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A novel strategy for detecting trace-level nanoplastics in aquatic environments: Multi-feature machine learning-enhanced SERS quantification leveraging the coffee ring effect

Researchers develop innovative SERS detection strategy leveraging the coffee ring effect to detect trace-level nanoplastics. The method overcomes sensitivity limitations of conventional SERS by analyzing coffee ring diameter and detection probability.

SourceCompuscript Ltd·JournalOpto-Electronic Advances·DateApr 10, 2025

Spinning into the future: fidget spinner revolutionizes bacterial detection

Researchers unveiled a portable, hand-powered device that leverages nanoplasmonic technology to detect bacteria with unprecedented accuracy. The plasmonic fidget spinner (P-FS) significantly improves sensitivity, enabling rapid diagnosis of bacterial infections in resource-limited settings.

Porous crystals detect nitric oxide

A copper-containing, electrically conducting, two-dimensional metal–organic framework has been developed for the highly selective detection of nitric oxide. The material detects NO at room temperature with high sensitivity and selectivity, making it suitable for air quality monitoring and medical applications.

SourceWiley·JournalAngewandte Chemie International Edition·TypeExperimental study·DateDec 12, 2024

NUS and A*STAR researchers develop wearable, stretchable sensor for quick, continuous, and non-invasive detection of solid-state skin biomarkers

Scientists created a wearable sensor that can monitor cholesterol and lactate levels on dry skin, enabling early disease detection. The sensor overcomes existing challenges of traditional methods, promising new opportunities for remote patient monitoring and population-wide health screening.

SourceNational University of Singapore·JournalNature Materials·TypeExperimental study·DateAug 19, 2024

Acquiring weak annotations for tumor localization in temporal and volumetric data

Researchers propose a novel annotation strategy called Drag&Drop, which enables manual labeling based on a single 2D annotation in high-dimensional volumetric data. The proposed framework achieves a comparable tumor detection rate to per-pixel annotations and higher rates than alternative weak annotation strategies.

SourceBeijing Zhongke Journal Publising Co. Ltd.·JournalMachine Intelligence Research·DateMay 12, 2024

Gwangju Institute of Science and Technology scientists develop deep learning-based biosensing platform to count viral particles better

Researchers at Gwangju Institute of Science and Technology (GIST) have developed a deep learning-based biosensing platform called DeepGT, which can accurately quantify nanoscale bioparticles, including viruses. The platform harnesses the advantages of Gires-Tournois biosensors and AI to refine visual artifacts and extract relevant info...

SourceGIST (Gwangju Institute of Science and Technology)·JournalNano Today·TypeComputational simulation/modeling·DateOct 17, 2023