M.Sc thesis defense: "Self-Integrating Memories Based on Guided Nanowires"

Date:
24
Thursday
November
2022
Lecture / Seminar
Time: 11:00-12:00
Location: Helen and Milton A. Kimmelman Building
Lecturer: Omri Ron
Organizer: Department of Molecular Chemistry and Materials Science
Details: M.Sc student in Prof. Ernesto Joselevich's group
Abstract: Neuromorphic computing designs have an important role in the modern ‘big data ... Read more Neuromorphic computing designs have an important role in the modern ‘big data’ era, as they are suitable for processing large amount of information in short time, eliminating the von Neumann (VN) bottleneck. The neuromorphic hardware, taking its inspiration from the human brain, is designed to be used for artificial intelligence tasks via physical neural networks, such as speech or image recognition, bioinformatics, visual art processing and much more. The memristor (memory + resistor), is one of the promising building blocks for this hardware, as it mimics the behavior of a human synapse, and can be used as an analog non-volatile memory. The memristor has been proven as a viable memory element and has been used for constructing resistive random access memory (RRAM) as a replacement for current VN hardware. However, the mechanism of operation and the conducting bridge formation mechanisms in electrochemical metallization memristors still require further investigation. A planar single-nanowire (NW) based memristor is a good solution for elucidating the mechanism of operation, thanks to the high localization of switching events, allowing in-situ investigation as well as post-process analysis. Our group, which has developed the guided-growth approach to grow guided planar NWs on different substrates, has used this method to integrate guided epitaxial NWs into functional devices such as field-effect transistors (FETs), photodetectors and even address decoders. However, the guided-growth approach has not been used for creating memristors up to date. In this work, I successfully synthesized guided NWs of two metal-oxides on flat and faceted sapphire substrates – ZnO and β-Ga2O3 were successfully grown in the VLS mechanism as surface guided NWs. I successfully grew planar guided β-Ga2O3 NWs on six different sapphire substrates, for the first time as far as we know. We characterized the newly grown β-Ga2O3 NWs with SEM, TEM, EDS and Raman spectroscopy. The monoclinic NWs grew along surprising directions on the flat sapphire surfaces and I demonstrated a new mode of growth – epitaxy favored growth on a faceted surface, when graphoepitaxy is also possible. I created electrochemical metallization memristors with the obtained NWs and successfully demonstrated the effect of resistive switching for β-Ga2O3 guided NW based devices. With the abovementioned achievements, we expanded the guided-growth approach on flat and faceted sapphire surfaces, and opened the opportunity for creating surface guided-NW based neuromorphic hardware.
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