Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 285

The DOI matches its Crossref record; 347 of the 347 references it cites were found in a registry or an index.

Antibacterial and Antiviral Functional Materials: Chemistry and Biological Activity toward Tackling COVID-19-like Pandemics

Open access
Balasubramaniam, Bhuvaneshwari, Prateek, Ranjan, Sudhir, Saraf, Mohit, Kar, Prasenjit, Singh, Surya Pratap, Thakur, Vijay Kumar, Singh, Anand, Gupta, Raju Kumar·2021·ACS Pharmacology & Translational Science

Abstract

The ongoing worldwide pandemic due to COVID-19 has created awareness toward ensuring best practices to avoid the spread of microorganisms. In this regard, the research on creating a surface which destroys or inhibits the adherence of microbial/viral entities has gained renewed interest. Although many research reports are available on the antibacterial materials or coatings, there is a relatively small amount of data available on the use of antiviral materials. However, with more research geared toward this area, new information is being added to the literature every day. The combination of antibacterial and antiviral chemical entities represents a potentially path-breaking intervention to mitigate the spread of disease-causing agents. In this review, we have surveyed antibacterial and antiviral materials of various classes such as small-molecule organics, synthetic and biodegradable polymers, silver, TiO 2, and copper-derived chemicals. The surface protection mechanisms of the materials against the pathogen colonies are discussed in detail, which highlights the key differences that could determine the parameters that would govern the future development of advanced antibacterial and antiviral materials and surfaces.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acsptsci.0c00174

Cites

347 of 347 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

1 retracted

Cited by

See all 285

Metadata

Authors
Balasubramaniam, B., Prateek, Ranjan, S., Saraf, M., Kar, P., Singh, S. P., Thakur, V. K., Singh, A., & Gupta, R. K.
Venue
ACS Pharmacology & Translational Science
Published
2020-12-29
Volume
4
Issue
1
Pages
8-54
ISSN
2575-9108 (ISSN-L)
OpenAlex
W3114969372
Cited by
285
References
347
FWCI
15.95
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.