论文标题
硅亚氧化物RRAM中的纳米级可塑性和神经形态动力学
Nanoscale plasticity and neuromorphic dynamics in silicon suboxide RRAM
论文作者
论文摘要
电阻随机记忆,也称为候选人,其电阻可以通过绝缘体内的电动驱动形成和导电细丝的破坏来调节,这是有望的候选神经形态应用的候选者,因为它们的可伸缩性,低功能操作和多样的功能行为。但是,由于相对于单个细丝的纳米尺度,理解各个丝和周围材料的动力学和周围材料的动力学是具有挑战性的。在目前的工作中,用于研究完全与CMOS兼容的硅亚氧化薄膜中纳米级电导率的演化。报道了不同的丝状可塑性和背景电导率提高,这表明可以通过复合芯(丝)和壳(背景电导率)动力学来最好地描述装置行为。此外,恒定电流测量结果表明了细丝形成与破裂之间的相互作用,从而导致纳米级区域的电流控制的电压尖峰,估计每个峰值的最佳能源消耗为25个attojoules。对于极低的功率神经形态计算,这是非常有希望的,并表明在较大设备中观察到的动态行为应持续并改善,并随着尺寸的缩小缩小。
Resistive random-access memories, also known as memristors, whose resistance can be modulated by the electrically driven formation and disruption of conductive filaments within an insulator, are promising candidates for neuromorphic applications due to their scalability, low-power operation and diverse functional behaviours. However, understanding the dynamics of individual filaments, and the surrounding material, is challenging, owing to the typically very large cross-sectional areas of test devices relative to the nanometre scale of individual filaments. In the present work, conductive atomic force microscopy is used to study the evolution of conductivity at the nanoscale in a fully CMOS-compatible silicon suboxide thin film. Distinct filamentary plasticity and background conductivity enhancement are reported, suggesting that device behaviour might be best described by composite core (filament) and shell (background conductivity) dynamics. Furthermore, constant current measurements demonstrate an interplay between filament formation and rupture, resulting in current-controlled voltage spiking in nanoscale regions, with an estimated optimal energy consumption of 25 attojoules per spike. This is very promising for extremely low-power neuromorphic computation and suggests that the dynamic behaviour observed in larger devices should persist and improve as dimensions are scaled down.