journal article·2021-01

An antimicrobial bio-based polymer foam from ZnO-stabilised pickering emulsion templated polymerisation

Xuwang Tian, Xiaohui Ge, Mengya Guo, Jinxia Ma, Zhiqian Meng, Peng Lu

Journal of Materials Science· Volume 56· Issue 2
Publisher page

Abstract

Pickering emulsion templating has become an effective method for preparing polymer foam with precise morphology. The present study reports an antibacterial foam prepared through the polymerisation of acrylated epoxidised soybean oil (AESO) in the external phase of a water-in-oil (w/o) Pickering emulsion. Zinc oxide (ZnO) was used to stabilise water into the AESO and endow the resulting foam with antimicrobial characteristics. The effects of the oil-to-water mass ratio (3:1–1:2) and ZnO concentration (0.1–3.0 wt%) on the stability of the emulsion were studied. The emulsions were characterised in terms of the volume fraction of the emulsion phase, the viscosity of the emulsion, and the interfacial tension. The emulsion prepared with an oil-to-water ratio of 3:2 and ZnO concentration of 1.0 wt% showed strong stability. Absorption of ZnO at the oil–water interface was observed by using graphene oxide quantum dot-doped ZnO as a fluorescent marker. Antibacterial foam was formed by heating the Pickering emulsion at 120 °C for 3 h. Scanning electron microscope images show that the foam has a closed-cell structure with an average pore diameter of approximately 200 μm. The prepared foam showed antibacterial activity with an inhibition rate against E.coli of 99%. The production of a porous polymer from sustainable materials through ZnO-stabilised Pickering emulsion templating provides a facile method for preparing innovative, functional bio-based materials.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Pickering emulsions and particle stabilization · Advanced Polymer Synthesis and Characterization · Electrospun Nanofibers in Biomedical Applications

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

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