Influence of erbium doping on zinc oxide nanoparticles: Structural, optical and antimicrobial activity
[Display omitted] •Pure and Er-doped ZnO were synthesized by a wet chemical method.•XRD shows that Er-doped ZnO at high at.% kept their hexagonal structure.•The optical band gap was improved as Er at.% increased.•Antimicrobial activity of Er-doped ZnO was tested against Staphylococcus aureus and Esc...
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Veröffentlicht in: | Applied surface science 2022-02, Vol.575, p.151764, Article 151764 |
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Sprache: | eng |
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•Pure and Er-doped ZnO were synthesized by a wet chemical method.•XRD shows that Er-doped ZnO at high at.% kept their hexagonal structure.•The optical band gap was improved as Er at.% increased.•Antimicrobial activity of Er-doped ZnO was tested against Staphylococcus aureus and Escherichia coli.•ANN model was trained with lab data, such model predicts absorbance with a 1–2% error.
Antimicrobial activity of the Zn1-xErxO (0, 1, 5, 10 at.%) nanoparticles were tested against Staphylococcus aureus and Escherichia coli. The nanoparticles were successfully synthesized by wet chemical route, where polyvinyl alcohol and sucrose were used. The influence of erbium content in structural, optical, and antimicrobial activity was analyzed. The average crystallite size is under 15 nm for all the samples according to X-ray diffraction results, and no secondary phases were observed even at high erbium content. Optical results exhibit a blue shift in the ultra-violet region. The X-ray photoelectron spectroscopy analysis confirmed the variations of Zn/O ratio, together with particles size and band gap are key factor in antimicrobial properties. The microbiological essays exhibit to these nanoparticles as a high potential agent with antibacterial activity versus S. aureus, with lower impact in E. coli. The absorbance results of these assays were used in two theoretical approaches. At first, Gompertz model used in the regression analysis showed the best fit for bacterial growth. Additionally, an artificial neural network was trained to forecast the result of new experiments, showing a good performance. |
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ISSN: | 0169-4332 1873-5584 |
DOI: | 10.1016/j.apsusc.2021.151764 |