Evidence map›Paper›PMID 42637727›Full record

ArticleMicrosystems & nanoengineering2026

Portable microwave sensor system for real-time detection of microplastics in seawater.

Yuxuan Hou, Qingzhou Wang, Qilong Zhang, Jiaxu Liu, Eun-Seong Kim, Nam-Young Kim, Guanlin Li, Yuanyue Li, Xiaocui Wang, Zhao Yao

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yuxuan HouShandong Key Laboratory of Micro-nano Packaging and System Integration, College of Electronic and Information, Qingdao University, Qingdao, China.
Qingzhou WangShandong Key Laboratory of Micro-nano Packaging and System Integration, College of Electronic and Information, Qingdao University, Qingdao, China.
Qilong ZhangShandong Key Laboratory of Micro-nano Packaging and System Integration, College of Electronic and Information, Qingdao University, Qingdao, China.
Jiaxu LiuShandong Key Laboratory of Micro-nano Packaging and System Integration, College of Electronic and Information, Qingdao University, Qingdao, China.
Eun-Seong KimDepartment of Molecular Medicine and Biopharmaceutical Sciences, Laboratory of Molecular Pathology and Cancer Genomics, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea. 3037eskim@gmail.com.
Nam-Young KimDepartment of Electronic Engineering, Kwangwoon University, Seoul, South Korea.
Guanlin LiSchool of Environment and Safety Engineering, Jiangsu University, Zhenjiang, China.
Yuanyue LiShandong Key Laboratory of Micro-nano Packaging and System Integration, College of Electronic and Information, Qingdao University, Qingdao, China.
Xiaocui WangSchool of Environment and Geography, Qingdao University, Qingdao, China. wangxiaocui@qdu.edu.cn.
Zhao YaoShandong Key Laboratory of Micro-nano Packaging and System Integration, College of Electronic and Information, Qingdao University, Qingdao, China. yzh17@qdu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid development of the global plastic industry, microplastic pollution has become an increasingly serious environmental concern. However, standardized technologies for convenient, accurate, and real-time microplastic detection are limited. To address this challenge, a microwave resonant sensor with a complete microplastic detection system equipped with a Bluetooth module for remote real-time monitoring of microplastic concentrations was developed. Microplastic concentrations were measured in deionized water containing polyvinyl chloride powder (particle size: 6.5 ± 1 μm), simulated artificial seawater, and real seawater samples. The integration of the microfluidic system mitigated the interference caused by the complex seawater matrix, thereby ensuring stable and reliable microwave-based detection of microplastic concentrations. The system demonstrated high repeatability for predicting the concentration of microplastics in seawater samples. The proposed method demonstrated a recognition rate of over 96% with a tolerance of ±0.01 mg/mL, while maintaining a minimum detection limit of 48.72 ng/mL. To improve the prediction accuracy, a convolutional neural network algorithm was employed to predict microplastic concentrations based on the test results, with the predicted and actual concentrations being highly consistent. Finally, a compact and portable seawater microplastic monitoring system was developed by integrating the microwave sensor with Bluetooth and embedded systems, enabling real-time microplastic concentration monitoring in marine environments.

Identifiers

PMID42637727
PMCPMC13503796

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.