@article{PourshahidiEngelmannOffenhaeusseretal.2022, author = {Pourshahidi, Ali Mohammad and Engelmann, Ulrich M. and Offenh{\"a}usser, Andreas and Krause, Hans-Joachim}, title = {Resolving ambiguities in core size determination of magnetic nanoparticles from magnetic frequency mixing data}, series = {Journal of Magnetism and Magnetic Materials}, volume = {563}, journal = {Journal of Magnetism and Magnetic Materials}, number = {In progress, Art. No. 169969}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0304-8853}, doi = {10.1016/j.jmmm.2022.169969}, year = {2022}, abstract = {Frequency mixing magnetic detection (FMMD) has been widely utilized as a measurement technique in magnetic immunoassays. It can also be used for the characterization and distinction (also known as "colourization") of different types of magnetic nanoparticles (MNPs) based on their core sizes. In a previous work, it was shown that the large particles contribute most of the FMMD signal. This leads to ambiguities in core size determination from fitting since the contribution of the small-sized particles is almost undetectable among the strong responses from the large ones. In this work, we report on how this ambiguity can be overcome by modelling the signal intensity using the Langevin model in thermodynamic equilibrium including a lognormal core size distribution fL(dc,d0,σ) fitted to experimentally measured FMMD data of immobilized MNPs. For each given median diameter d0, an ambiguous amount of best-fitting pairs of parameters distribution width σ and number of particles Np with R2 > 0.99 are extracted. By determining the samples' total iron mass, mFe, with inductively coupled plasma optical emission spectrometry (ICP-OES), we are then able to identify the one specific best-fitting pair (σ, Np) one uniquely. With this additional externally measured parameter, we resolved the ambiguity in core size distribution and determined the parameters (d0, σ, Np) directly from FMMD measurements, allowing precise MNPs sample characterization.}, language = {en} } @article{EngelmannPourshahidiShalabyetal.2022, author = {Engelmann, Ulrich M. and Pourshahidi, Mohammad Ali and Shalaby, Ahmed and Krause, Hans-Joachim}, title = {Probing particle size dependency of frequency mixing magnetic detection with dynamic relaxation simulation}, series = {Journal of Magnetism and Magnetic Materials}, volume = {563}, journal = {Journal of Magnetism and Magnetic Materials}, number = {In progress, Art. No. 169965}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0304-8853}, doi = {10.1016/j.jmmm.2022.169965}, year = {2022}, abstract = {Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles' magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing.}, language = {en} } @article{EngelmannSimsekShalabyetal.2024, author = {Engelmann, Ulrich M. and Simsek, Beril and Shalaby, Ahmed and Krause, Hans-Joachim}, title = {Key contributors to signal generation in frequency mixing magnetic detection (FMMD): an in silico study}, series = {Sensors}, volume = {24}, journal = {Sensors}, number = {6}, publisher = {MDPI}, address = {Basel}, issn = {1424-8220}, doi = {10.3390/s24061945}, pages = {Artikel 1945}, year = {2024}, abstract = {Frequency mixing magnetic detection (FMMD) is a sensitive and selective technique to detect magnetic nanoparticles (MNPs) serving as probes for binding biological targets. Its principle relies on the nonlinear magnetic relaxation dynamics of a particle ensemble interacting with a dual frequency external magnetic field. In order to increase its sensitivity, lower its limit of detection and overall improve its applicability in biosensing, matching combinations of external field parameters and internal particle properties are being sought to advance FMMD. In this study, we systematically probe the aforementioned interaction with coupled N{\´e}el-Brownian dynamic relaxation simulations to examine how key MNP properties as well as applied field parameters affect the frequency mixing signal generation. It is found that the core size of MNPs dominates their nonlinear magnetic response, with the strongest contributions from the largest particles. The drive field amplitude dominates the shape of the field-dependent response, whereas effective anisotropy and hydrodynamic size of the particles only weakly influence the signal generation in FMMD. For tailoring the MNP properties and parameters of the setup towards optimal FMMD signal generation, our findings suggest choosing large particles of core sizes dc > 25 nm nm with narrow size distributions (σ < 0.1) to minimize the required drive field amplitude. This allows potential improvements of FMMD as a stand-alone application, as well as advances in magnetic particle imaging, hyperthermia and magnetic immunoassays.}, language = {en} }