Evidence map›Paper›PMID 39203696›Full record

ArticleMicromachines2024

Development of a Portable Residual Chlorine Detection Device with a Combination of Microfluidic Chips and LS-BP Algorithm to Achieve Accurate Detection of Residual Chlorine in Water.

Tongfei Wang, Jiping Niu, Haoran Pang, Xiaoyu Meng, Ruqian Sun, Jiaqing Xie

Abstract read
In one paragraph

Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Tongfei WangCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China.
Jiping NiuCollege of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China.
Haoran PangCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China.
Xiaoyu MengCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China.
Ruqian SunCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China.
Jiaqing XieCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China.ORCID 0000-0002-0025-4356

Funding

Shaanxi Province Science Foundation for Youths NO. 2021JQ-173The National Natural Science Foundation of China NO. 52109067The National Natural Science Foundation of China NO. 52305507
6 · The paper itself

Abstract

Chlorine is widely used for sterilization and disinfection of water, but the presence of excess residual chlorine in water poses a substantial threat to human health. At present, there is no portable device which can achieve accurate, rapid, low-cost, and convenient detection of residual chlorine in water. Therefore, it is necessary to develop a device that can perform accurate, rapid, low-cost, and convenient detection of residual chlorine in water. In this study, a portable residual chlorine detection device was developed. A microfluidic chip was studied to achieve efficient mixing of two-phase flow. This microfluidic chip was used for rapid mixing of reagents in the portable residual chlorine detection device, reducing the consumption of reagents, detection time, and device volume. A deep learning algorithm was proposed for predicting residual chlorine concentration in water, achieving precise detection. Firstly, the microfluidic chip structure for detecting mixed reagents was optimized, and the microfluidic chip was fabricated by a 3D-printing method. Secondly, a deep learning (LS-BP) algorithm was constructed and proposed for predicting residual chlorine concentration in water, which can realize dual-channel signal reading. Thirdly, the corresponding portable residual chlorine detection device was developed, and the detection device was compared with residual chlorine detection devices and methods in other studies. The comparison results indicate that the portable residual chlorine detection device has high detection accuracy, fast detection speed, low cost, and good convenience. The excellent performance of the portable residual chlorine detection device makes it suitable for detecting residual chlorine in drinking water, swimming pool water, aquaculture and other fields.

Indexed as

deep learning algorithmsLS-BP algorithmmicrofluidic chipresidual chlorine

Identifiers

PMID39203696
PMCPMC11356599

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LicenceCC BY
Read underepoch 390

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.