In next-generation neuromorphic computing applications, the primary challenge lies in achieving energy-efficient and reliable memristors while minimizing their energy consumption to a level comparable to that of biological synapses. In this work, hexagonal boron nitride (h-BN)-based metal-insulator-semiconductor (MIS) memristors operating is presented at the attojoule-level tailored for high-performance artificial neural networks. The memristors benefit from a wafer-scale uniform h-BN resistive switching medium grown directly on a highly doped Si wafer using metal–organic chemical vapor deposition (MOCVD), resulting in outstanding reliability and low variability. Notably, the h-BN-based memristors exhibit exceptionally low energy consumption of attojoule levels, coupled with fast switching speed. The switching mechanisms are systematically substantiated by electrical and nano-structural analysis, confirming that the h-BN layer facilitates the resistive switching with extremely low high resistance states (HRS) and the native SiO_x on Si contributes to suppressing excessive current, enabling attojoule-level energy consumption. Furthermore, the formation of atomic-scale conductive filaments leads to remarkably fast response times within the nanosecond range, and allows for the attainment of multi-resistance states, making these memristors well-suited for next-generation neuromorphic applications. The h-BN-based MIS memristors hold the potential to revolutionize energy consumption limitations in neuromorphic devices, bridging the gap between artificial and biological synapses.

中文翻译：

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用于高性能神经形态计算的阿托焦六方氮化硼忆阻器


在下一代神经形态计算应用中，主要挑战在于实现高效且可靠的忆阻器，同时将其能耗降至与生物突触相当的水平。在这项工作中，基于六方氮化硼（h-BN）的金属绝缘体半导体（MIS）忆阻器在阿焦耳级工作，专为高性能人工神经网络而设计。忆阻器受益于使用金属有机化学气相沉积 (MOCVD) 在高掺杂硅晶圆上直接生长的晶圆级均匀 h-BN 电阻开关介质，从而具有出色的可靠性和低变异性。值得注意的是，基于 h-BN 的忆阻器表现出阿焦耳级的极低能耗，以及快速的开关速度。通过电学和纳米结构分析系统地证实了开关机制，证实 h-BN 层促进了极低高阻态 (HRS) 的电阻开关，而 Si 上的原生 SiO _x 有助于抑制电流过大，导致焦耳级能量消耗。此外，原子级导电丝的形成导致纳秒范围内的显着快速响应时间，并允许实现多电阻状态，使这些忆阻器非常适合下一代神经形态应用。基于 h-BN 的 MIS 忆阻器有可能彻底改变神经形态设备的能耗限制，缩小人工突触和生物突触之间的差距。