Results 231 to 240 of about 1,883,790 (358)

In Situ Study of Resistive Switching in a Nitride‐Based Memristive Device

open access: yesAdvanced Functional Materials, EarlyView.
In situ TEM biasing experiment demonstrates the volatile I‐V characteristic of MIM lamella device. In situ STEM‐EELS Ti L2/L3 ratio maps provide direct evidence of the oxygen vacancies migrations under positive/negative electrical bias, which is critical for revealing the RS mechanism for the MIM lamella device.
Di Zhang   +19 more
wiley   +1 more source

Mouth Movement Recognition Using Template Matching and its Implementation in an Intelligent Room

open access: diamond, 2012
Kiyoshi Takita   +4 more
openalex   +1 more source

Grain Boundary Space Charge Engineering of Solid Oxide Electrolytes: Model Thin Film Study

open access: yesAdvanced Functional Materials, EarlyView.
This study demonstrates unprecedented control of grain boundary electrical properties in solid electrolytes. Selective diffusion of cations through grain boundaries in thin films enables 12 orders of magnitude variation in ionic resistance, proving that systematic chemical modification of grain boundary electrical properties is feasible.
Thomas Defferriere   +5 more
wiley   +1 more source

Insight into the Internal Structure of Biogenic, Synthetic and Geological Apatite by Electron Microscopy and X‐Ray Scattering

open access: yesAdvanced Functional Materials, EarlyView.
Apatite occurs in many forms in nature, e.g. in teeth and geological minerals. Internally, biological apatite contains nanocrystals that are also found in synthetically prepared calcium phosphate nanoparticles which are used in biomedicine, e.g. for gene and drug delivery and for bone regeneration. Abstract Calcium phosphate is the inorganic component (
Kathrin Kostka   +3 more
wiley   +1 more source

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

open access: yesAdvanced Functional Materials, EarlyView.
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

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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