Results 171 to 180 of about 1,412,608 (290)

A Pressure Microsensor Made of Parylene‐C for Use as Medical Implant

open access: yesAdvanced Materials Technologies, EarlyView.
A monolithic parylene‐C pressure sensor with gold strain gauges provides 6.2 μV$\mu{\rm V}$·mmHg$\cdot{\rm mmHg}$−1$^{-1}$ sensitivity. The morphology of a sputtered thin film strain sensor is granular/columnar, which results in a high gauge factor of 7.5. Thermal bonding and parylene‐C coating create a hermetic cavity.
Ann‐Kathrin Klein   +2 more
wiley   +1 more source

Present fields of mathematical research [PDF]

open access: yesProceedings of the Edinburgh Mathematical Society, 1883
openaire   +1 more source

Cap‐oPMN: Oral Inflammatory Load Quantification Using Capillary Microfluidics and Automated Image Processing

open access: yesAdvanced Materials Technologies, EarlyView.
ABSTRACT Quantifying oral polymorphonuclear neutrophils (oPMNs) is a clinically validated approach for assessing periodontal inflammation. However, current methods, such as manual hemocytometry and flow cytometry, are time‐consuming (>3 h), require invasive sampling, and depend on staining and complex instrumentation, making them unsuitable for point ...
Mohsen Hassani   +9 more
wiley   +1 more source

Stress‐Normalized Sensitivity as a Comparative Benchmark for Intrinsically Piezoresistive Nanocomposite Materials in Wearable Electronics

open access: yesAdvanced Materials Technologies, EarlyView.
A stress‐normalised sensitivity metric (S = G/Y) is introduced as a materials‐level benchmark for intrinsically piezoresistive nanocomposites. By decoupling electromechanical response (G) from stiffness (Y), the framework enables direct comparison across diverse systems and clarifies design trade‐offs for wearable sensors.
Conor S. Boland
wiley   +1 more source

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

open access: yesAdvanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov   +3 more
wiley   +1 more source

The Evolution of Laser‐Induced Damage Patterns in Polymer Stabilized Liquid Crystals: Insights From Morphological Characterization and Thermo‐Driven Simulations

open access: yesAdvanced Optical Materials, EarlyView.
A dual‐domain PSLC architecture enables direct comparison of alignment‐dependent laser damage within a single device. Crack‐like and seal‐like morphologies emerge under different damage conditions, and their evolution is interpreted through quantitative image analysis and heat‐driven simulations.
Dengcheng Chen   +4 more
wiley   +1 more source

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