Comparative Modeling of Frequency Mixing Measurements of Magnetic Nanoparticles Using Micromagnetic Simulations and Langevin Theory
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 stati...
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doaj-9e882706a0924c4fb33885892327dd872021-05-31T23:39:17ZengMDPI AGNanomaterials2079-49912021-05-01111257125710.3390/nano11051257Comparative Modeling of Frequency Mixing Measurements of Magnetic Nanoparticles Using Micromagnetic Simulations and Langevin TheoryUlrich M. Engelmann0Ahmed Shalaby1Carolyn Shasha2Kannan M. Krishnan3Hans-Joachim Krause4Department of Medical Engineering and Applied Mathematics, FH Aachen University of Applied Sciences, 52428 Jülich, GermanyDepartment of Medical Engineering and Applied Mathematics, FH Aachen University of Applied Sciences, 52428 Jülich, GermanyDepartment of Physics, University of Washington, Seattle, WA 98195, USADepartment of Physics, University of Washington, Seattle, WA 98195, USADepartment of Medical Engineering and Applied Mathematics, FH Aachen University of Applied Sciences, 52428 Jülich, GermanyDual 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.https://www.mdpi.com/2079-4991/11/5/1257magnetic nanoparticlesfrequency mixing magnetic detectionLangevin theorymicromagnetic simulationnonequilibrium dynamicsmagnetic relaxation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ulrich M. Engelmann Ahmed Shalaby Carolyn Shasha Kannan M. Krishnan Hans-Joachim Krause |
spellingShingle |
Ulrich M. Engelmann Ahmed Shalaby Carolyn Shasha Kannan M. Krishnan Hans-Joachim Krause Comparative Modeling of Frequency Mixing Measurements of Magnetic Nanoparticles Using Micromagnetic Simulations and Langevin Theory Nanomaterials magnetic nanoparticles frequency mixing magnetic detection Langevin theory micromagnetic simulation nonequilibrium dynamics magnetic relaxation |
author_facet |
Ulrich M. Engelmann Ahmed Shalaby Carolyn Shasha Kannan M. Krishnan Hans-Joachim Krause |
author_sort |
Ulrich M. Engelmann |
title |
Comparative Modeling of Frequency Mixing Measurements of Magnetic Nanoparticles Using Micromagnetic Simulations and Langevin Theory |
title_short |
Comparative Modeling of Frequency Mixing Measurements of Magnetic Nanoparticles Using Micromagnetic Simulations and Langevin Theory |
title_full |
Comparative Modeling of Frequency Mixing Measurements of Magnetic Nanoparticles Using Micromagnetic Simulations and Langevin Theory |
title_fullStr |
Comparative Modeling of Frequency Mixing Measurements of Magnetic Nanoparticles Using Micromagnetic Simulations and Langevin Theory |
title_full_unstemmed |
Comparative Modeling of Frequency Mixing Measurements of Magnetic Nanoparticles Using Micromagnetic Simulations and Langevin Theory |
title_sort |
comparative modeling of frequency mixing measurements of magnetic nanoparticles using micromagnetic simulations and langevin theory |
publisher |
MDPI AG |
series |
Nanomaterials |
issn |
2079-4991 |
publishDate |
2021-05-01 |
description |
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. |
topic |
magnetic nanoparticles frequency mixing magnetic detection Langevin theory micromagnetic simulation nonequilibrium dynamics magnetic relaxation |
url |
https://www.mdpi.com/2079-4991/11/5/1257 |
work_keys_str_mv |
AT ulrichmengelmann comparativemodelingoffrequencymixingmeasurementsofmagneticnanoparticlesusingmicromagneticsimulationsandlangevintheory AT ahmedshalaby comparativemodelingoffrequencymixingmeasurementsofmagneticnanoparticlesusingmicromagneticsimulationsandlangevintheory AT carolynshasha comparativemodelingoffrequencymixingmeasurementsofmagneticnanoparticlesusingmicromagneticsimulationsandlangevintheory AT kannanmkrishnan comparativemodelingoffrequencymixingmeasurementsofmagneticnanoparticlesusingmicromagneticsimulationsandlangevintheory AT hansjoachimkrause comparativemodelingoffrequencymixingmeasurementsofmagneticnanoparticlesusingmicromagneticsimulationsandlangevintheory |
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