding liquid and quasi‐solid‐state ZAB activity. The system delivers long‐term durability, a peak power density of 127 mW cm−2 and successfully powers an LED and a mini fan.
Manami Banerjee   +10 more
wiley   +1 more source

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

The Double-Layer Potential for Spectral Constants Revisited. [PDF]

open access: yesIntegr Equ Oper Theory
Schwenninger FL, de Vries J.
europepmc   +1 more source

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

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

Isoscattering non-isospectral quantum graphs. [PDF]

open access: yesSci Rep
Farooq O   +3 more
europepmc   +1 more source

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