The Development of Nanochannel Memristor Through Ag Ion Intercalation in h-BN/MoTe2 Heterostructures

Memristors based on 2D materials have attracted attention as next-generation memory devices due to their high data processing performance and low power consumption. Current research on memristor devices is actively progressing through the utilization of various 2D materials. In particular, h-BN with its excellent insulation and chemical stability, plays a crucial role in heterojunctions with other 2D materials. Combining it with TMD materials such as MoTe₂, WS₂, and MoS₂ can maximize the performance of memristor devices.<br/>In this study, we utilize hexagonal boron nitride (h-BN) and transition metal dichalcogenides (TMDs), which play a crucial role in enhancing the electrical properties of memristors. This study involves fabricating memristors with vertical structures by stacking TMD materials, such as MoTe₂, on h-BN flakes and analyzing their electrical properties through ion intrercalation processes. As we change e-beam lithography recipe, such as acceleration voltage and develop time, and reactive ion etching recipe with SF₆ gas to pattern the nanochannels improving the performance of memristors by controlling the width and depth of the nanochannels. Our results show that Ag ion intercalation through h-BN nanochannels maximizes the on/off ratio of memristors and induces stable phase transitions.<br/>As AI technology expands and the demand for high-performance memory devices increases, investments in memristor-based technology have grown, leading to the growth of memristor memory. The potential applications of TMD-based nanochannel memristors in next-generation neuromorphic devices have been identified, and they will contribute to groundbreaking technological advancements in the IT field. This research suggests the potential for developing neuromorphic artificial synaptic devices based on memristors, contributing to innovations in IT technologies. We expect it will significantly contribute to the practical application of memristor devices and play a key role in future artificial intelligence and neuromorphic computing systems.