Evidence map›Paper›PMID 39730719›Full record

ArticleScientific reports2024

Electrochemical polymerized DL-phenylalanine modified carbon nanotube sensor for the selective and sensitive determination of caffeic acid with riboflavin.

Kanthappa B, J G Manjunatha, Sameh Mohamed Osman, Narges Ataollahi

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Article in Scientific reports, 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

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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.

2 · The registry

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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

4 authors.

Kanthappa BDepartment of Chemistry, FMKMC College, Constituent College of Mangalore University, Madikeri, Karnataka, India, 571201.
J G ManjunathaDepartment of Chemistry, FMKMC College, Constituent College of Mangalore University, Madikeri, Karnataka, India, 571201. manju1853@gmail.com.
Sameh Mohamed OsmanChemistry Department, College of Science, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia.
Narges AtaollahiDepartment of Civil, Environmental and Mechanical Engineering, University of Trento, Via Mesiano, 77, 38123, Trento, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, DL-phenylalanine modified with a multiwall carbon nanotube paste electrode is used as advanced electrochemical sensor for analysing of 0.1 mM caffeic acid (CFA) with simultaneous detection of riboflavin (RFN). The developed sensors include electrochemically polymerized DL-phenylalanine (DL-PA) modified multiwall carbon nanotube paste electrode [DL-PAMMCNTPE] and bare multiwall carbon nanotube paste electrode [BMCNTPE]. The increasing stability in the developed electrochemical sensor for the quantification of CFA is highlighted in detail, along with its characterization using voltammetric techniques such as electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), differential pulse voltammetry (DPV), and linear Sweep Voltammetry (LSV). Scanning electron microscopy (SEM) technique was used to studied the structural analysis of BMCNTPE and DL-PAMMCNTPE surface. The investigation of 0.1 mM CFA in 0.2 M phosphate buffered solution (PBS) using a 7.0 pH at 0.1 V/s scan rate was highlighted using DL-PAMMCNTPE, which shows good electrochemical responses compared to BMCNTPE. This work characterizes the voltammetric responses by inspecting the pH effect, scan rate effect, and concentration difference of CFA at the DL-PAMMCNTPE surface. The CFA responses specify that the scan rate progress is adsorption controlled. The concentration of CFA detection was started from 20 μM to 600 μM using DPV method, with lower limit of detection (LOD) of 0.280 μM and limit of quantification (LOQ) of 0.936 μM. And for CV method concentration range 20 to 550 μM, with LOD of 0.198 μM and LOQ of 0.702 μM. Furthermore, the developed electrochemical sensor responses are shows good stability, repeatability, and reproducibility, for CFA. The analytical applicability of CFA in apple juice and coffee powder samples was also evaluated.

Indexed as

Caffeic AcidsElectrochemical TechniquesNanotubes, CarbonPhenylalanineRiboflavinBiosensing TechniquesDielectric SpectroscopyElectrodesHydrogen-Ion ConcentrationLimit of DetectionPolymerizationcaffeic acidCaffeic AcidsNanotubes, CarbonPhenylalanineRiboflavinCaffeic acidDL-phenylalanineElectrochemical analyserMultiwall carbon nanotube paste sensorVoltammetry

Identifiers

PMID39730719
PMCPMC11681202

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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.