# Voltage-induced strain clocking of nanomagnets with perpendicular magnetic anisotropies

## TL;DR

This study models voltage-induced strain clocking in nanomagnetic logic with perpendicular anisotropies, revealing material-dependent efficiencies and switching behaviors, and demonstrating versatile clocking mechanisms for potential in-memory computing.

## Contribution

It introduces a comprehensive finite element simulation of strain-mediated Bennett clocking in different multiferroic nanomagnetic systems with perpendicular anisotropies, highlighting material-specific advantages and switching modes.

## Key findings

- Terfenol-D exhibits the highest energy efficiency, 100 times more than Ni and CoFeB.
- CoFeB has slower switching and lower bit-density due to dipole coupling.
- Precessional and Bennett clocking modes can be achieved with the same architecture using different voltages.

## 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 is slower and 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.

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Source: https://tomesphere.com/paper/1812.02268