Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 337

The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.

Antimicrobial Metal Nanomaterials: From Passive to Stimuli‐Activated Applications

Open access
Cheeseman, Samuel, Christofferson, Andrew J., Kariuki, Rashad, Cozzolino, Daniel, Daeneke, Torben, Crawford, Russell J., Truong, Vi Khanh, Chapman, James, Elbourne, Aaron·2020·Advanced Science

Abstract

The development of antimicrobial drug resistance among pathogenic bacteria and fungi is one of the most significant health issues of the 21st century. Recently, advances in nanotechnology have led to the development of nanomaterials, particularly metals that exhibit antimicrobial properties. These metal nanomaterials have emerged as promising alternatives to traditional antimicrobial therapies. In this review, a broad overview of metal nanomaterials, their synthesis, properties, and interactions with pathogenic micro‐organisms is first provided. Secondly, the range of nanomaterials that demonstrate passive antimicrobial properties are outlined and in‐depth analysis and comparison of stimuli‐responsive antimicrobial nanomaterials are provided, which represent the next generation of microbiocidal nanomaterials. The stimulus applied to activate such nanomaterials includes light (including photocatalytic and photothermal) and magnetic fields, which can induce magnetic hyperthermia and kinetically driven magnetic activation. Broadly, this review aims to summarize the currently available research and provide future scope for the development of metal nanomaterial‐based antimicrobial technologies, particularly those that can be activated through externally applied stimuli.

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 · 10.1002/advs.201902913

Cites

32 of 32 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

Cited by

See all 337

Metadata

Authors
Cheeseman, S., Christofferson, A. J., Kariuki, R., Cozzolino, D., Daeneke, T., Crawford, R. J., Truong, V. K., Chapman, J., & Elbourne, A.
Venue
Advanced Science
Publisher
Wiley
Published
2020-04-06
Volume
7
Issue
10
Pages
1902913-1902913
ISSN
2198-3844 (ISSN-L)
OpenAlex
W3015599600
Cited by
337
References
32
FWCI
18.27
Type
journal article
Language
en
Open access
gold

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.