IEEE TRANSACTIONS ON MAGNETICS, VOL. 50, NO. 11, NOVEMBER 2014
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Magnetic, Structural, and Particle Size Analysis of Single- and Multi-Core Magnetic Nanoparticles Frank Ludwig1 , Olga Kazakova2, Luis Fernández Barquín3 , Andrea Fornara4 , Lutz Trahms5 , Uwe Steinhoff5 , Peter Svedlindh6, Erik Wetterskog6 , Quentin A. Pankhurst7, Paul Southern7 , Puerto Morales3 , Mikkel Fougt Hansen8, Cathrine Frandsen9, Eva Olsson10, Stefan Gustafsson10, Nicole Gehrke11 , Kerstin Lüdtke-Buzug12, Cordula Grüttner13 , Christian Jonasson14, and Christer Johansson14 1 Institute
of Electrical Measurement and Fundamental Electrical Engineering, Technische Universität Braunschweig, Braunschweig D-38106, Germany 2 National Physical Laboratory, Teddington TW11 0LW, U.K. 3 Departamento CITIMAC, University of Cantabria, Santander E-39005, Spain 4 SP Technical Research Institute of Sweden, Stockholm SE-114 86, Sweden 5 Physikalisch-Technische Bundesanstalt, Berlin D-10587, Germany 6 Department of Engineering Sciences, Uppsala University, Uppsala 751 21, Sweden 7 Institute of Biomedical Engineering, University College of London, London WC1E 6BT, U.K. 8 Department of Micro- and Nanotechnology, DTU Nanotech, Kgs. Lyngby DK-2800, Denmark 9 Department of Physics, DTU, Kgs. Lyngby DK-2800, Denmark 10 Department of Applied Physics, Chalmers University of Technology, Göteborg SE-412 96, Sweden 11 nanoPET Pharma GmbH, Berlin D-10115, Germany 12 Institute of Medical Engineering, University of Lübeck, Lübeck D-23562, Germany 13 Micromod Partikeltechnologie GmbH, Rostock D-18119, Germany 14 Acreo Swedish ICT AB, Göteborg SE-400 14, Sweden We have measured and analyzed three different commercial magnetic nanoparticle systems, both multi-core and single-core in nature, with the particle (core) size ranging from 20 to 100 nm. Complementary analysis methods and same characterization techniques were carried out in different labs and the results are compared with each other. The presented results primarily focus on determining the particle size—both the hydrodynamic size and the individual magnetic core size—as well as magnetic and structural properties. The used analysis methods include transmission electron microscopy, static and dynamic magnetization measurements, and Mössbauer spectroscopy. We show that particle (hydrodynamic and core) size parameters can be determined from different analysis techniques and the individual analysis results agree reasonably well. However, in order to compare size parameters precisely determined from different methods and models, it is crucial to establish standardized analysis methods and models to extract reliable parameters from the data. Index Terms— Magnetic analysis, magnetic materials, magnetic particles, nanoparticles.
I. I NTRODUCTION
M
AGNETIC iron oxide nanoparticles with sizes from a few nanometers and multi-core composite particles with sizes up to several micrometers can be found in several biomedical applications in the areas of diagnosis, therapy, actuating, and imaging [1], [2]. Single-core magnetic nanoparticles can be coarsely divided into small particles that show internal magnetic relaxation (Néel relaxation) and larger particles that are thermally blocked. An ensemble of singlecore particles, with a typical relaxation time shorter than the specific time scale of the measurement (the measurement time) of the system, behaves as a superparamagnetic material and shows no hysteresis effect and no residual magnetization (remanence). On the other hand, an ensemble of thermally Manuscript received March 7, 2014; revised April 28, 2014; accepted April 29, 2014. Date of current version November 18, 2014. Corresponding author: F. Ludwig (e-mail:
[email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TMAG.2014.2321456
blocked particles has a magnetic relaxation time that is longer than the specific measurement time scale and both hysteresis and time-dependent effects can be found in their response to an external magnetic field. Magnetic nanoparticles can further be coated by an organic shell in order to improve their biocompatibility and facilitate their suspension in a carrier liquid. In that case, the particle magnetic moment can be decoupled from the physical particle rotation in the liquid (Néel relaxation) or have a particle moment that is physically locked in a specific particle direction. In the latter case, magnetic relaxation occurs at the same rate as the particle rotation in the liquid (Brownian relaxation). The parameters that determine whether we have Néel or Brownian relaxation of a nanoparticle system dispersed in the carrier liquid at given temperature, are the sizes and shapes of the nanoparticles, the magnetic material properties (through the magnetic anisotropy) and the viscous properties of the liquid. Both types of magnetic behavior (Néel and Brownian relaxation) can be used in different biomedical applications, such as in magnetic biosensor detection systems,
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IEEE TRANSACTIONS ON MAGNETICS, VOL. 50, NO. 11, NOVEMBER 2014
or as local heat sources in magnetic hyperthermia to kill tumor cells, separation in immunoassay, drug delivery, or as contrast substances in magnetic resonance imaging or magnetic particle imaging [3]. Since the behavior of magnetic nanoparticles in a suspension crucially depends on their physical properties, it is of vital importance for the different applications, particularly in medicine, that the magnetic nanoparticle systems are analyzed with methods that are well defined and standardized. There are many analysis techniques that are used to characterize magnetic nanoparticle systems, for instance magnetization versus field curves (M–H ) at different temperatures, dynamic magnetic analysis such as AC susceptometry (ACS), magnetorelaxometry (MRX), Mössbauer spectroscopy, electron microscopy, dynamic light scattering, X-ray diffraction, ferromagnetic resonance and neutron scattering. These techniques give information on the physical and chemical properties of the magnetic nanoparticle systems. In this paper, we present primarily results from analysis techniques that give information on particle size (hydrodynamic and as well as core size) as well as on magnetic and structural properties.
