Enhanced Reliability and Controllability in Filamentary Oxide‐Based 3D Vertical Structured Resistive Memory with Pulse Scheme Algorithm for Versatile Neuromorphic Applications

IF 18.5 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Hyesung Na, Sungjun Kim
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引用次数: 0

Abstract

This study explores the application of the incremental step pulse with verify algorithm (ISPVA) scheme in Pt/TiOX/TiN vertical resistive random‐access memory (VRRAM) devices to enhance both the reliability and controllability of resistive switching. ISPVA improves the linearity and symmetry of resistive switching, enabling accurate representation of up to 6‐bit states and ensuring precise transitions between low and high resistance states. Additionally, ISPVA ensures consistent current states across different layers, thereby improving electrical response uniformity and enhancing the performance of multilayer structures for high‐density applications. These improvements provide a stable memory window and guarantee the device's endurance for up to 1000 cycles. This study further demonstrates the implementation of various synaptic memory functions, including spike‐time‐dependent plasticity (STDP), spike‐number‐dependent plasticity (SNDP), spike‐amplitude‐dependent plasticity (SADP), spike‐duration‐dependent plasticity (SDDP), and spike‐rate‐dependent plasticity (SRDP). The findings also demonstrate that nociceptive and Pavlovian characteristics can be achieved for on‐receptor computing and associative learning. By integrating ISPVA and advanced fabrication techniques, VRRAM devices can effectively address challenges such as device‐to‐device variability and stochastic properties, thereby establishing a new benchmark for next‐generation computing and memory technologies.
基于脉冲方案算法的多用途神经形态应用中基于氧化丝的三维垂直结构电阻存储器的增强可靠性和可控性
本研究探讨了增量阶跃脉冲验证算法(ISPVA)方案在Pt/TiOX/TiN垂直电阻随机存取存储器(VRRAM)器件中的应用,以提高电阻开关的可靠性和可控性。ISPVA提高了电阻开关的线性度和对称性,能够精确表示高达6位的状态,并确保在低电阻状态和高电阻状态之间精确转换。此外,ISPVA确保在不同层之间保持一致的电流状态,从而改善电响应均匀性并增强高密度应用中多层结构的性能。这些改进提供了一个稳定的内存窗口,并保证设备的续航时间长达1000个周期。本研究进一步证明了各种突触记忆功能的实现,包括spike - time - dependent plasticity (STDP)、spike - number - dependent plasticity (SNDP)、spike - amplitude - dependent plasticity (SADP)、spike - duration - dependent plasticity (SDDP)和spike - rate - dependent plasticity (SRDP)。研究结果还表明,伤害性和巴甫洛夫特征可以在受体计算和联想学习中实现。通过集成ISPVA和先进的制造技术,VRRAM器件可以有效地解决器件间可变性和随机特性等挑战,从而为下一代计算和存储技术建立新的基准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Advanced Functional Materials
Advanced Functional Materials 工程技术-材料科学:综合
CiteScore
29.50
自引率
4.20%
发文量
2086
审稿时长
2.1 months
期刊介绍: Firmly established as a top-tier materials science journal, Advanced Functional Materials reports breakthrough research in all aspects of materials science, including nanotechnology, chemistry, physics, and biology every week. Advanced Functional Materials is known for its rapid and fair peer review, quality content, and high impact, making it the first choice of the international materials science community.
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