Photoluminescence and Photocatalytic Properties of MWNTs Decorated with Fe-Doped ZnO Nanoparticles.
Adriana PopaMaria StefanSergiu Gabriel MacaveiLaura Elena MuresanCristian LeosteanCornelia Veronica Floare-AvramDana TolomanPublished in: Materials (Basel, Switzerland) (2023)
The present work reports the photoluminescence (PL) and photocatalytic properties of multi-walled carbon nanotubes (MWCNTs) decorated with Fe-doped ZnO nanoparticles. MWCNT:ZnO-Fe nanocomposite samples with weight ratios of 1:3, 1:5 and 1:10 were prepared using a facile synthesis method. The obtained crystalline phases were evidenced by X-ray diffraction (XRD). X-ray Photoelectron spectroscopy (XPS) revealed the presence of both 2+ and 3+ valence states of Fe ions in a ratio of approximately 0.5. The electron paramagnetic resonance EPR spectroscopy sustained the presence of Fe 3+ ions in the ZnO lattice and evidenced oxygen vacancies. Transmission electron microscopy (TEM) images showed the attachment and distribution of Fe-doped ZnO nanoparticles along the nanotubes with a star-like shape. All of the samples exhibited absorption in the UV region, and the absorption edge was shifted toward a higher wavelength after the addition of MWCNT component. The photoluminescence emission spectra showed peaks in the UV and visible region. Visible emissions are a result of the presence of defects or impurity states in the material. All of the samples showed photocatalytic activity against the Rhodamine B (RhB) synthetic solution under UV irradiation. The best performance was obtained using the MWCNT:ZnO-Fe(1:5) nanocomposite samples, which exhibited a 96% degradation efficiency. The mechanism of photocatalytic activity was explained based on the reactive oxygen species generated by the nanocomposites under UV irradiation in correlation with the structural and optical information obtained in this study.
Keyphrases
- visible light
- quantum dots
- electron microscopy
- walled carbon nanotubes
- high resolution
- aqueous solution
- energy transfer
- reduced graphene oxide
- reactive oxygen species
- physical activity
- magnetic resonance imaging
- single molecule
- deep learning
- solid state
- machine learning
- radiation therapy
- convolutional neural network
- body mass index
- healthcare
- electronic health record
- municipal solid waste