Fig. 1. Left: TEM image of a Micromod BNF-Starch multi-core cluster. Right: corresponding multi-core particle size distribution. The circle in the left picture defines the diameter of the cluster.
II. E XPERIMENTAL The studied particle systems are two multi-core particle systems; BNF-Starch: magnetite core with a total hydrodynamic particle diameter of 80 nm from Micromod and FeraSpin R: magnetite core with a total hydrodynamic particle diameter (i.e., the diameter including shell) of 60 nm from nanoPET; two magnetite single-core particle systems; SHP-25 and SHP-20 with nominal particle core diameters of 25 and 20 nm from Ocean Nanotech. The above particle sizes have been estimated by the manufacturers using dynamic light scattering and TEM measurements. The TEM analysis was performed using two different instruments: 1) an FEI Tecnai F20 equipped with a LaB6 electron gun and operated at 200 kV and 2) an FEI Titan 80–300 equipped with a field emission gun and operating at 80 or 300 kV. Sample preparation was carried out by placing a drop of diluted particle suspension on a Cu grid coated with a perforated carbon film, and leaving it to dry in air. Static magnetization versus field was measured using a Quantum Design MPMS-XL system. Measurements were performed at 300 K and at lower temperatures down to 10 K. Dynamic magnetization versus excitation frequency was measured with two AC (DynoMag system and a lab ACS) and a high-frequency AC susceptometer (lab prototype ACS) in the frequency range from 1 Hz to 10 MHz. These measurements were carried out at room temperature. To further study the dynamic magnetic properties, we also used MRX analysis (with fluxgates [4], FG-MRX, and SQUID sensors [5], SQUID-MRX) at room temperature. Mössbauer spectroscopy in zero field was performed at temperatures between 17 K and room temperature. The magnetic particle spectroscopy (MPS) [6] system comprised a Helmholtz coil pair for generating a homogeneous oscillating excitation field in combination with a static offset field. Both could be set to a maximum field amplitude of
Fig. 2. Mössbauer spectra at 150 and 17 K in zero field of the BNF-Starch particle system.
40 mT. Standardized measurements are performed with an excitation frequency of 25 kHz and with field amplitudes of 20 or 25 mT. III. R ESULTS The TEM images were recorded for samples BNF-Starch 80 and SHP-25. BNF-Starch 80 clusters consist of individual nanocrystals with cubic or rhombohedral shape with a characteristic dimension of 10–20 nm (Fig. 1). To determine the size distribution of these clusters, a circle was drawn around each cluster so that all nanocrystals fitted into it. The evaluation of 200 clusters provided a cluster diameter of 100 ± 24 nm. The single-core particle system SHP-25 comprised nearly spherical cores with a diameter of 24.5 ± 1.9 nm as determined from the particle size distribution. This value is in agreement with that quoted by the manufacturer. Mössbauer spectra of the BNF-Starch particle system can be seen in Fig. 2. From the Mössbauer analysis, we can determine that the BNF-Starch multi-core particle system contains magnetic nanoparticles of non-stochiometric magnetite (with Verwey
LUDWIG et al.: MAGNETIC, STRUCTURAL, AND PARTICLE SIZE ANALYSIS OF SINGLE- AND MULTI-CORE MAGNETIC NANOPARTICLES
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Fig. 4. Volume fraction versus particle diameter as result of the fitting of the magnetization versus field curves. As known from measurements on other multi-core particle systems, the fit of M–H curves measured on BNF-Starch and FeraSpin R required the inclusion of a bimodal distribution of moments. The core diameters were determined using the given saturation magnetization value.
