Evidence map›Paper›PMID 34835626›Full record

ReviewNanomaterials (Basel, Switzerland)2021

Azaporphyrins Embedded on Carbon-Based Nanomaterials for Potential Use in Electrochemical Sensing-A Review.

Tomasz Koczorowski, Magdalena Cerbin-Koczorowska, Tomasz Rębiś

Open access · goldAbstract readReview
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
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

7 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
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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

3 authors at 2 institutions in 1 country.

Tomasz KoczorowskiChair and Department of Chemical Technology of Drugs, Poznan University of Medical Sciences, Grunwaldzka 6, 60-780 Poznan, Poland.ORCID 0000-0001-8446-4758
Magdalena Cerbin-KoczorowskaDepartment of Medical Education, Poznan University of Medical Sciences, 7 Rokietnicka Str., 60-806 Poznan, Poland.ORCID 0000-0003-0940-1006
Tomasz RębiśInstitute of Chemistry and Technical Electrochemistry, Poznan University of Technology, Berdychowo 4, 60-965 Poznan, Poland.
Poznan University of Medical Sciences · PLPoznań University of Technology · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phthalocyanines and porphyrazines as macrocyclic aza-analogues of well-known porphyrins were deposited on diverse carbon-based nanomaterials and investigated as sensing devices. The extended π-conjugated electron system of these macrocycles influences their ability to create stable hybrid systems with graphene or carbon nanotubes commonly based on π-π stacking interactions. During a 15-year period, the electrodes modified by deposition of these systems have been applied for the determination of diverse analytes, such as food pollutants, heavy metals, catecholamines, thiols, glucose, peroxides, some active pharmaceutical ingredients, and poisonous gases. These procedures have also taken place, on occasion, in the presence of various polymers, ionic liquids, and other moieties. In the review, studies are presented that were performed for sensing purposes, involving azaporphyrins embedded on graphene, graphene oxide or carbon nanotubes (both single and multi-walled ones). Moreover, possible methods of electrode fabrication, limits of detection of each analyte, as well as examples of macrocyclic compounds applied as sensing materials, are critically discussed.

Indexed as

carbon nanotubesgraphenephthalocyaninesporphyrazinessensing

Identifiers

PMID34835626
PMCPMC8620011
OpenAlexW3209815380

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.