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A Continuous-flow Photocatalytic Reactor for the Precisely Controlled Deposition of Metallic Nanoparticles
Published on: April 10, 2019
Controllable synthesis of graphene-based titanium dioxide nanocomposites by atomic layer deposition
Xiangbo Meng1, Dongsheng Geng, Jian Liu
1Department of Mechanical and Materials Engineering, The University of Western Ontario, London, ON, N6A 5B8, Canada.
Nanotechnology
|March 12, 2011
Summary
Atomic layer deposition (ALD) precisely synthesized titanium dioxide-graphene nanosheet nanocomposites. This controllable method allows tunable morphology and phase for advanced applications.
Area of Science:
- Materials Science
- Nanotechnology
- Chemical Engineering
Background:
- Graphene-based nanocomposites offer unique properties for various applications.
- Controlling the synthesis of metal oxide nanostructures on graphene is crucial.
- Atomic Layer Deposition (ALD) provides precise control over thin film growth.
Purpose of the Study:
- To synthesize graphene-based metal oxide nanocomposites using ALD.
- To investigate the controllable synthesis of titanium dioxide (TiO(2)) on graphene nanosheets (GNS).
- To explore the tunability of TiO(2) morphology and phase using ALD.
Main Methods:
- Utilized Atomic Layer Deposition (ALD) for nanocomposite synthesis.
- Employed titanium isopropoxide and water as precursors for TiO(2) deposition.
- Varied ALD cycles and growth temperatures to control TiO(2) characteristics.
Main Results:
- Successfully synthesized TiO(2)-graphene nanosheet (TiO(2)-GNS) nanocomposites.
- Demonstrated ALD's capability for controllable TiO(2) deposition.
- Achieved tunable TiO(2) morphologies (nanoparticles to nanofilms) and structural phases (amorphous to crystalline) by adjusting ALD cycles and temperature.
Conclusions:
- ALD is a highly effective method for producing tunable TiO(2)-GNS nanocomposites.
- The synthesized nanocomposites exhibit significant potential for applications in photocatalysis, energy storage, and sensing.
- Further research into growth mechanisms can optimize material properties for specific applications.

