Evidence map›Paper›PMID 36570033›Full record

ArticleMaterials today. Communications2023

Prospects of ZnS and ZnO as smart semiconductor materials in light-activated antimicrobial coatings for mitigation of severe acute respiratory syndrome coronavirus-2 infection.

V G Benatto, J P A de Jesus, A A de Castro, L C Assis, T C Ramalho, F A La Porta

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Materials today. Communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. 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 at 2 institutions in 1 country.

V G BenattoLaboratory of Nanotechnology and Computational Chemistry, Federal University of Technology - Paraná, Londrina 86036-370, Brazil.
J P A de JesusLaboratory of Nanotechnology and Computational Chemistry, Federal University of Technology - Paraná, Londrina 86036-370, Brazil.
A A de CastroDepartment of Chemistry, Federal University of Lavras, Lavras 37200-000, Brazil.
L C AssisDepartment of Chemistry, Federal University of Lavras, Lavras 37200-000, Brazil.
T C RamalhoDepartment of Chemistry, Federal University of Lavras, Lavras 37200-000, Brazil.
F A La PortaLaboratory of Nanotechnology and Computational Chemistry, Federal University of Technology - Paraná, Londrina 86036-370, Brazil.
Universidade Federal de Lavras · BRUniversidade Tecnológica Federal do Paraná · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We carried out theoretical and experimental analyses of ZnO and ZnS nanoparticles as smart semiconductor materials in light-activated antimicrobial coating for application in masks. We used low-cost hydrothermally processable precursors to direct the growth of the coatings on cotton fabric. Both ZnO and ZnS coatings had high reactivities as disinfection agents in photocatalysis reactions for the degradation of a methylene blue dye solution. Also, these coatings showed excellent UV protection properties. For understanding at the molecular level, the broad-spectrum biological activities of the ZnO and ZnS coatings against Fusarium Oxysporum fungi, Escherichia coli bacteria, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus and their variants, were investigated computationally. Hexagonal Zn

Indexed as

COVID-19Hydro(solvo)thermal processingPhotocatalystsTheoretical calculationsUV protectionZnO and ZnS coatings

Identifiers

PMID36570033
PMCPMC9758762
OpenAlexW4311795996

What OpenQuestion holds

Textmetadata
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.