Khan Asir Intisar, Yu Heshan, Zhang Huairuo, Goggin John R, Kwon Heungdong, Wu Xiangjin, Perez Christopher, Neilson Kathryn M, Asheghi Mehdi, Goodson Kenneth E, Vora Patrick M, Davydov Albert, Takeuchi Ichiro, Pop Eric
Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA.
Department of Materials Science and Engineering, University of Maryland, College Park, MD, 20742, USA.
Adv Mater. 2023 Jul;35(30):e2300107. doi: 10.1002/adma.202300107. Epub 2023 Jun 15.
Phase-change memory (PCM) is a promising candidate for neuro-inspired, data-intensive artificial intelligence applications, which relies on the physical attributes of PCM materials including gradual change of resistance states and multilevel operation with low resistance drift. However, achieving these attributes simultaneously remains a fundamental challenge for PCM materials such as Ge Sb Te , the most commonly used material. Here bi-directional gradual resistance changes with ≈10× resistance window using low energy pulses are demonstrated in nanoscale PCM devices based on Ge Sb Te , a new phase-change nanocomposite material . These devices show 13 resistance levels with low resistance drift for the first 8 levels, a resistance on/off ratio of ≈1000, and low variability. These attributes are enabled by the unique microstructural and electro-thermal properties of Ge Sb Te , a nanocomposite consisting of epitaxial SbTe nanoclusters within the Ge-Sb-Te matrix, and a higher crystallization but lower melting temperature than Ge Sb Te . These results advance the pathway toward energy-efficient analog computing using PCM.
相变存储器（PCM）是神经启发式、数据密集型人工智能应用的一个有前途的候选者，它依赖于PCM材料的物理属性，包括电阻状态的逐渐变化和具有低电阻漂移的多级操作。然而，对于最常用的材料如GeSbTe等PCM材料来说，同时实现这些属性仍然是一个基本挑战。在此，基于一种新型相变纳米复合材料GeSbTe的纳米级PCM器件展示了使用低能量脉冲实现的约10倍电阻窗口的双向渐变电阻变化。这些器件在前8个电平显示出13个电阻电平且具有低电阻漂移、约1000的电阻开/关比以及低变异性。这些属性是由GeSbTe独特的微观结构和电热特性实现的，GeSbTe是一种由Ge - Sb - Te基质内的外延SbTe纳米团簇组成的纳米复合材料，其结晶温度高于但熔化温度低于GeSbTe。这些结果推动了使用PCM实现节能模拟计算的进程。
