19 October 2012 MOCVD growth and characterization of ZnO nanowire arrays for advanced ultraviolet detectors
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Abstract
Zinc oxide (ZnO) provides a unique wide bandgap biocompatible material system exhibiting both semiconducting and piezoelectric properties, and is a versatile functional material that has a diverse group of growth morphologies. Bulk ZnO has a bandgap of 3.37 eV that corresponds to emissions in the solar blind ultraviolet (UV) spectral band (240-280 nm). We have grown highly ordered vertical arrays of ZnO nanowires (NWs) and nanorods using a metal organic chemical vapor deposition (MOCVD) growth process on Si(111), SiO2, and sapphire substrates. The structural and optical properties of the grown vertically aligned ZnO nanostructure arrays were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), and photoluminescence (PL) measurements. The unique diffraction pattern for ZnO(002) concurred with the SEM inspection indicating vertical orientation of the NWs and nanorods. UV detectors based on ZnO NWs offer high UV sensitivity and low visible sensitivity for applications such as missile plume detection and threat warning. An analytical model that can predict sensor performance with and without gain for a desired UV band of interest has also been developed that has the potential for substantial improvements in sensor performance and reduction in size for a variety of threat warning applications. In addition, testing and characterization of photomultiplier tubes (PMTs) exposed to eight individual UV LEDs having peak wavelengths ranging from 248 nm to 370 nm has been performed to provide a relative UV detection performance benchmark. Compared to PMTs, the NW arrays are expected to exhibit low noise, extended lifetimes, high quantum efficiency, and very low power requirements.
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Abdiel Rivera, John Zeller, Tariq Manzur, Ashok Sood, Mehdi Anwar, "MOCVD growth and characterization of ZnO nanowire arrays for advanced ultraviolet detectors", Proc. SPIE 8540, Unmanned/Unattended Sensors and Sensor Networks IX, 854008 (19 October 2012); doi: 10.1117/12.979218; https://doi.org/10.1117/12.979218
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