Evidence map›Paper›PMID 39275613›Full record

ArticleSensors (Basel, Switzerland)2024

Pd Nanoparticles Loaded on Cu Nanoplate Sensor for Ultrasensitive Detection of Dopamine.

Haihu Tan, Xuan Zhang, Jinpu Xie, Zengmin Tang, Sijia Tang, Lijian Xu, Pingping Yang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

7 authors.

Haihu TanCollege of Packaging and Materials Engineering, Hunan University of Technology, Zhuzhou 412007, China.
Xuan ZhangCollege of Packaging and Materials Engineering, Hunan University of Technology, Zhuzhou 412007, China.
Jinpu XieCollege of Packaging and Materials Engineering, Hunan University of Technology, Zhuzhou 412007, China.
Zengmin TangCollege of Life Science and Chemistry, Hunan University of Technology, Zhuzhou 412007, China.
Sijia TangCollege of Life Science and Chemistry, Hunan University of Technology, Zhuzhou 412007, China.
Lijian XuCollege of Life Science and Chemistry, Hunan University of Technology, Zhuzhou 412007, China.
Pingping YangCollege of Life Science and Chemistry, Hunan University of Technology, Zhuzhou 412007, China.ORCID 0009-0009-2132-936X

Funding

the National Natural Science Foundation of China U23A20138, 52374387
6 · The paper itself

Abstract

The detection of dopamine is of great significance for human health. Herein, Pd nanoparticles were loaded on Cu nanoplates (Pd/Cu NPTs) by a novel liquid phase reduction method. A novel dopamine (DA) electrochemical sensor based on the Pd NPs/Cu/glass carbon electrode (Pd/Cu NPTs/GCE) was constructed. This sensor showed a wide linear range of 0.047 mM to 1.122 mM and a low limit of detection (LOD) of 0.1045 μM (S/N = 3) for DA. The improved performance of this sensor is attributed to the obtained tiny Pd nanoparticles which increase the catalytic active sites and electrochemical active surface areas (ECSAs). Moreover, the larger surface area of two-dimensional Cu nanoplates can load more Pd nanoparticles, which is another reason to improve performance. The Pd/Cu NPTs/GCE sensor also showed a good reproducibility, stability, and excellent anti-interference ability.

Indexed as

CopperDopamineElectrochemical TechniquesLimit of DetectionMetal NanoparticlesPalladiumBiosensing TechniquesElectrodesHumansReproducibility of ResultsCopperDopaminePalladiumdopamineelectrochemical active surface areasPd nanoparticlessensortwo–dimensional Cu nanoplates

Identifiers

PMID39275613
PMCPMC11397903

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.