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Supported MOCVD TiO2 Thin Films Grown on Modified Stainless Steel Mesh for Sensing Applications
Naida El Habra1, Francesca Visentin1, Francesca Russo2
1Institute of Condensed Matter Chemistry and Technologies for Energy (ICMATE), National Research Council (CNR), Corso Stati Uniti 4, 35127 Padova, Italy.
Titanium dioxide (TiO2) thin films on etched metal mesh show enhanced performance as chemical oxygen demand (COD) sensors. Optimized etching and MOCVD growth boost TiO2
Area of Science:
- Materials Science
- Environmental Sensing
- Nanotechnology
Background:
- Semiconductor metal oxides, particularly titanium dioxide (TiO2), are vital sensing materials.
- TiO2 thin films offer stability, non-toxicity, and photocatalytic properties for sensor applications.
- Chemical oxygen demand (COD) sensors utilize TiO2's photocatalysis to oxidize organic pollutants.
Purpose of the Study:
- To develop nanostructured TiO2 thin films on metallic mesh for enhanced COD sensing.
- To optimize inorganic acid-based etching protocols for increased surface area.
- To evaluate the photocatalytic activity of the developed TiO2 thin films as COD sensors.
Main Methods:
- Low-pressure metal organic chemical vapor deposition (MOCVD) for TiO2 film growth on AISI 316 mesh.
- Development and testing of inorganic acid-based chemical etching protocols (HCl/H2SO4 at 55 °C).
- Characterization using SEM, XRD, EDX, and XPS; photocatalytic testing with model pollutants (ISO 10678:2010).
Main Results:
- Optimized HCl/H2SO4 etching at 55 °C yielded the most suitable surface morphology for increased surface area.
- MOCVD-grown TiO2 films on etched mesh demonstrated significantly enhanced photocatalytic activity.
- The best performing sensor showed a 60% increase in activity, degrading 66 µmol of MB per square meter per hour.
Conclusions:
- Nanostructured TiO2 thin films on optimized etched metallic mesh represent a promising advancement in COD sensor technology.
- The developed fabrication method enhances surface area and photocatalytic efficiency.
- This approach offers a viable pathway for creating high-performance environmental sensors.
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