TY  - JOUR
A1  - Engelmann, Ulrich M.
A1  - Shasha, Carolyn
A1  - Teeman, Eric
A1  - Slabu, Iona
A1  - Krishnan, Kannan M.
T1  - Predicting size-dependent heating efficiency of magnetic nanoparticles from experiment and stochastic Néel-Brown Langevin simulation
JF  - Journal of Magnetism and Magnetic Materials
Y1  - 2019
U6  - http://dx.doi.org/10.1016/j.jmmm.2018.09.041
SN  - 0304-8853
VL  - 471
IS  - 1
SP  - 450
EP  - 456
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - CHAP
A1  - Engelmann, Ulrich M.
A1  - Shasha, Carolyn
A1  - Slabu, Ioana
T1  - Magnetic nanoparticle relaxation in biomedical application: focus on simulating nanoparticle heating
T2  - Magnetic nanoparticles in human health and medicine
Y1  - 2021
SN  - 978-1-119-75467-1
SP  - 327
EP  - 354
PB  - Wiley-Blackwell
CY  - Hoboken, New Jeersey
ER  - 
TY  - JOUR
A1  - Engelmann, Ulrich M.
A1  - Shalaby, Ahmed
A1  - Shasha, Carolyn
A1  - Krishnan, Kannan M.
A1  - Krause, Hans-Joachim
T1  - Comparative modeling of frequency mixing measurements of magnetic nanoparticles using micromagnetic simulations and Langevin theory
JF  - Nanomaterials
N2  - Dual frequency magnetic excitation of magnetic nanoparticles (MNP) enables enhanced biosensing applications. This was studied from an experimental and theoretical perspective: nonlinear sum-frequency components of MNP exposed to dual-frequency magnetic excitation were measured as a function of static magnetic offset field. The Langevin model in thermodynamic equilibrium was fitted to the experimental data to derive parameters of the lognormal core size distribution. These parameters were subsequently used as inputs for micromagnetic Monte-Carlo (MC)-simulations. From the hysteresis loops obtained from MC-simulations, sum-frequency components were numerically demodulated and compared with both experiment and Langevin model predictions. From the latter, we derived that approximately 90% of the frequency mixing magnetic response signal is generated by the largest 10% of MNP. We therefore suggest that small particles do not contribute to the frequency mixing signal, which is supported by MC-simulation results. Both theoretical approaches describe the experimental signal shapes well, but with notable differences between experiment and micromagnetic simulations. These deviations could result from Brownian relaxations which are, albeit experimentally inhibited, included in MC-simulation, or (yet unconsidered) cluster-effects of MNP, or inaccurately derived input for MC-simulations, because the largest particles dominate the experimental signal but concurrently do not fulfill the precondition of thermodynamic equilibrium required by Langevin theory.
KW  - Magnetic nanoparticles
KW  - Frequency mixing magnetic detection
KW  - Langevin theory
KW  - Micromagnetic simulation
KW  - Nonequilibrium dynamics
Y1  - 2021
SN  - 2079-4991
U6  - http://dx.doi.org/10.3390/nano11051257
N1  - This article belongs to the Special Issue Applications and Properties of Magnetic Nanoparticles
VL  - 11
IS  - 5
SP  - 1
EP  - 16
PB  - MDPI
CY  - Basel
ER  -