We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Cost-Effective and Wireless Portable Device for Rapid and Sensitive Quantification of Micro/Nanoplastics
AI summary Read the abstract
Researchers developed a wireless portable device for rapid quantification of micro- and nanoplastics in water samples, offering a field-deployable alternative to laboratory-based analysis for environmental monitoring.
The accumulation of micro/nanoplastics (MNPs) in ecosystems poses tremendous environmental risks for terrestrial and aquat-ic organisms. Designing rapid, field-deployable, and sensitive devices for assessing the potential risks of MNPs pollution is critical. However, current techniques for MNPs detection have limited effectiveness. Here, we design a wireless portable de-vice that allows rapid, sensitive, and on-site detection of MNPs, followed by remote data processing via machine learn-ing algorithms for quantitative fluorescence imaging. We uti-lized a supramolecular labeling strategy, employing lumines-cent metal-phenolic networks composed of zirconium ions, tannic acid, and rhodamine B, to efficiently label various sizes of MNPs (e.g., 50 nm – 10 μm). Results showed that our de-vice can quantify MNPs as low as 330 microplastics and 3.08×106 nanoplastics in less than 20 min. We demonstrated the applicability of the device to real-world samples through determination of MNPs released from plastic cups after hot water and flow induction, and nanoplastics in tap water. More-over, the device is user-friendly and operative by untrained personnel to conduct data processing on APP remotely. The analytical platform integrating quantitative imaging, custom-ized data processing, decision tree model and low-cost analysis ($0.015 per assay) has great potential for high-throughput screening of MNPs in agrifood and environmental systems.
More Papers Like This
Cost-Effective and Wireless Portable Device for Rapid and Sensitive Quantification of Micro/Nanoplastics
AI summary Read the abstract
Researchers designed a low-cost, wireless portable device that can rapidly detect and quantify micro- and nanoplastics using fluorescent labeling and smartphone-based imaging. The device achieved sensitive detection across particle sizes from 50 nanometers to 10 micrometers and could transmit results wirelessly for analysis using machine learning algorithms. The technology could make field-based microplastic monitoring far more accessible and affordable than current laboratory methods.
Portable On-Site Optical Detection and Quantification of Microplastics
AI summary Read the abstract
Researchers built a portable, on-site optical device to detect and quantify microplastics in water. The device addresses the challenge of detecting small, often translucent particles without a laboratory setting. Portable microplastic detection tools could enable real-time monitoring in the field, supporting faster environmental assessments.
Smart Portable Sensor System for Microplastic Detection in Water
AI summary Read the abstract
Researchers built a low-cost portable device that uses a light sensor to detect microplastics in water, showing results on a small screen and indicator lights. In tests with water samples containing different contamination levels, the device responded quickly and accurately classified the level of contamination.
Rapid Detection of Micro/Nanoplastics Via Integration of Luminescent Metal Phenolic Networks Labeling and Quantitative Fluorescence Imaging in A Portable Device
AI summary Read the abstract
Researchers developed a portable wireless device for rapid on-site detection of micro- and nanoplastics using fluorescent labeling and machine learning-powered image analysis. The study demonstrates that this approach enables sensitive and quantitative identification of plastic particles in environmental samples, addressing the need for field-deployable monitoring tools.
Smartphone-enabled rapid quantification of microplastics
AI summary Read the abstract
A smartphone-based system was developed to rapidly quantify microplastics from environmental samples, reducing analysis time from hours or days to a much faster workflow without requiring expensive lab equipment. The method was validated against standard techniques and shown to be suitable for field-deployable microplastic monitoring.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.