Voltage-induced strain clocking of nanomagnets with perpendicular magnetic anisotropies

Abstract

Nanomagnetic logic (NML) has attracted attention during the last two decades due to its promise of high energy efficiency combined with non-volatility. Data transmission in NML relies on Bennett clocking through dipole interaction between neighboring nanomagnetic bits. This paper uses a fully coupled finite element model to simulate Bennett clocking based on strain-mediated multiferroic system for Ni, CoFeB and Terfenol-D with perpendicular magnetic anisotropies. Simulation results demonstrate that Terfenol-D system has the highest energy efficiency, which is 2 orders of magnitude more efficient than Ni and CoFeB. However, the high efficiency is associated with switching incoherency due to its large magnetostriction coefficient. It is also suggested that the CoFeB clocking system has lower bit-density than in Ni or Terfenol-D systems due to its large dipole coupling. Moreover, we demonstrate that the precessional perpendicular switching and the Bennett clocking can be achieved using the same strain-mediated multiferroic architecture with different voltage pulsing. This study opens new possibilities to an all-spin in-memory computing system.

Proposal of Global Strain Clocking Scheme for Majority Logic Gate

“…Therefore, we should choose the nanomagnet as thin as possible. However, the magnetization is prone to deviate from the in-plane due to the perpendicular magnetic anisotropy when the thickness is too small [41]. Therefore, the authors selected the nanomagnet is 120nm length, 9-15nm thickness, and 60-90nm width.…”

Voltage-Controlled Energy-Efficient Domain Wall Synapses With Stochastic Distribution of Quantized Weights in the Presence of Thermal Noise and Edge Roughness

“…To implement these devices, domain walls (DWs) are translated to different positions by externally applied magnetic field [12], an electric current that causes Spin-Orbit Torque (SOT) [13][14][15], Spin Transfer Torque (STT) [16][17][18] or a strain gradient [19][20]. Strain control of magnetization consumes ultra-low energy [21][22][23][24][25][26][27]. Hence, manipulation of DWs with strain can be utilized to implement energy efficient neuromorphic devices.…”