@article{PourshahidiAchtsnichtNambipareecheeetal.2021,
  author    = {Pourshahidi, Ali Mohammad and Achtsnicht, Stefan and Nambipareechee, Mrinal Murali and Offenh{\"a}usser, Andreas and Krause, Hans-Joachim},
  title     = {Multiplex detection of magnetic beads using offset field dependent frequency mixing magnetic detection},
  series = {Sensors},
  volume    = {21},
  journal   = {Sensors},
  number    = {17},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s21175859},
  pages     = {16 Seiten},
  year      = {2021},
  abstract  = {Magnetic immunoassays employing Frequency Mixing Magnetic Detection (FMMD) have recently become increasingly popular for quantitative detection of various analytes. Simultaneous analysis of a sample for two or more targets is desirable in order to reduce the sample amount, save consumables, and save time. We show that different types of magnetic beads can be distinguished according to their frequency mixing response to a two-frequency magnetic excitation at different static magnetic offset fields. We recorded the offset field dependent FMMD response of two different particle types at frequencies ƒ₁ + n⋅ƒ₂, n = 1, 2, 3, 4 with ƒ₁ = 30.8 kHz and ƒ₂ = 63 Hz. Their signals were clearly distinguishable by the locations of the extremes and zeros of their responses. Binary mixtures of the two particle types were prepared with different mixing ratios. The mixture samples were analyzed by determining the best linear combination of the two pure constituents that best resembled the measured signals of the mixtures. Using a quadratic programming algorithm, the mixing ratios could be determined with an accuracy of greater than 14\%. If each particle type is functionalized with a different antibody, multiplex detection of two different analytes becomes feasible.},
  language  = {en}
}
@article{EngelmannShalabyShashaetal.2021,
  author    = {Engelmann, Ulrich M. and Shalaby, Ahmed and Shasha, Carolyn and Krishnan, Kannan M. and Krause, Hans-Joachim},
  title     = {Comparative modeling of frequency mixing measurements of magnetic nanoparticles using micromagnetic simulations and Langevin theory},
  series = {Nanomaterials},
  volume    = {11},
  journal   = {Nanomaterials},
  number    = {5},
  publisher = {MDPI},
  address   = {Basel},
  isbn      = {2079-4991},
  doi       = {10.3390/nano11051257},
  pages     = {1 -- 16},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}