Results 171 to 180 of about 20,865 (296)

Piezoresistive Natural Rubber Composites: A Comparison Between Low‐Temperature Glutaraldehyde Curing Agents and Conventional Sulfur Curing Systems

open access: yesPolymer Composites, Volume 47, Issue 5, Page 4310-4325, 10 March 2026.
The secondary electrical signal peak during cyclic experiment observed in S‐cured NR sensors was eliminated with GA curing due to the homogeneous distribution of crosslink points in the GA‐cured NR network. ABSTRACT This study examines the piezoresistive behavior of natural rubber (NR) composites cured with sulfur (S) and glutaraldehyde (GA) and ...
Rawiporn Promsung   +5 more
wiley   +1 more source

Crack‐Growing Interlayer Design for Deep Crack Propagation and Ultrahigh Sensitivity Strain Sensing

open access: yesAdvanced Functional Materials, Volume 36, Issue 22, 16 March 2026.
A crack‐growing semi‐cured polyimide interlayer enabling deep cracks for ultrahigh sensitivity in low‐strain regimes is presented. The sensor achieves a gauge factor of 100 000 at 2% strain and detects subtle deformations such as nasal breathing, highlighting potential for minimally obstructive biomedical and micromechanical sensing applications ...
Minho Kim   +11 more
wiley   +1 more source

Microplastics from Wearable Bioelectronic Devices: Sources, Risks, and Sustainable Solutions

open access: yesAdvanced Functional Materials, Volume 36, Issue 20, 9 March 2026.
Bioelectronic devices (e.g., e‐skins) heavily rely on polymers that at the end of their life cycle will generate microplastics. For research, a holistic approach to viewing the full impact of such devices cannot be overlooked. The potential for devices as sources for microplastics is raised, with mitigation strategies surrounding polysaccharide and ...
Conor S. Boland
wiley   +1 more source

Strain Engineering of Correlated Charge-Ordered Phases in 1T-TaS<sub>2</sub>. [PDF]

open access: yesNano Lett
Luque Merino R   +5 more
europepmc   +1 more source

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

open access: yesAdvanced Functional Materials, Volume 36, Issue 24, 23 March 2026.
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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