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bandgap of 2.26 eV that is used in many applications in optoelectronic devices. Compared
to the two dimensional (2D) thin-film semiconductors, one-dimensional (1D)
nanowires can have different electronic properties for potential novel applications.
In this work, we present the study of ZnTe nanowires (NWs) that are synthesized
through a simple vapor-liquid-solid (VLS) method. By controlling the presence or
the absence of Au catalysts and controlling the growth parameters such as growth
temperature, various growth morphologies of ZnTe, such as thin films and nanowires
can be obtained. The characterization of the ZnTe nanostructures and films was
performed using scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy
(EDX), high- resolution transmission electron microscope (HRTEM), X-ray
diffraction (XRD), photoluminescence (PL), Raman spectroscopy and light scattering
measurement. After confirming the crystal purity of ZnTe, two-terminal diodes and
three-terminal transistors were fabricated with both nanowire and planar nano-sheet
configurations, in order to correlate the nanostructure geometry to device performance
including field effect mobility, Schottky barrier characteristics, and turn-on
characteristics. Additionally, optoelectronic properties such as photoconductive gain
and responsivity were compared against morphology. Finally, ZnTe was explored in
conjunction with ZnO in order to form type-II band alignment in a core-shell nanostructure.
Various characterization techniques including scanning electron microscopy,
energy-dispersive X-ray spectroscopy , x-ray diffraction, Raman spectroscopy, UV-vis
reflectance spectra and photoluminescence were used to investigate the modification
of ZnO/ZnTe core/shell structure properties. In PL spectra, the eliminated PL intensity
of ZnO wires is primarily attributed to the efficient charge transfer process
occurring between ZnO and ZnTe, due to the band alignment in the core/shell structure. Moreover, the result of UV-vis reflectance spectra corresponds to the band
gap energy of ZnO and ZnTe, respectively, which confirm that the sample consists of
ZnO/ZnTe core/shell structure of good quality.
This creative project is an extension of the work being done as part of Senior Design in<br/>developing the See-Through Car Pillar, a system designed to render the forward car pillars in a car<br/>invisible to the driver so they can have an unobstructed view utilizing displays, sensors, and a<br/>computer. The first half of the paper provides the motivation, design and progress of the project, <br/>while the latter half provides a literature survey on current automobile trends, the viability of the<br/>See-Through Car Pillar as a product in the market through case studies, and alternative designs and <br/>technologies that also might address the problem statement.
The purpose of this project is to create a useful tool for musicians that utilizes the harmonic content of their playing to recommend new, relevant chords to play. This is done by training various Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) on the lead sheets of 100 different jazz standards. A total of 200 unique datasets were produced and tested, resulting in the prediction of nearly 51 million chords. A note-prediction accuracy of 82.1% and a chord-prediction accuracy of 34.5% were achieved across all datasets. Methods of data representation that were rooted in valid music theory frameworks were found to increase the efficacy of harmonic prediction by up to 6%. Optimal LSTM input sizes were also determined for each method of data representation.