ArticleACS omega2021
Laser-Induced Carbon Electrodes in a Three-Dimensionally Printed Flow Reactor for Detecting Lead Ions.
Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed.
- Microfluidic Devices for Heavy Metal Ions Detection: A Review.Micromachines · 2023Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nowadays, heavy metal pollution has attracted wide attention. Many electrochemical methods have been developed to detect heavy metal ions. The electrode surface usually needs to be modified, and the process is complicated. Herein, we demonstrate the fabrication of electrodes by direct laser sintering on commercial polymer films. The prepared porous carbon electrodes can be used directly without any modification. The electrodes were fixed in a 3D-printed flow reactor, which led to very little analyte required during the detection process. The velocities of the analyte under stirring and flowing conditions were simulated numerically. The results prove that flow detection is more conducive to improving detection sensitivity. The limit of detection is about 0.0330 mg/L for Pb
Identifiers
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Registered trials
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.