论文类型：期刊论文
第一作者：赵锐哲,李鑫
通讯作者：童浩,缪向水
合写作者：缪向水
发表刊物：Applied Physics Letters
所属单位：华中科技大学
学科门类：工学
一级学科：电子科学与技术
文献类型：J
卷号：123
期号：3
页面范围：033503
关键字：Telecommunication networks, Electrical circuits, Convolutional neural network, Artificial neural networks, Phase change memories, Optical imaging, Amorphous materials, Scanning electron microscopy, Nanoribbons, Chemical processes
DOI码：10.1063/5.0154995
发表时间：4512-05-01
摘要：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.
发布期刊链接：https://pubs.aip.org/aip/apl/article/123/3/033503/2903061/A-nanoribbon-device-for-analog-phase-change-memory