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Antimicrobial Copper-Based Materials and Coatings: Potential Multifaceted Biomedical Applications
Abstract
Surface contamination by microbes leads to several detrimental consequences like hospital- and device-associated infections. One measure to inhibit surface contamination is to confer the surfaces with antimicrobial properties. Copper's antimicrobial properties have been known since ancient times, and the recent resurgence in exploiting copper for application as antimicrobial materials or coatings is motivated by the growing concern about antibiotic resistance and the pressure to reduce antibiotic use. Copper, unlike silver, demonstrates rapid and high microbicidal efficacy against pathogens that are in close contact under ambient indoor conditions, which enhances its range of applicability. This review highlights the mechanisms behind copper's potent antimicrobial property, the design and fabrication of different copper-based antimicrobial materials and coatings comprising metallic copper/copper alloys, copper nanoparticles or ions, and their potential for practical applications. Finally, as the antimicrobial coatings market is expected to grow, we offer our perspectives on the implications of increased copper release into the environment and the potential ecotoxicity effects and possibility of development of resistant genes in pathogens.
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Metadata
- Authors
- Mitra, D., Kang, E.-T., & Neoh, K. G.
- Venue
- ACS Applied Materials & Interfaces
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-12-27
- Volume
- 12
- Issue
- 19
- Pages
- 21159-21182
- ISSN
- 1944-8244 (ISSN-L)
- 1944-8252
- OpenAlex
- W2998065350
- Cited by
- 322
- References
- 128
- FWCI
- 7.09
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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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.