Multifilamentary switching of Cu/SiOx memristive devices with a Ge-implanted a-Si underlayer for analog synaptic devices - Kim, Keonhee; Lim, Jae Gwang; Hu, Su Man; Jeong, Yeonjoo; Kim, Jaewook; Lee, Suyoun; Kwak, Joon Young; Park, Jongkil; Hwang, Gyu Weon; Lee, Kyeong-Seok; Park, Seongsik; Lee, Wook-Seong; et al. (Nature Publishing Group, 2023)
Various memristive devices have been proposed for use in neuromorphic computing systems as artificial synapses. Analog synaptic devices with linear conductance updates during training are efficiently essential to train neural networks. Although many different analog memristors have been proposed, a more reliable approach to implement analog synaptic devices is needed. In this study, we propose the memristor of a Cu/SiOx/implanted a-SiGex/p(++) c-Si structure containing an a-Si layer with properly controlled conductance through Ge implantation. The a-SiGex layer plays a multifunctional role in device operation by limiting the current overshoot, confining the heat generated during operation and preventing the silicide formation reaction between the active metal (Cu) and the Si bottom electrode. Thus, the a-SiGex interface layer enables the formation of multi-weak filaments and induces analog switching behaviors. The TEM observation shows that the insertion of the a-SiGex layer between SiOx and c-Si remarkably suppresses the formation of copper silicide, and reliable set/reset operations are secured. The origin of the analog switching behaviors is discussed by analyzing current-voltage characteristics and electron microscopy images. Finally, the memristive-neural network simulations show that our developed memristive devices provide high learning accuracy and are promising in future neuromorphic computing hardware.