Zhang, Lu
(2016)
UNDERSTANDING MEMRISTORS AND SELECTORS FOR FUTURE STORAGE AND COMPUTING APPLICATIONS: MODELING AND ANALYSIS.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
The memristor and selector devices are the most promising candidates in the research of emerging memory technologies and neuromorphic computing applications. To understand the device properties and guide for future applications, models for those devices based on physical mechanisms are essential. We developed models for two popular memristors and a selector.
We developed a SPICE-compatible compact model of TiO2-TiO2-x memristors based on classic ion transportation theory. Our model is shown to simulate important dynamic memristive properties like real-time memristance switching, which are critical in memristor-based analog circuit designs. The model, as well as its analytical approximation, is validated with the experimentally obtained data from real devices. Minor deviations of our model from the measured data are also analyzed and discussed.
We illustrate a heuristic two-state-variable memristor model of charged O vacancy drift resistive switches that includes the effects of internal Joule heating on both the electronic transport and the drift velocity (i.e. switching speed) of vacancies in the switching material. The dynamical state variables correspond to the cross-sectional area of a conducting channel in the device and the gap between the end of the channel and one of the electrodes. The model was calibrated against low voltage pulse-sweep and state-test data collected from a TaOx memristor so that the contributions of the channel gap, area and temperature to switching can be analyzed. The model agrees well with experimental results for long switching times and low-to-intermediate voltage operation.
A selector device that demonstrates high nonlinearity, low switching voltage and volatility was fabricated using HfOx materials with Ag electrodes. The electronic conductance of such volatile selector device was studied under both static and dynamic conditions, with DC and AC measurements respectively. From experimental observations, a compact model is developed in this study to illustrate the physical process of the formation and dissipation of Ag filament for electron transport through the device. A dynamic capacitance model is used to fit the transient current traces under different voltage bias through the device and allow the extraction of parameters associated with the various parasitic components in the device.
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| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
|
| Date: |
20 September 2016 |
| Date Type: |
Publication |
| Defense Date: |
7 July 2016 |
| Approval Date: |
20 September 2016 |
| Submission Date: |
15 July 2016 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
130 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Electrical Engineering |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
memristor, selector, modeling, ion transport theory, state variable, dynamic conductance and capacitance |
| Date Deposited: |
20 Sep 2016 18:41 |
| Last Modified: |
15 Nov 2016 14:34 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/28634 |
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