Size Distribution of Magnetic Marker Estimated from AC Susceptibility in Solution for Biosensor Application

Abstract

The ac susceptibility of magnetic markers in solution was studied for biosensor application, where the marker consisted of magnetic nanoparticles and a coating material. From the frequency dependence of the susceptibility caused by the Brownian rotation of the marker, we estimated the distribution of marker size, which is an important parameter for biosensor application. For this purpose, we analyzed the experimental data by the singular value decomposition (SVD) method. Using this method, we can directly estimate the size distribution without assuming any distribution function. The estimated distributions were also compared with those obtained from optical dynamic light scattering (DLS) measurements. It was shown that the size distribution estimated by magnetic measurement (SVD) slightly shifts to a size lower than that estimated by the optical measurement (DLS). It was also shown that the frequency dependence of the susceptibility can be better explained by the size distribution estimated by the SVD method than by the distribution estimated with DLS. The difference between the magnetic and optical measurement results was discussed in terms of aggregation of the markers.

Real-time measurement of Brownian relaxation of magnetic nanoparticles by a mixing-frequency method

“…As shown in the Fig. 2, Debye model with the superposition of MNPs' hydrodynamic size distribution 12 is a good fit in our case, although it is argued that Debye model is only valid for small-amplitude ͑Ͻ1 kA/ m͒ ͑Ref. 13͒ low-frequency 14 applied ac field and a high frequency susceptibility ϱ is needed for the Debye fitting.…”

Hysteresis Loss of Fractionated Magnetic Nanoparticles for Hyperthermia Application

“…The distribution function m ( ) can be obtained by applying the singular value decomposition (SVD) method [10], [13], [14] to the M-H curve shown in Fig. 1.…”

Magnetic Nanoparticle Imaging Using Second Harmonic Signals for Sentinel Lymph Node Detection

“…As shown, it is not possible to distinguish two MNP samples directly from the contour map. We showed that to distinguish the two samples, the spatial resolution can be considerably improved by analyzing the contour map using the SVD method 12) . This technique enables us to convert the contour map Bz(x,y) measured at z = 0 to the MNP density distribution n(x,y) at a given sample depth z.…”

“…For this purpose, we developed an MPI system that uses the second harmonic signal from the MNPs, with which we could significantly decrease the interference of the excitation field 10), 11) . We also developed a method to improve the spatial resolution of MNP detection by using the mathematical technique known as singular value decomposition (SVD) 12) . This technique enables us to convert the measured contour map of the signal field to the MNP density distribution n(x,y) at a given sample depth z, and could much improve the spatial resolution of MNP detection.…”