Large-Scale Scientific Computing - 12th International Conference, LSSC 2019, Sozopol, Bulgaria, June 10-14, 2019, Revised Selected Papers
Large-Scale Scientific Computing - 12th International Conference, LSSC 2019, Sozopol, Bulgaria, June 10-14, 2019, Revised Selected Papers
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大规模科学计算 - 第 12 届国际会议，LSSC 2019，保加利亚索佐波尔，2019 年 6 月 10-14 日，修订后的精选论文
DOI：
10.1007/978-3-030-41032-2_49
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Sadi T
中科院分区：
文献类型：
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作者：
Sadi T
通过使用基于动力学蒙特卡罗方法的随机模拟模型，我们研究了基于氧化物的电阻式随机存取存储器（RRAM）器件的物理、操作和可靠性，所述氧化物包括富硅二氧化硅（SiO）和氧化铪- HfO-一种广泛使用的过渡金属氧化物。在过去的十年里，对RRAM技术的兴趣一直在稳步增长，因为它被广泛视为下一代非易失性存储器设备。模拟过程描述了自洽的电子电荷和热输运效应在三维（3D）空间中，允许导电丝负责开关的动态研究。我们专注于这些设备的可靠性的研究，特别是在系统中的氧气不足如何影响开关效率。
By using a stochastic simulation model based on the kinetic Monte Carlo approach, we study the physics, operation and reliability of resistive random-access memory (RRAM) devices based on oxides, including silicon-rich silica (SiO) and hafnium oxide – HfO– a widely used transition metal oxide. The interest in RRAM technology has been increasing steadily in the last ten years, as it is widely viewed as the next generation of non-volatile memory devices. The simulation procedure describes self-consistently electronic charge and thermal transport effects in the three-dimensional (3D) space, allowing the study of the dynamics of conductive filaments responsible for switching. We focus on the study of the reliability of these devices, by specifically looking into how oxygen deficiency in the system affects the switching efficiency.