Effect of Particle Size Distribution on Chain Structures in Magnetorheological Fluids

Sherman, Stephen G.; Wereley, Norman M.

doi:10.1109/tmag.2013.2245409

Cited by 42 publications

(23 citation statements)

References 9 publications

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“…17,18 Furthermore, magnetic fluid characteristics and structures differ under varying alternating magnetic field strengths, such that the fraction of agglomerates changes the magnetization and susceptibility of the ferrofluid. 19,20 In this work, we proposed a revised cluster-based model to more accurately estimate the SLP by considering magnetic nanoparticle aggregation. Under an alternating magnetic field, magnetic susceptibility is temperature dependent and can be conveniently described by the Langevin function.…”

Section: Introductionmentioning

confidence: 99%

Effective heating of magnetic nanoparticle aggregates for in vivo nano-theranostic hyperthermia

Wang¹,

Hsu²,

Li³

et al. 2017

IJN

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Magnetic resonance (MR) nano-theranostic hyperthermia uses magnetic nanoparticles to target and accumulate at the lesions and generate heat to kill lesion cells directly through hyperthermia or indirectly through thermal activation and control releasing of drugs. Preclinical and translational applications of MR nano-theranostic hyperthermia are currently limited by a few major theoretical difficulties and experimental challenges in in vivo conditions. For example, conventional models for estimating the heat generated and the optimal magnetic nanoparticle sizes for hyperthermia do not accurately reproduce reported in vivo experimental results. In this work, a revised cluster-based model was proposed to predict the specific loss power (SLP) by explicitly considering magnetic nanoparticle aggregation in in vivo conditions. By comparing with the reported experimental results of magnetite Fe3O4 and cobalt ferrite CoFe2O4 magnetic nanoparticles, it is shown that the revised cluster-based model provides a more accurate prediction of the experimental values than the conventional models that assume magnetic nanoparticles act as single units. It also provides a clear physical picture: the aggregation of magnetic nanoparticles increases the cluster magnetic anisotropy while reducing both the cluster domain magnetization and the average magnetic moment, which, in turn, shift the predicted SLP toward a smaller magnetic nanoparticle diameter with lower peak values. As a result, the heating efficiency and the SLP values are decreased. The improvement in the prediction accuracy in in vivo conditions is particularly pronounced when the magnetic nanoparticle diameter is in the range of ~10–20 nm. This happens to be an important size range for MR cancer nano-theranostics, as it exhibits the highest efficacy against both primary and metastatic tumors in vivo. Our studies show that a relatively 20%–25% smaller magnetic nanoparticle diameter should be chosen to reach the maximal heating efficiency in comparison with the optimal size predicted by previous models.

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Section: Introductionmentioning

confidence: 99%

Effective heating of magnetic nanoparticle aggregates for in vivo nano-theranostic hyperthermia

Wang¹,

Hsu²,

Li³

et al. 2017

IJN

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“…To the best of our knowledge, only two papers, the papers by Wang et al (1997) and Sherman and Wereley (2013) address this issue. A pioneering paper by Wang et al (1997) used 2D molecular dynamic simulation methods to demonstrate that the shear stress of ER fluids decreases with increasing the standard deviation of a Gaussian distribution of the particle size and then reaches a steady value at high polydispersity levels.…”

Section: Introductionmentioning

confidence: 99%

“…Thermal forces were not included in the simulations and only two Mason numbers were investigated. More recently, Sherman and Wereley (2013) carried out a large-scale (high particle count) simulation study on polydisperse MR fluids with lognormal distribution at a particle volume concentration of / ¼ 0:30. In their study, the mean particle diameter was fixed at 8 lm and the carrier fluid viscosity was 0.1 Pa s. They investigated the structure formation and shear rheology for a wide range in standard deviation of the distribution from 0.001 to 0.3.…”

Section: Introductionmentioning

confidence: 99%

Simulations of polydisperse magnetorheological fluids: A structural and kinetic investigation

Fernández-Toledano

Ruiz-López

Hidalgo‐Álvarez

et al. 2015

Journal of Rheology

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A simulation method is proposed to explore the effect of particle size polydispersity in magnetorheology including Brownian motion. The method aims to extend the classical particle-level simulation methodology developed by Klingenberg et al. [J. Chem. Phys. 91, 7888–7895 (1989)] for the case of polydisperse magnetorheological (MR) fluids. The simulation study concerns the aggregation kinetics at rest as well as the rheological behavior under start-up of steady shear and dynamic oscillatory shear tests at increasing strain amplitudes. Results demonstrate that the effect of polydispersity is only relevant at the transition regime between magnetostatic to hydrodynamic control of the suspension structure. The yielding behavior is correlated to the structural characteristics (radial distribution functions, pair correlation functions, and angular connectivities) of the MR fluids before the onset of flow. A more abrupt transition is observed for polydisperse MR fluids because interparticle links are weaker in this case if compared to monodisperse suspensions in spite of the fact that polydisperse MR fluids exhibit a larger connectivity.

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“…Generally, we believe that the hydrodynamic size distribution of magnetic nanoparticles follows lognormal distribution [31,32,33,34] f(d)=1d2πσexp[−12σ2(lndμ)2] here, d is the diameter of particles, μ is the median diameter of the lognormal distribution, σ is the standard deviation of lnd. Therefore, the lognormal distribution function is used to fit the hydrodynamic size distribution measured by DLS, and the results are shown in Table 1.…”

Section: Resultsmentioning

confidence: 99%

Characterization and Relaxation Properties of a Series of Monodispersed Magnetic Nanoparticles

Zhang

Cheng

Liu

2019

Sensors

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Magnetic iron oxide nanoparticles are relatively advanced nanomaterials, and are widely used in biology, physics and medicine, especially as contrast agents for magnetic resonance imaging. Characterization of the properties of magnetic nanoparticles plays an important role in the application of magnetic particles. As a contrast agent, the relaxation rate directly affects image enhancement. We characterized a series of monodispersed magnetic nanoparticles using different methods and measured their relaxation rates using a 0.47 T low-field Nuclear Magnetic Resonance instrument. Generally speaking, the properties of magnetic nanoparticles are closely related to their particle sizes; however, neither longitudinal relaxation rate r 1 nor transverse relaxation rate r 2 changes monotonously with the particle size d . Therefore, size can affect the magnetism of magnetic nanoparticles, but it is not the only factor. Then, we defined the relaxation rates r i ′ (i = 1 or 2) using the induced magnetization of magnetic nanoparticles, and found that the correlation relationship between r 1 ′ relaxation rate and r 1 relaxation rate is slightly worse, with a correlation coefficient of R 2 = 0.8939, while the correlation relationship between r 2 ′ relaxation rate and r 2 relaxation rate is very obvious, with a correlation coefficient of R 2 = 0.9983. The main reason is that r 2 relaxation rate is related to the magnetic field inhomogeneity, produced by magnetic nanoparticles; however r 1 relaxation rate is mainly a result of the direct interaction of hydrogen nucleus in water molecules and the metal ions in magnetic nanoparticles to shorten the T 1 relaxation time, so it is not directly related to magnetic field inhomogeneity.

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Effect of Particle Size Distribution on Chain Structures in Magnetorheological Fluids

Cited by 42 publications

References 9 publications

Effective heating of magnetic nanoparticle aggregates for in vivo nano-theranostic hyperthermia

Effective heating of magnetic nanoparticle aggregates for in vivo nano-theranostic hyperthermia

Simulations of polydisperse magnetorheological fluids: A structural and kinetic investigation

Characterization and Relaxation Properties of a Series of Monodispersed Magnetic Nanoparticles

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