Correlation between tunneling magnetoresistance and magnetization in dipolar-coupled nanoparticle arrays

Abstract

The tunneling magnetoresistance (TMR) of a hexagonal array of dipolar coupled anisotropic magnetic nanoparticles is studied using a resistor network model and a realistic micromagnetic configuration obtained by Monte Carlo simulations. Analysis of the field-dependent TMR and the corresponding magnetization curve shows that dipolar interactions suppress the maximum TMR effect, increase or decrease the field-sensitivity depending on the direction of applied field and introduce strong dependence of the TMR on the direction of the applied magnetic field. For off-plane magnetic fields, maximum values in the TMR signal are associated with the critical field for irreversible rotation of the magnetization. This behavior is more pronounced in strongly interacting systems (magnetically soft), while for weakly interacting systems (magnetically hard) the maximum of TMR ( ) occurs below the coercive field ( ), in contrast to the situation for non-interacting nanoparticles () or in-plane fields. The relation of our simulations to recent TMR measurements in self-assembled Co nanoparticle arrays is discussed.

The roles of the exchange and dipole couplings on the magnetoresistance for the nanoparticle arrays

“…Finally, the magnetoresistance of the sample is defined by MRðHÞ ¼ ðRðHÞ À R S Þ=R S ¼ ðs S À sðHÞÞ=s ðHÞ [2], where R S and s S denote the saturation values of the resistivity and conductivity, respectively. figures, it is also found that the maximum TMR effects occur also at the coercive field H c .…”

“…In order to calculate the net resistance of the system, we converted the two dimensional microstructure into a network resistors by connecting each pair of adjacent units by a resistor. Based on the resistor network model employed to study the TMR, it is found that the unknown potentials {F i } can be obtained by solving the set of linear equations in P ij s ij ðF i À F j Þ ¼ 0 with the boundary conditions [2], here {F i } denotes the electric potential at a node associated with the unit i and s ij is the conductivity between two particles i and j. In addition, the whole result depends closely on the magnetic configuration hm i i, which is used as input to obtain the inter-particle conductivities.…”

“…In addition, the whole result depends closely on the magnetic configuration hm i i, which is used as input to obtain the inter-particle conductivities. The magnetic configuration of the nanoparticle ensemble under an applied field H and finite temperature T was obtained by the standard Metroplis algorithm [2][3][4]. Then the sample conductivity can be calculated from s ¼ 1=2F 2…”

“…Correlation between tunneling magnetoresistance and magnetization dynamic behavior has become a central issue for the magnetic nanoparticle arrays. Recently, resistor network (RN) models have been used to simulate the magnetoresistance for granular films and self-assembled nanoparticle arrays [2]. For no exchange-coupled nanoparticle arrays, analysis of the field-dependent TMR and the corresponding magnetization curve shows that dipolar interactions suppress the maximum TMR effect.…”

“…Tunneling of spin-polarized electrons and magnetoresistance in complex phase systems, such as granular films, self-assembled nanoparticle arrays, magnetic semiconductors, are of great current interests due to the potential application of these materials in advancing the magnetic storage density and basic scientific interest [1][2][3]. Correlation between tunneling magnetoresistance and magnetization dynamic behavior has become a central issue for the magnetic nanoparticle arrays.…”