Viscous effects on nanoparticle magnetization harmonics

Rauwerdink, Adam M.; Weaver, John B.

doi:10.1016/j.jmmm.2009.10.024

Cited by 102 publications

(89 citation statements)

References 27 publications

(37 reference statements)

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“…Dynamic effects such as changes in viscosity or molecular binding have also been shown to influence a ratio of harmonics using a technique termed magnetic spectroscopy of nanoparticle Brownian motion ͑MSB͒. 18,19 Here we present harmonic phase angle as a means of pulling further information from the nanoparticle's harmonic spectrum. We focus on viscous effects and the impact of excitation parameters such as frequency and amplitude.…”

Section: 2mentioning

confidence: 99%

Harmonic phase angle as a concentration‐independent measure of nanoparticle dynamics

Rauwerdink

Weaver

2010

Medical Physics

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Purpose:The harmonic spectrum of magnetic nanoparticles contains valuable information about the quantity and environment of the particles. Harmonic amplitudes have been used to produce quantitative images and ratios of these amplitudes have been used to monitor changes in the particle environment. Harmonic phase angles have not yet been utilized in these pursuits. The authors explore harmonic phase angle as a concentration-independent means of remotely monitoring the dynamic magnetization of nanoparticles. Methods: A magnetic nanoparticle spectrometer was used to explore the impacts of viscosity and excitation frequency and amplitude on the phase angle of magnetization harmonics. A dynamic model, which accounts for particle relaxation times, was used to model some results. Results: Harmonic phase angle can undergo large changes when a nanoparticle's Brownian motion is altered. Excitation parameters and particle characteristics have a profound effect on the extent of these changes. Conclusions: Phase angle can allow for monitoring of various impacts on a nanoparticle's Brownian motion. When combined with other concentration-independent metrics, such as ratios of harmonic amplitudes, valuable information about the particle's environment can be gathered.

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Section: 2mentioning

confidence: 99%

Harmonic phase angle as a concentration‐independent measure of nanoparticle dynamics

Rauwerdink

Weaver

2010

Medical Physics

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“…In many magnetic nanoparticle (MNP) applications like biosensing, [1][2][3][4][5][6][7] hyperthermia, 8,9 and magnetic particle imaging, [10][11][12][13] nanoparticles are driven to rotate by oscillating magnetic fields.…”

Section: Describing Driven Nanoparticle Rotationsmentioning

confidence: 99%

“…Since many applications use a single oscillating field (see, for example, magnetic particle imaging 11 or magnetic nanoparticle spectroscopy [4][5][6] ), we choose n ! nðtÞẑ and simplify the FPE to only depend on the polar angle and time W(h, t).…”

Section: The Fokker-planck Equation For Brownian Nanoparticle Rotmentioning

confidence: 99%

Comparisons of characteristic timescales and approximate models for Brownian magnetic nanoparticle rotations

Reeves

Weaver

2015

Journal of Applied Physics

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Magnetic nanoparticles are promising tools for a host of therapeutic and diagnostic medical applications. The dynamics of rotating magnetic nanoparticles in applied magnetic fields depend strongly on the type and strength of the field applied. There are two possible rotation mechanisms and the decision for the dominant mechanism is often made by comparing the equilibrium relaxation times. This is a problem when particles are driven with high-amplitude fields because they are not necessarily at equilibrium at all. Instead, it is more appropriate to consider the "characteristic timescales" that arise in various applied fields. Approximate forms for the characteristic time of Brownian particle rotations do exist and we show agreement between several analytical and phenomenological-fit models to simulated data from a stochastic Langevin equation approach. We also compare several approximate models with solutions of the Fokker-Planck equation to determine their range of validity for general fields and relaxation times. The effective field model is an excellent approximation, while the linear response solution is only useful for very low fields and frequencies for realistic Brownian particle rotations. V C 2015 AIP Publishing LLC.[http://dx.doi.org/10.1063/1.4922858] I. DESCRIBING DRIVEN NANOPARTICLE ROTATIONSIn many magnetic nanoparticle (MNP) applications like biosensing, 1-7 hyperthermia, 8,9 and magnetic particle imaging, 10-13 nanoparticles are driven to rotate by oscillating magnetic fields.14 Understanding the resulting magnetic particle dynamics is important to advance these applications. A typical way to discuss the dynamics is through the timescales of the nanoparticle rotations. [15][16][17] In particular, we often consider the relaxation time: the timescale for a sample of particles to return to equilibrium after some perturbation (e.g., alignment with a field). Conventional magnetic particles are understood to have two rotational mechanisms. The entire particle can rotate as a rigid body by Brownian rotations, 18 and the particle's magnetic moment can also rotate internally due to restructuring of electronic states in N eel rotation. 19,20 The equilibrium relaxation time is different for each mechanism and depends on many parameters. 21,22 However, because most applications involve magnetically excited particles, it is more important to examine non-equilibrium timescales determining the speed of movements in varying driving fields-these timescales can be very different from the relaxation time. One only needs to imagine that in a stronger field, the particles will align faster to see why this is true. We will hence refer to those non-equilibrium timescales as the "characteristic times" of the rotations.In reality, the possibility for N eel rotations complicates the matter and it is important to understand which mechanism is dominant for chosen nanoparticles. 23,24 This is an open problem because these processes will in general not be decoupled. If the processes did truly happen independently (in parallel)...

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“…This is an important result because magnetization harmonics are used exclusively in practical imaging and sensing. 20,21 FIG. 2.…”

Section: Model Benchmarkingmentioning

confidence: 99%

Simulations of magnetic nanoparticle Brownian motion

Reeves

Weaver²

2012

Journal of Applied Physics

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Magnetic nanoparticles are useful in many medical applications because they interact with biology on a cellular level thus allowing microenvironmental investigation. An enhanced understanding of the dynamics of magnetic particles may lead to advances in imaging directly in magnetic particle imaging or through enhanced MRI contrast and is essential for nanoparticle sensing as in magnetic spectroscopy of Brownian motion. Moreover, therapeutic techniques like hyperthermia require information about particle dynamics for effective, safe, and reliable use in the clinic. To that end, we have developed and validated a stochastic dynamical model of rotating Brownian nanoparticles from a Langevin equation approach. With no field, the relaxation time toward equilibrium matches Einstein's model of Brownian motion. In a static field, the equilibrium magnetization agrees with the Langevin function. For high frequency or low amplitude driving fields, behavior characteristic of the linearized Debye approximation is reproduced. In a higher field regime where magnetic saturation occurs, the magnetization and its harmonics compare well with the effective field model. On another level, the model has been benchmarked against experimental results, successfully demonstrating that harmonics of the magnetization carry enough information to infer environmental parameters like viscosity and temperature. V C 2012 American Institute of Physics.

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Viscous effects on nanoparticle magnetization harmonics

Cited by 102 publications

References 27 publications

Harmonic phase angle as a concentration‐independent measure of nanoparticle dynamics

Harmonic phase angle as a concentration‐independent measure of nanoparticle dynamics

Comparisons of characteristic timescales and approximate models for Brownian magnetic nanoparticle rotations

Simulations of magnetic nanoparticle Brownian motion

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