Fig. 3. Magnetization versus field for the BNF-Starch particle system at 10 and 300 K. The figure below is a close up in field of the figure above.
transition between 150 and 17 K and increased linewidths of the subcomponent spectra). The result of magnetite in the magnetic nanoparticles is also supported by XRD analysis of the BNF particle system. Static magnetization measurements on the BNF-Starch particle system at 10 and 300 K are shown in Fig. 3. The intrinsic saturation magnetization of the nanocrystals at room temperature—as determined by one partner—is about 390 kA/m for the BNF-Starch particles, about 350 kA/m for the FeraSpin R system, and about 260 and 280 kA/m for the SHP-25 and SHP-20 particle systems, respectively. The value for bulk magnetite at room temperature amounts to 480 kA/m. The reduction of the intrinsic magnetization is due to size effects of magnetic nanoparticles. The M–H curves measured in another lab on suspensions of the particle systems at room temperature were also analyzed assuming a lognormal distribution of non-interacting magnetic moments for the single-core particles. For the multicore particle systems, a bimodal distribution had to be assumed to obtain good fits. The result of the measurement and analysis of the data can be seen in Fig. 4. The distribution of core diameters was also determined from MRX measurements (Fig. 5) utilizing either the SQUID setup at the PTB or the fluxgate setup at TU Braunschweig. In both cases, samples were also immobilized by freeze-drying the nanoparticles in a mannitol matrix. Consequently, particle moments can only relax via the internal Néel mechanism with the corresponding time constant depending on the anisotropy energy K · Vc (Vc is the core volume). With known anisotropy constant, K , the particle core diameter can be estimated. Since the harmonic spectrum in MPS also reflects the distribution of magnetic moments, it can also be used to
Fig. 5. Magnetic flux density signal as a function of time measured on suspended (blue line) and immobile (black line) BNF-Starch test sample. Fluxgate sensor system was used in this measurement. The green dashed line is the MSM fit.
Fig. 6.
MPS spectra of the BNF-Starch particle system.
determine the core size distribution. The diameter of the particle core is determined by applying the Langevin model and solving the inverse problem based on the predominant harmonics. The MPS spectra (Fig. 6) were recorded for an excitation field of 25 mT amplitude and 25 kHz excitation frequency. The results of the magnetic core size distribution using the above given methods are listed in Table I.
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TABLE I S UMMARY OF M EAN VALUES dc AND W IDTH σc OF THE M AGNETIC C ORE S IZE D ISTRIBUTION . T HE D OUBLE VALUES OF THE M EAN S IZE AND D ISTRIBUTION W IDTH FOR BNF-S TARCH AND F ERA S PIN R I NDICATE THE R ESULTS U SING B IMODAL S IZE D ISTRIBUTION IN THE
M–H A NALYSIS . L OGNORMAL D ISTRIBUTION I S U SED IN THE A NALYSIS . VALUES A RE IN nm
extract size parameters from the experimental data, especially for the multi-core particles (BNF-Starch and FeraSpin R). The dh values of single-core particle samples SHP-20 and SHP-25 compare well with the dc values in Table I, whereas the regarding multicore values appear logically different. From ACS measurements (data not shown), it is also observed that all of the liquid suspension particle systems show dominant Brownian relaxation (with peaks from 400 Hz to 10 kHz), except for the SHP-20 particle system where a Néel relaxation peak is above 10 MHz. IV. C ONCLUSION
Fig. 7. AC susceptibility versus frequency for the BNF-Starch particle system from 1 Hz to 10 MHz. The relaxation peak at 400 Hz is due to Brownian relaxation. Symbols represent experimental data and solid lines result of the fitting. TABLE II S UMMARY OF M EAN VALUES dh AND W IDTH σh OF THE H YDRODYNAMIC S IZE D ISTRIBUTION . L OG -N ORMAL D ISTRIBUTION I S U SED IN THE A NALYSIS . VALUES A RE IN nm
We have shown that particle size parameters (hydrodynamic as well as core size) can be determined from different analysis techniques. The results agree reasonably well in the case of hydrodynamic sizes (Table II) when the results from the ACS analysis at two different labs are compared. There are some deviations of the results and this is primarily an effect of somewhat different used models to extract the size parameters. In Table I where the magnetic core size determinations are compiled larger deviations between the analysis techniques can be seen. This is probably an effect of that the models used to extract the core size parameters are not exactly representative of the analysed particle systems with respect to including magnetic interactions in the models, using mono or bimodal core size distributions in the analysis, the use of magnetic parameters independently determined from other analysis techniques for instance the magnetic anisotropy in the MRX analysis and finally the use of an appropriate dynamic magnetic model in the MPS analysis. In order to achieve a more consistent picture and the possibility to compare size parameters precisely determined from different analysis methods, it is crucial to use standardized analysis methods and to improve the models in order to extract magnetic nanoparticle parameters from the experimental data. We will further work on these issues and publish the results in later papers. ACKNOWLEDGMENT This work was supported by the European Commission Seventh Framework Programme through the NanoMag project under Grant 604448.
The diversity of values in Table I indicates how crucial the precise and reliable determination of core size distributions depends on the applied model and the used magnetic particle parameters that is included in the models in order to extract parameters of the particle core size. The hydrodynamic size of particles and clusters was determined by ACS measurements on particle suspensions. An example of the AC susceptibility versus frequency for the BNF particle system can be seen in Fig. 7. The hydrodynamic size parameters determined using ACS by different groups are summarized in Table II. For comparison, the hydrodynamic size for the FeraSpin R particles was determined by dynamic light scattering to be 63.1 nm. Again, the spread in parameters obtained on nominally identical samples is caused by the chosen models to
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