Monte Carlo Simulations on Resistive Switching Memristor Modeling

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dc.contributor.advisorSpanos, Pol D
dc.creatorKetron, Tyler Wayne
dc.date.accessioned2020-04-23T16:22:10Z
dc.date.available2021-05-01T05:01:11Z
dc.date.created2020-05
dc.date.issued2020-04-23
dc.date.submittedMay 2020
dc.date.updated2020-04-23T16:22:10Z
dc.description.abstractPromising attributes in data processing such as faster read/write times, longer retention, and superior scalability have put resistive switching memristors in the spotlight of research. This thesis presents a numerical method to determine the variability in switching that different memristors exhibit. Current-voltage relationships and cyclic voltage sweeps are gathered from specific memristor devices with various geometrical configurations. Using the inverse sampling method and Monte Carlo simulations, the variation in switching characteristics for these memristors are characterized by a phenomenological approach. Further, randomness is introduced to assess the effect of geometric parameters in a probabilistic model and trends within the response. The model is validated by comparison with experimental data reported in the literature. The presented model is effective in capturing the variation in memristor responses. This, has been shown to be an important attribute in neuromorphic computing applications, and can aid experimentalists and manufacturers in refining memristor designs.
dc.embargo.terms2021-05-01
dc.format.mimetypeapplication/pdf
dc.identifier.citationKetron, Tyler Wayne. "Monte Carlo Simulations on Resistive Switching Memristor Modeling." (2020) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/108343">https://hdl.handle.net/1911/108343</a>.
dc.identifier.urihttps://hdl.handle.net/1911/108343
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectMemristors
dc.subjectmemristive systems
dc.subjecthysteresis
dc.subjectMonte Carlo
dc.subjectrandomness
dc.titleMonte Carlo Simulations on Resistive Switching Memristor Modeling
dc.typeThesis
dc.type.materialText
thesis.degree.departmentMechanical Engineering
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
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