Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.
Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.
Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.
Author ORCID Identifier
https://orcid.org/0000-0002-7425-3305
AccessType
Open Access Dissertation
Document Type
dissertation
Degree Name
Doctor of Philosophy (PhD)
Degree Program
Electrical and Computer Engineering
Year Degree Awarded
2024
Month Degree Awarded
February
First Advisor
Jun Yao
Subject Categories
Electronic Devices and Semiconductor Manufacturing | Hardware Systems | Nanotechnology Fabrication
Abstract
Neuromorphic systems built from memristors that emulate bioelectrical information processing in the brain may overcome the limitations of traditional computing architectures. However, functional emulation alone may still not attain all the merits of bio-computation, which uses action potentials of 50–120 mV at least ten times lower than signal amplitude in conventional electronics to achieve extraordinary power efficiency and effective functional integration. Reducing the functional voltage in memristors to this biological amplitude can thus advance neuromorphic engineering and bio-emulated integration. In this dissertation, we demonstrate a type of bio-voltage memristor whose operation voltage is as low as the biological amplitude (e.g., 50-120 mV). The device is made of silver active electrodes, together with dielectric protein nanowires harvested from microbe G. Sulfurreducens, which is considered the key factor for bio-voltage switching, possibly attributed to the protein nanowires catalyze metallization. With the advantage of low-voltage switching, we develop the parameter-matched artificial synapse and neurons for the wearable bio-electronic interface, as well as the comprehensive artificial sensory system harnessing the function of bio-signal fusion and dispersion. In addition, we also propose a new strategy to address the sneak-path issue by utilizing the bio-voltage memristor’s retention property. The unidirectional current flow in the bio-voltage memristor suppresses the sneak-path current, whereas the transient-retention window is exploited for bidirectional programming. This methodology was also extended to other technology-matured electrical components (e.g., diode) for high-efficient in-situ neuromorphic computing by studying diode’s reverse recovery.
DOI
https://doi.org/10.7275/36322623
Recommended Citation
Fu, Tianda, "BIO-VOLTAGE MEMRISTOR: FROM DEVICE TO APPLICATIONS" (2024). Doctoral Dissertations. 3048.
https://doi.org/10.7275/36322623
https://scholarworks.umass.edu/dissertations_2/3048
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Included in
Electronic Devices and Semiconductor Manufacturing Commons, Hardware Systems Commons, Nanotechnology Fabrication Commons