Device Stack Optimization for Protonic Non-Volatile Programmable Resistors

Analog computing could alleviate computational bottlenecks in digital deep learning systems by utilizing local information processing through the physical properties of devices, such as electrochemical ion-intercalation in three-terminal devices where channel resistance is modulated by ionic exchange via an electrolyte. Previous work has demonstrated such ionic programmable resistors featuring WO₃ as the channel, phosphorous-doped SiO₂ (PSG) as the electrolyte, Pd as the gate reservoir, and protons as the ions. This thesis aimed to optimize the device stack in four directions and demonstrated a symmetric WO₃-PSG-WO₃ structure in a CMOS-compatible process, with the help of circular transfer length model (CTLM), which efficiently examines the resistance properties of WO₃. We have explored: (a) device protonation as part of the fabrication process, (b) encapsulation preventing proton depletion during device fabrication and operation, (c) contact metal optimization to replace gold with a CMOS-compatible material, (d) PSG evaluation vehicle for device performance optimization. The symmetric device combining all the stack optimizations features non-volatile and repeatable conductance modulation with voltage pulses.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Shen, Dingyu

Advisor dc:contributor.advisor

• del Alamo, Jesús A.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/156286

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/156286