GaN-based Room Temperature Spintronics for Next Generation Low Power Consumption Electronic Devices

V. Saravade, A. Ghods, Andrew Woode, Chuanle Zhou, I. Ferguson
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Abstract

There has been an exponential growth in the microelectronics industry over the last 70 years with a consistent miniaturization of transistors’ size and increase in the speed and on-chip transistors density with reasonable power consumption, as seen in Figure 1 [1] . This trend will saturate soon especially due to the unintended thermal noise that is dissipated, as the density of transistors on the chips increase and as the corresponding electronics approach their physical limits. There is a need to implement new processing and computing techniques [2] with more compact size, lower power consumption and enhanced performance. Neuromorphic computing mimics the parallel processing of the mammalian brain and the quantum decoherence within the neurons, and seems to be promising for future applications and needs high speed electronics [3] . Quantum computing could enhance the functionalities, storage capabilities, and data manipulation and transmission, for the next generation of devices. Spintronics is an enabling technology to meet the speed, power, and scalability requirements for quantum information and neuromorphic computing [4 , 5] . The non-volatile nature of spintronic memory could help to tackle power efficiency challenges of microelectronics. Spin of a material is directly related with magnetic, electrical, and optical properties. It is necessary to investigate materials and understand their properties to control and manipulate their spin and use for spintronic applications. However, most materials show conducive properties for spintronics at cryogenic temperatures, which limits their practical applications. There is a need to investigate spintronic materials for quantum applications at room temperature (RT).
下一代低功耗电子器件的氮化镓室温自旋电子学
在过去的70年里,微电子工业呈指数级增长,晶体管尺寸不断小型化,速度和片上晶体管密度不断提高,功耗合理,如图1[1]所示。随着芯片上晶体管密度的增加和相应的电子器件接近其物理极限,这种趋势很快就会饱和,特别是由于意想不到的热噪声被消散。有必要实现新的处理和计算技术[2],使其具有更紧凑的尺寸、更低的功耗和更高的性能。神经形态计算模拟了哺乳动物大脑的并行处理和神经元内的量子退相干,在未来的应用中似乎很有前景,并且需要高速电子器件[3]。量子计算可以增强下一代设备的功能、存储能力、数据操作和传输。自旋电子学是满足量子信息和神经形态计算对速度、功率和可扩展性要求的一种使能技术[4,5]。自旋电子存储器的非易失性可以帮助解决微电子的功率效率挑战。材料的自旋与磁性、电学和光学性质直接相关。为了控制和操纵材料的自旋并将其应用于自旋电子学,研究材料并了解其性质是必要的。然而,大多数材料在低温下表现出有利于自旋电子学的特性,这限制了它们的实际应用。有必要研究在室温下量子应用的自旋电子材料。
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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