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探索具有共存磁阻和忆阻特性的氧化镁基磁性隧道结的多功能性

Exploring Multifunctionality in MgO-Based Magnetic Tunnel Junctions with Coexisting Magnetoresistance and Memristive Properties

Alejandro Schulman, Elvira Paz, Tim Böhnert, Alex Steven Jenkins, Ricardo Ferreira

arXiv 2607.20040首次发表:更新:

AI 中文总结

研究探索氧化镁基磁性隧道结的多功能性,证明其磁阻与忆阻特性共存,线性磁阻无滞后,有非易失性忆阻行为,掺杂降低忆阻功耗,忆阻开关可调控自旋电子功能,为相关电路整合应用铺路。

AI 中文摘要

磁隧道结(MTJs)和忆阻器是两种关键的新兴纳米技术,在数字革命前沿的潜在应用中备受关注。将这些现象整合到单个多功能器件中是利用忆阻系统的可重新编程性与MTJs的高产量和多样功能的重要一步。本研究证明了基于氧化镁的MTJs上磁阻和忆阻特性的共存。这些器件显示出作为磁场函数的线性响应且无滞后的磁阻,满足良好磁场传感器的要求,并展示了作为施加电场函数直至纳秒脉冲的非易失性和准模拟忆阻行为。此外,通过掺杂氧化物势垒,忆阻功耗降低了20%,赋予器件多功能性有前景的可扩展性潜力。研究还表明,忆阻开关可用于可逆地完全抑制和恢复自旋电子功能。这些结果可为忆阻器和自旋电子器件在复杂可重新编程电路中的无缝整合铺平道路,以应对如可重新编程多功能场传感器阵列和神经形态计算等应用。

英文摘要

Magnetic tunnel junctions (MTJs) and memristors are two key emerging nanotechnologies that attracted significant interest for potential applications at the forefront of the digital revolution, including sensing, data storage, and non-conventional computation. The co-integration of these phenomena into a single multifunctional device is an important step toward harnessing the re-programmability of memristive systems with the high yield and varied functionality of MTJs. This study demonstrates the co-existence of magnetoresistance and memristive properties on MgO-based MTJs. These devices show a magnetoresistance with a linear response as a function of a magnetic field and no hysteresis, which are the requirements for good magnetic field sensors, as well as demonstrating a non-volatile and quasi-analogue memristive behavior as a function of an applied electrical field down to nanosecond pulses. Furthermore, by doping the oxide barrier, the memristive power consumption is lowered by 20% giving the multi-functionality of the devices a promising scalability potential. This study also shows that, memristive switching can be reversibly used to completely suppress and recover the spintronic functionalities. These results can pave the way for a seamless co-integration of memristors and spintronic devices in complex reprogrammable circuits addressing applications such as reprogrammable multifunctional field sensor arrays and neuromorphic computing.

Comments9 pages, 5 figures adn 1 table. Published version of record. Published in Advanced Functional Materials 33 (2023), 2305238

Journal refAdv. Funct. Mater. 2023, 33, 2305238

DOI:10.1002/adfm.202305238

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