Magnetic nanoparticles are critical to a broad range of applications, from medical diagnostics and therapeutics to biotechnological processes and single molecule manipulation. To advance these applications, facile and robust routes to synthesize highly magnetic nanoparticles over a wide size range are needed. Here, we demonstrate that changing the degassing temperature of thermal decomposition of metal acetylacetonate precursors from 90 to 25°C tunes the size of ferrimagnetic Zn x Fe 3-x O 4 nanocubes from 25 to 100 nm, respectively. We show that degassing at 90°C nearly entirely removes acetylacetone ligands from the reaction, which results in an early formation of monomers and a reaction-controlled growth following LaMer's model towards small nanocubes. In contrast, degassing at 25°C only partially dissociates acetylacetone ligands from the metal center and triggers a delayed formation of monomers, which leads to intermediate assembled structures made of tiny irregular crystallites and an eventual formation of large nanocubes via a diffusion-controlled growth mechanism. Using complementary techniques, we determine the substitution fraction x of Zn 2+ to be in the range of 0.35-0.37. Our method reduces the complexity of the thermal decomposition method by narrowing the synthesis parameter space to a single physical parameter and enables fabrication of highly magnetic and uniform zinc ferrite nanocubes over a broad size range. The resulting particles are promising for a range of applications, from magnetic fluid hyperthermia to actuation of macromolecules. File list (2) download file view on ChemRxiv Lak et al. Manuscript.pdf (4.40 MiB) download file view on ChemRxiv Lak et al. Supporting Information.pdf (1.77 MiB)
We investigated the effect of core size distribution on the performance of a magnetic nanoparticle thermometer (MNPT) in circumstances when Néel relaxation dominates the dynamic behavior of particles. Numerical simulations revealed the effects of excitation field strength and core size distribution on the temperature dependence of the amplitude and phase of harmonics. In MNPT, the field dependences of sensitivity deviated significantly from those calculated when the core size distribution was neglected. These simulation results were compared with those from experiments for which reasonable agreement was obtained. These findings must be carefully considered when designing an optimal MNPT system.
The magnetic moment of magnetic nanoparticles (MNPs) is one of the key parameters for various applications. We have experimentally studied the effective magnetic moment of multi-core MNPs and especially their dependence on the applied magnetic field. In contrast to single-core MNPs, the situation is considerably more complex since the effective magnetic moment depends on the size of individual crystallites, their packing density, core configuration, and, thus, the interaction between them. Different approaches to determine the effective magnetic moment are applied for two multi-core MNP systems (FeraSpin XL and BNF Starch). The effective magnetic moment at low magnetic fields is obtained from the ac susceptibility spectra measured at ac field amplitudes up to 9 mT. The obtained values are compared with the high-field values measured at 7 T. In the small-field range (up to 9 mT), a linear field dependence of the effective magnetic moment is found for FeraSpin XL while the value of BNF Starch was found to be nearly constant. The low-field values of both MNP systems are smaller than the values at larger fields, proving the magnetic field dependence of the effective magnetic moment of multi-core MNPs. The estimated values are discussed within a simple model. A consistent picture was found for BNF Starch while the model fails for FeraSpin XL. The different behaviors of both studied multi-core MNP systems are related to the magnetic interactions between the individual crystallites inside a multi-core structure, which are strong for FeraSpin XL due to the high packing density of the crystallites.
We estimated the effective magnetic anisotropy constant K of magnetic nanoparticles (MNPs) from the temperature dependence of the coercive field Hc of the M–H curve for use in biosensing applications. For this purpose, a previous analytical expression for Hc was extended so that it can be applied to nanoparticles with a size distribution. Using the extended expression for Hc, we estimated the K value of multi-core based MNP sample that consists of crystalline aggregates of elementary particles. We prepared three MNP samples. One is Resovist, in which elementary particles and aggregates are mixed. The Resovist sample was magnetically divided into two fractions called MS1 and MS3, which included mainly aggregates and elementary particles, respectively. We discuss the K value of elementary particles and aggregates from the comparison among the three samples. It is suggested that the K value of the aggregates is much smaller than that of the elementary particles. The temperature dependence of K of the aggregates is also discussed.
The small-angle neutron scattering data of nanostructured magnetic samples contain information regarding their chemical and magnetic properties. Often, the first step to access characteristic magnetic and structural length scales is a model-free investigation. However, due to measurement uncertainties and a restricted q range, a direct Fourier transform usually fails and results in ambiguous distributions. To circumvent these problems, different methods have been introduced to derive regularized, more stable correlation functions, with the indirect Fourier transform being the most prominent approach. Here, the indirect Fourier transform is compared with the singular value decomposition and an iterative algorithm. These approaches are used to determine the correlation function from magnetic small-angle neutron scattering data of a powder sample of iron oxide nanoparticles; it is shown that with all three methods, in principle, the same correlation function can be derived. Each method has certain advantages and disadvantages, and thus the recommendation is to combine these three approaches to obtain robust results.
Magnetic nanoparticles are critical to a broad range of applications, from medical diagnostics and therapeutics to biotechnological processes and single molecule manipulation. To advance these applications, facile and robust routes to synthesize highly magnetic nanoparticles over a wide size range are needed. Here, we demonstrate that changing the degassing temperature of thermal decomposition of metal acetylacetonate precursors from 90 to 25°C tunes the size of ferrimagnetic Zn<sub>x</sub>Fe<sub>3-x</sub>O<sub>4</sub> nanocubes from 25 to 100 nm, respectively. We show that degassing at 90°C nearly entirely removes acetylacetone ligands from the reaction, which results in an early formation of monomers and a reaction-controlled growth following LaMer's model towards small nanocubes. In contrast, degassing at 25°C only partially dissociates acetylacetone ligands from the metal center and triggers a delayed formation of monomers, which leads to intermediate assembled structures made of tiny irregular crystallites and an eventual formation of large nanocubes via a diffusion-controlled growth mechanism. Using complementary techniques, we determine the substitution fraction x of Zn<sup>2+</sup> to be in the range of 0.35-0.37. Our method reduces the complexity of the thermal decomposition method by narrowing the synthesis parameter space to a single physical parameter and enables fabrication of highly magnetic and uniform zinc ferrite nanocubes over a broad size range. The resulting particles are promising for a range of applications, from magnetic fluid hyperthermia to actuation of macromolecules.
Nonlinear handheld detection of magnetic nanoparticles is used to assess the lymph node status of cancer patients. Joint sensitivity and resolving power of nonlinear handheld detection can be maximized by optimizing the frequency of the excitation field, which is strongly influenced by Brownian and Néel relaxation. The characteristic frequency of magnetic nanoparticles that defines sensitivity and resolving power is usually assessed by AC susceptometry. In this study, we used SPaQ data to predict handheld detection performance for magnetic nanoparticles with various particle sizes. SPaQ assesses dynamics by measuring the derivative of the magnetization originating from magnetic nanoparticles activated by an alternating excitation field. The ratio between the maximum signal difference and full-width-at-half-maximumis used to estimate the optimal excitation frequency. Thereupon, it was shown that a particle with a combination of Brownian and Néel relaxation is superior in nonlinear handheld detection compared to Brownian or Néel only particles. Moreover, the optimal excitation frequency is generally established at a slightly higher frequency compared to the characteristic frequency assessed by AC susceptometry. Consequently, this insight into the consequences of the dynamic behavior of magnetic nanoparticles under an alternating magnetic field enables the optimization of nonlinear handheld detection for specific clinical applications.
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