journal article·2021-11Open access

Antimicrobial surfaces: a review of synthetic approaches, applicability and outlook

Urbashi Mahanta, Mudrika Khandelwal, Atul Suresh Deshpande

Journal of Materials Science· Volume 56· Issue 32

Abstract

The rapid spread of microorganisms such as bacteria, fungi, and viruses can be extremely detrimental and can lead to seasonal epidemics or even pandemic situations. In addition, these microorganisms may bring about fouling of food and essential materials resulting in substantial economic losses. Typically, the microorganisms get transmitted by their attachment and growth on various household and high contact surfaces such as doors, switches, currency. To prevent the rapid spread of microorganisms, it is essential to understand the interaction between various microbes and surfaces which result in their attachment and growth. Such understanding is crucial in the development of antimicrobial surfaces. Here, we have reviewed different approaches to make antimicrobial surfaces and correlated surface properties with antimicrobial activities. This review concentrates on physical and chemical modification of the surfaces to modulate wettability, surface topography, and surface charge to inhibit microbial adhesion, growth, and proliferation. Based on these aspects, antimicrobial surfaces are classified into patterned surfaces, functionalized surfaces, superwettable surfaces, and smart surfaces. We have critically discussed the important findings from systems of developing antimicrobial surfaces along with the limitations of the current research and the gap that needs to be bridged before these approaches are put into practice. Supplementary information The online version contains supplementary material available at 10.1007/s10853-021-06404-0.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Bacterial biofilms and quorum sensing · Surface Modification and Superhydrophobicity · Polymer Surface Interaction Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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