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Doctor of Philosophy (PhD)
Year Degree Awarded
Month Degree Awarded
Stephen S. Nonnenmann
Materials Science and Engineering | Nanoscience and Nanotechnology | Semiconductor and Optical Materials
Novel nonvolatile memory technologies garner intense research interest as conventional ash devices approach their physical limit. Memristors, often comprising an insulating thin film between two metal electrodes to constitute a class of two-terminal devices, enable a variety of important large data storage and data-driven computing applications. In addition to nonvolatile behavior, other features such as high scalability, low power consumption, and sub-nanosecond response times make memristors among the most attractive candidate systems. Their strength in electronic storage relies on the unique properties of the tunable variations in resistance induced from the accumulation of charged defects based on the applied bias history.
Metal oxides serve as the most common "storage" materials, demonstrating advantages including simple fabrication, high reliability, and fast operation speeds. While the basic working concepts and the underlying conduction mechanisms have been established through combined experimental and simulation studies, the role of metal insulator interface, which acts as the crux of coupled electronic-ionic interactions, has not been fully understood. Continuous scaling, for the purpose of high density memories, also requires a detailed understanding of the switching behavior and transport mechanism. Other technical challenges include the development of innovative, low-cost fabrication methods that effectively enable high-performance structures as an alternative to complicated process modules. Stable retention and endurance of the switching characteristics, as well as uniformity of the switching parameters to ensure a valid program/read operation also represent significant challenges. Studies in device and materials optimization remain in the formative stages, and thus motivate this work to drive progress in the most attractive areas, including size dependent behavior and switching performance of memristors.
This collection of work aims to correlate resistive switching within metal oxide based memristors with the fundamental physical mechanisms and material properties on a highly localized scale. Chapter 3 relates the device size and the resulting performance matrix of memory cells in the first step towards fully understanding the scaling projection and reliability issues that affect nanoscale architectures. Chapter 4 demonstrates a convective self-assembly, transferable approach that enables the fabrication of highly-controlled nanoribbon comprising solution-processed nanocrystals, providing multiple degrees of freedom for understanding the interfacial memristive behavior of functional oxide nanostructures. As a powerful tool in the study of resistive switching, conductive AFM probes the homogeneity of the charge transport properties, thus offering electrical information by locally applied bias when it is placed in direct contact with desired regime. Finally we also focus on the improving the cycle-to-cycle uniformity by embedding nanostructure into conventional metal-insulator-metal (MIM) geometry in Chapter 5. This improvement is attributed to the concentration of electric field when metal nanoislands are inserted into the oxide film matrix. The details of this work will highlight the tunable and optimizable template-driven method that can be applied on any memristive systems, yielding a superior uniformity of operating voltage and resistance states.
In summary, this thesis promotes the development of novel, high-performance metal oxide based memristors enabled by the availability of new, nanostructured materials and innovations in device structure engineering. The switching performance, underlying mechanisms, area/defect concentration effects, development of solution-processed nanocrystals assemblies and chemistries, and highly enhanced uniformity in memristors are addressed by combining systematic deposition approaches with the advanced nanoscopic observation of the conducting filament, leading to the strongest competitor among future nonvolatile memory solution.
Wang, Jiaying, "PROBING LOCAL VACANCY-DRIVEN RESISTIVE SWITCHING IN METAL OXIDE NANOSTRUCTURES" (2018). Doctoral Dissertations. 1403.