• 文献标题:   Graphene-Based STT-RAM Cell With Improved Switching for Scaled Technology Nodes
  • 文献类型:   Article
  • 作  者:   VARGHANI A, PEIRAVI A, MORADI F
  • 作者关键词:   graphenebased spin filter, micromagnetic simulation, spintransfer torque randomaccess memory sttram
  • 出版物名称:   IEEE TRANSACTIONS ON MAGNETICS
  • ISSN:   0018-9464 EI 1941-0069
  • 通讯作者地址:   Aarhus Univ
  • 被引频次:   1
  • DOI:   10.1109/TMAG.2015.2473135
  • 出版年:   2016

▎ 摘  要

Spin-transfer torque random-access memory (STT-RAM) is a nonvolatile, scalable, and fast memory structure, which benefits from high endurance and relatively low power consumption. However, there are some challenges in designing STT-RAM such as the tradeoff between decreasing the write current and the retention time. Increasing the write voltage as the cell size is scaled down is another challenge for STT-RAM due to the increasing resistance of its magnetic tunnel junction (MTJ). In this paper, a novel STT-RAM cell structure with a graphene-based spin filter including three graphene layers as MTJ is proposed for sub-20 nm technology nodes (e. g., 14 nm and beyond). By flowing a small (e. g., 3 mu A) and short width current pulse (e. g., 1 ns) through the center graphene layer, a reduction of 69% in the amplitude of the intrinsic switching current density (38% less than the predicted value for the conventional in-plane STT-RAM) is achieved without any penalty of data retention time for an 8 nm technology node. Furthermore, by flowing current through the center graphene layer, the intrinsic switching voltage of the proposed structure is decreased by 27%, 51%, and 59% for 14, 10, and 8 nm widths of the MTJ, respectively. The behavior of the proposed structure in a fast (precessional) switching mode (switching time less than 3 ns) is evaluated. Consequently, a reduction of 38% in the switching current density and the switching voltage can be attained for the 8 nm technology node, using the proposed idea. Simulation results are obtained using an object-oriented micromagnetic framework.