Indexed by: Journal paper

First Author: 赵锐哲,李鑫

Correspondence Author: TONG HAO,缪向水

Co-author: 缪向水

Journal: Applied Physics Letters

Affiliation of Author(s): 华中科技大学

Discipline: Engineering

First-Level Discipline: Electronic Science And Technology

Document Type: J

Volume: 123

Issue: 3

Page Number: 033503

Key Words: Telecommunication networks, Electrical circuits, Convolutional neural network, Artificial neural networks, Phase change memories, Optical imaging, Amorphous materials, Scanning electron microscopy, Nanoribbons, Chemical processes

DOI number: 10.1063/5.0154995

Date of Publication: 4512-05-01

Abstract: Phase change memory (PCM) is one of the most mature technologies for non-von Neumann computing. However, abrupt amorphization becomes a barrier for training artificial neural networks, due to limitations of the inherent operational mechanism of phase change materials. The devices can achieve a gradual conductance change in the crystallization process, while the conductance change for amorphization process is much more abrupt. This work presents a possible explanation for the RESET abrupt change issue in T-shaped devices, based on the analysis of the volume and connectivity of the amorphous and crystalline regions. Using this model, a nanoribbon device for analog PCM targeting neural network applications is designed, fabricated, and characterized. The designed device can realize a gradual RESET without changing the amplitude and width of RESET pulses. Using a nanoribbon device as a single synapse in the designed array reduces the number of SET operations needed to achieve the same accuracy in convolutional neural network simulation by 75%, which implies a significant reduction in power and time consumption. This work provides an effective way to implement gradual RESET for PCM devices.

Links to published journals: https://pubs.aip.org/aip/apl/article/123/3/033503/2903061/A-nanoribbon-device-for-analog-phase-change-memory