Dynamic response of exchange bias in graphene nanoribbons

TL;DR

This study investigates how the exchange bias in graphene nanoribbons responds dynamically to different magnetic field sweep rates, revealing a rate-dependent training effect and power law behavior of the bias field.

Contribution

It provides new experimental insights into the dynamic magnetic behavior of GNRs, especially regarding the influence of field sweep rate on exchange bias and training effects.

Findings

Pronounced training effect at low sweep rates

Exchange bias increases with sweep rate following a power law

Response linked to relaxation times of spins in GNRs

Abstract

The dynamics of magnetic hysteresis, including the training effect and the field sweep rate dependence of the exchange bias, is experimentally investigated in exchange-coupled potassium split graphene nanoribbons (GNRs). We find that, at low field sweep rate, the pronounced absolute training effect is present over a large number of cycles. This is reflected in a gradual decrease of the exchange bias with the sequential field cycling. However, at high field sweep rate above 0.5 T/min, the training effect is not prominent. With the increase in field sweep rate, the average value of exchange bias field grows and is found to follow power law behavior. The response of the exchange bias field to the field sweep rate variation is linked to the difference in the time it takes to perform a hysteresis loop measurement compared with the relaxation time of the anti-ferromagnetically aligned spins. The present results may broaden our current understanding of magnetism of GNRs and would be helpful in establishing the GNRs based spintronic devices.