Evidence map›Paper›PMID 41706729›Full record

ArticlePloS one2026

Design and research of a passively mixed microfluidic chip for copper ion detection.

Yuxuan Geng, Longjiang Song, Junfei Wu, Wenjie Zhao, Ping Fu, Yanyong Liu, Luning Jia, Yalin Yuan

Abstract read
In one paragraph

Article in PloS one, 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

8 authors.

Yuxuan GengCollege of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, China.ORCID https://orcid.org/0009-0005-3459-3224
Longjiang SongCollege of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, China.
Junfei WuCollege of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, China.
Wenjie ZhaoCollege of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, China.
Ping FuCollege of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, China.ORCID https://orcid.org/0009-0009-8108-1300
Yanyong LiuCollege of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, China.
Luning JiaCollege of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, China.
Yalin YuanCollege of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

At the micro-scale channel dimensions and relatively low Reynolds numbers, fluids can only mix through diffusion in a laminar flow state. This dependence on molecular diffusion significantly hinders the mixing performance of microfluidic chips. To address this issue and promote the application of microfluidic technology in the detection of heavy metal ions, we propose a high-performance microfluidic chip with variable cross-sectional channels based on passive mixing. By setting bias centrifugal bends and linear flow channels with periodic diameter changes, the mixing efficiency of the microfluidic chip has been significantly improved. To verify the theoretical mixing effect, we set up eight groups of different Reynolds number conditions for the microfluidic chip and simulated the fluid flow in laminar state. Through analyzing the simulation cloud diagrams and the mass fraction mixing index, it was found that when the Reynolds number was 0.5, the mixing efficiency of the microfluidic chip reached the optimal state, with a mass fraction mixing index of 0.9998, and the pressure drop was only 0.1502 Pa, which was higher than the mixing efficiency of similar chips under the same conditions. Using 3D printing technology to fabricate the microfluidic chip and conducting characterization analysis. To verify the actual mixing effect, a colorimetric mixing experiment was set up, and a visual mixing effect analysis of the chip was conducted. Through ICP-MS for copper ion detection experiments, three control experiments were set up to conduct a data-driven mixed effect comparison analysis of the chip. After verification, the overall and local mixing effects of the microfluidic chip were highly consistent with the simulation results under the same conditions, and the detection value of the mixed solution was 101.99% of the completely mixed solution, showing good consistency. Therefore, this chip has excellent mixing performance and is conducive to promoting the application of passive microfluidic chips in fields such as heavy metal detection.

Indexed as

CopperLab-On-A-Chip DevicesMicrofluidic Analytical TechniquesMicrofluidicsColorimetryEquipment DesignIonsCopperIons

Identifiers

PMID41706729
PMCPMC12915913

What OpenQuestion holds

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LicenceCC BY
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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.