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Cost-Effective and Wireless Portable Device for Rapid and Sensitive Quantification of Micro/Nanoplastics

ACS Sensors 2024 28 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 55 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.

Haoxin Ye, Haoming Yang, Teresa M. Seifried Teresa M. Seifried Haoxin Ye, Matthew Kowal, Haoxin Ye, Teresa M. Seifried Haoxin Ye, Haoxin Ye, Haoxin Ye, Teresa M. Seifried Haoxin Ye, Haoxin Ye, Teresa M. Seifried Haoming Yang, Haoxin Ye, Teresa M. Seifried Xinzhe Zheng, Haoxin Ye, Xinzhe Zheng, Teresa M. Seifried Teresa M. Seifried Xinzhe Zheng, Teresa M. Seifried Teresa M. Seifried Xinzhe Zheng, Xinzhe Zheng, Xinzhe Zheng, Haoxin Ye, Tianxi Yang, Haoming Yang, Haoming Yang, Haoming Yang, Tianxi Yang, Matthew Kowal, Matthew Kowal, Matthew Kowal, Matthew Kowal, Edward R. Grant, Tianxi Yang, Tianxi Yang, Tianxi Yang, Teresa M. Seifried Teresa M. Seifried Teresa M. Seifried Edward R. Grant, Edward R. Grant, Edward R. Grant, Edward R. Grant, Edward R. Grant, Edward R. Grant, David D. Kitts, Tianxi Yang, Gurvendra Pal Singh, Gurvendra Pal Singh, Gurvendra Pal Singh, Krishna Aayush, Rickey Y. Yada, Krishna Aayush, Rickey Y. Yada, Krishna Aayush, Edward R. Grant, Rickey Y. Yada, Guanghui Gao, Guanghui Gao, Guanghui Gao, Tianxi Yang, Edward R. Grant, Edward R. Grant, Edward R. Grant, Edward R. Grant, Tianxi Yang, Tianxi Yang, David D. Kitts, Rickey Y. Yada, Rickey Y. Yada, Rickey Y. Yada, Tianxi Yang, Tianxi Yang, Tianxi Yang, Teresa M. Seifried

Summary

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.

The accumulation of micro/nanoplastics (MNPs) in ecosystems poses tremendous environmental risks for terrestrial and aquatic 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 device that allows rapid, sensitive, and on-site detection of MNPs, followed by remote data processing via machine learning algorithms for quantitative fluorescence imaging. We utilized a supramolecular labeling strategy, employing luminescent 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 device can quantify MNPs as low as 330 microplastics and 3.08 × 10<sup>6</sup> 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. Moreover, the device is user-friendly and operative by untrained personnel to conduct data processing on the APP remotely. The analytical platform integrating quantitative imaging, customized 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.

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