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Publication Citation: Highly selective GaN-nanowire/TiO2-nanocluster hybrid sensors for detection of benzene and related environment pollutants

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Author(s): Norman A. Sanford;
Title: Highly selective GaN-nanowire/TiO2-nanocluster hybrid sensors for detection of benzene and related environment pollutants
Published: June 15, 2011
Abstract: Nanowire‹nanocluster hybrid chemical sensors were realized by functionalizing gallium nitride (GaN) nanowires (NWs) with titanium dioxide (TiO2) nanoclusters for selectively sensing benzene and other related aromatic compounds. Hybrid sensor devices were developed by fabricating two-terminal devices using individual GaN NWs followed by the deposition of TiO2 nanoclusters using RF magnetron sputtering. The sensor fabrication process employed standard microfabrication techniques. X-ray diffraction and high-resolution analytical transmission electron microscopy using energy-dispersive x-ray and electron energy-loss spectroscopies confirmed the presence of the anatase phase in TiO2 clusters after post-deposition anneal at 700 ◦C. A change of current was observed for these hybrid sensors when exposed to the vapors of aromatic compounds (benzene, toluene, ethylbenzene, xylene and chlorobenzene mixed with air) under UV excitation, while they had no response to non-aromatic organic compounds such as methanol, ethanol, isopropanol, chloroform, acetone and 1,3-hexadiene. The sensitivity range for the noted aromatic compounds except chlorobenzene were from 1% down to 50 parts per billion (ppb) at room temperature. By combining the enhanced catalytic properties of the TiO2 nanoclusters with the sensitive transduction capability of the nanowires, an ultra-sensitive and selective chemical sensing architecture is demonstrated. We have proposed a mechanism that could qualitatively explain the observed sensing behavior.
Citation: Nanotechnology
Volume: 22
Pages: pp. 2 - 11
Research Areas: Nanotech/Environment, Health & Safety, Nanomanufacturing, Hybrid Materials, Nanomaterials
PDF version: PDF Document Click here to retrieve PDF version of paper (1MB)