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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 lm 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 metalinsulator
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 e ectively 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 signicant 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 rst step towards fully understanding the scaling
projection and reliability issues that a ect 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
o ering 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
eld when metal nanoislands are inserted into the oxide lm 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 e ects, development of solutionprocessed
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 lament, leading to the strongest
competitor among future nonvolatile memory solution.
Wang, Jiaying and Wang, Jiaying, "PROBING LOCAL VACANCY-DRIVEN RESISTIVE SWITCHING IN METAL OXIDE NANOSTRUCTURES" (2018). Doctoral Dissertations. 1403.
Available for download on Sunday, September 01, 2019