Monitoring superparamagnetic Langevin behavior of individual SrRuO3nanostructures

Abstract

Patterned nanostructures on the order of 200 nm × 200 nm of the itinerant ferromagnet SrRuO3 give rise to superparamagnetic behavior below the Curie temperature (∼ 150 K) down to a sampledependent blocking temperature. We monitor the superparamagnetic fluctuations of an individual volume and demonstrate that the field dependence of the time-averaged magnetization is well described by the Langevin equation. On the other hand, the rate of the fluctuations suggests that the volume in which the magnetization fluctuates is smaller by more than an order of magnitude. We suggest that switching via nucleation followed by propagation gives rise to Langevin behavior of the total volume, whereas the switching rate is determined by a much smaller nucleation volume.PACS numbers: 75.60.Jk, The magnetization of ferromagnetic nanoparticles commonly exhibit thermally induced fluctuations known as a superparamagnetic behavior at a temperature interval below the Curie temperature. Superparamagnetism has been known for decades [1]; however, the interest in this fundamental phenomenon has increased in recent years in connection with a wider use of spintronic devices consisting of nanoscale magnetic components [2]. Although the best way to study superparamagnetism is by exploring the superparamagnetic behavior of an individual nanoparticle, so far due to technical challenges the study of superparamagnetism has been mainly performed with ensembles of magnetic nanoparticles where the fluctuations are not observed directly but inferred from the field and temperature dependence of the average magnetization of the ensemble [3][4][5][6][7][8].The magnetic fluctuations of an individual superparamagnetic nanoparticle are described in the framework of the Néel-Brown model [9][10][11]. In its simplest form, the model describes a thermally activated process of coherent rotation of a single magnetic domain particle with uniaxial magnetic anisotropy at a temperature T over an energy barrier E b , and it predicts an average waiting time for reversal τ given by τ = τ 0 e E b /kB T , where τ 0 is a sample specific constant linked to Larmor frequency with a typical value on the order of 10 −9 s [12]. The temperature below which the waiting time exceeds the relevant measuring time (commonly on the order of 100 s) is defined as the blocking temperature T b given by T b = 25K u V /k B , where K u , V , and k B are the anisotropy constant, the volume of the sample, and Boltzmann constant, respectively.The field dependence of the average magnetization − → M is described by the Langevin equation, where µ 0 − → H is the magnetic field. The application of the Langevin equation to describe the magnetization curves of ensembles of nanoparticles is not straightforward due to variations in the volume and shape of the nanoparticles. Therefore, any fit requires making assumptions regarding the volume distribution [13]. On the other hand, in the few reports where superparamagnetic fluctuations of individual superparamagnetic nanoparticles were monitored [14][15][1...

Broadband Spectroscopy of Thermodynamic Magnetization Fluctuations through a Ferromagnetic Spin-Reorientation Transition

“…Spontaneous magnetization fluctuations can occur in ferromagnetic materials, even in thermal equilibrium, particularly when the magnetic anisotropy energy becomes comparable to or less than the available thermal energy [1][2][3][4][5][6][7]. These intrinsic thermodynamic fluctuations encode valuable information about the magnetization dynamics of the system itself, because their frequency spectrum S(ν) is intimately and necessarily related to the dissipative (imaginary) part of the magnetic susceptibility χ (ν), in accord with the fluctuation-dissipation theorem [2,8] (namely, χ (ν) ∼ ν k B T S(ν), where k B T is the thermal energy).…”

Zero-dimensionality of a scaled-down VO2 metal-insulator transition via high-resolution electrostatic gating

“…During phase transitions, spatially heterogeneous domain structures are formed that affect material properties 6,7 . However, when phase transition materials are miniaturized to smaller than the size of individual domains, the phase transition becomes single-domain and exhibits different behavior [8][9][10][11][12][13] . Therefore, when designing functional devices using phase transition materials, it is essential to understand the effects of miniaturization.…”

“…

An understanding of the phase transitions at the nanoscale is essential in state-of-the-art engineering [1][2][3][4][5] , instead of simply averaging the heterogeneous domains formed during phase transitions 6,7 . However, as materials are scaled down, the steepness of the phase transition rapidly increases [8][9][10][11][12][13] and requires extremely high precision in the control method. Here, a three-terminal device, which could precisely control the phase transition electrically [14][15][16][17][18][19] , was applied for the first time to a scaled-down metal-insulator transition material VO 2 .

…”

Physical Properties of Semiconducting/Magnetic Nanocomposites

“…The adjustability in their size, shape, and mutual arrangement is examined especially concerning the magnetic properties. Single domain (Goya et al, 2003) and superparamagnetic (Sinwani et al, 2014) particles are crucial in many realms. Their incorporation in a matrix material to determine the magnetic properties or for stabilization is also widespread.…”