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Keywords = 3D magnetic stray field mapping

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23 pages, 1104 KB  
Article
μFlow: A Computational Platform for Microfluidic Hall-Effect Magnetic Bead Detection with Parametric Design Optimization
by Harshitha Govindaraju and Umer Hassan
Micromachines 2026, 17(9), 1042; https://doi.org/10.3390/mi17091042 - 31 Aug 2026
Viewed by 353
Abstract
Microfluidic Hall-effect biosensors detect superparamagnetic bead labels as they flow past a thin-film Hall element in a microchannel. Designing one couples bead magnetization, stray-field distribution, Hall transport, and channel flow across 14 parameters that finite-element solvers explore only at minutes to hours per [...] Read more.
Microfluidic Hall-effect biosensors detect superparamagnetic bead labels as they flow past a thin-film Hall element in a microchannel. Designing one couples bead magnetization, stray-field distribution, Hall transport, and channel flow across 14 parameters that finite-element solvers explore only at minutes to hours per configuration. We present a coupled analytical–numerical framework for this signal chain: Clausius–Mossotti bead magnetization with a volume fraction correction, a point-dipole stray field, a volume-averaged Hall voltage, Poiseuille transport, and a Johnson–Nyquist and Hooge 1/f noise model, evaluated across 12 sensor presets compiled from the literature, spanning graphene, III–V semiconductors, Si CMOS, bismuth, and topological insulators; any other platform can be defined from user-supplied transport parameters. Benchmarked against a companion COMSOL Multiphysics 6.0 study, the framework reproduces the Hall voltage to within 4.8% at a favorable bead-to-sensor area ratio and deviates by 22% and 15% at off-optimum geometries, consistent with the point-dipole near-field limit at h/rb=1. Three design rules follow: a signal-to-noise ridge at sensor widths comparable to the bead diameter (w*db; area ratios 0.4–1.0 at constant voltage, 0.5–2.6 at constant current), matching reported single-bead geometries; a material choice that must be made under an explicit electrical drive constraint; and a sampling-limited flow-velocity window. Predicted signals agree at the order-of-magnitude level with published InAs and Si CMOS experiments. We release the model as a freely accessible, no-install browser implementation with a built-in 2D axisymmetric magnetostatic finite-element (FEM) solver that maps where the dipole approximation degrades. Full article
(This article belongs to the Special Issue Nanomaterials for Energy Storage and Sensing Applications)
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15 pages, 4502 KB  
Article
High-Fidelity 3D Stray Magnetic Field Mapping of Smartphones to Address Safety Considerations with Active Implantable Electronic Medical Devices
by Nandita Saha, Jason M. Millward, Carl J. J. Herrmann, Faezeh Rahimi, Haopeng Han, Philipp Lacour, Florian Blaschke and Thoralf Niendorf
Sensors 2023, 23(3), 1209; https://doi.org/10.3390/s23031209 - 20 Jan 2023
Cited by 6 | Viewed by 6418
Abstract
Case reports indicate that magnets in smartphones could be a source of electromagnetic interference (EMI) for active implantable medical devices (AIMD), which could lead to device malfunction, compromising patient safety. Recognizing this challenge, we implemented a high-fidelity 3D magnetic field mapping (spatial resolution [...] Read more.
Case reports indicate that magnets in smartphones could be a source of electromagnetic interference (EMI) for active implantable medical devices (AIMD), which could lead to device malfunction, compromising patient safety. Recognizing this challenge, we implemented a high-fidelity 3D magnetic field mapping (spatial resolution 1 mm) setup using a three-axis Hall probe and teslameter, controlled by a robot (COSI Measure). With this setup, we examined the stray magnetic field of an iPhone 13 Pro, iPhone 12, and MagSafe charger to identify sources of magnetic fields for the accurate risk assessment of potential interferences with AIMDs. Our measurements revealed that the stray fields of the annular array of magnets, the wide-angle camera, and the speaker of the smartphones exceeded the 1 mT limit defined by ISO 14117:2019. Our data-driven safety recommendation is that an iPhone 13 Pro should be kept at least 25 mm away from an AIMD to protect it from unwanted EMI interactions. Our study addresses safety concerns due to potential device–device interactions between smartphones and AIMDs and will help to define data-driven safety guidelines. We encourage vendors of electronic consumer products (ECP) to provide information on the magnetic fields of their products and advocate for the inclusion of smartphones in the risk assessment of EMI with AIMDs. Full article
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15 pages, 2719 KB  
Article
The Scanning TMR Microscope for Biosensor Applications
by Kunal N. Vyas, David M. Love, Adrian Ionescu, Justin Llandro, Pratap Kollu, Thanos Mitrelias, Stuart Holmes and Crispin H. W. Barnes
Biosensors 2015, 5(2), 172-186; https://doi.org/10.3390/bios5020172 - 2 Apr 2015
Cited by 2 | Viewed by 8047
Abstract
We present a novel tunnel magnetoresistance (TMR) scanning microscopeset-up capable of quantitatively imaging the magnetic stray field patterns of micron-sizedelements in 3D. By incorporating an Anderson loop measurement circuit for impedancematching, we are able to detect magnetoresistance changes of as little as 0.006%/Oe. [...] Read more.
We present a novel tunnel magnetoresistance (TMR) scanning microscopeset-up capable of quantitatively imaging the magnetic stray field patterns of micron-sizedelements in 3D. By incorporating an Anderson loop measurement circuit for impedancematching, we are able to detect magnetoresistance changes of as little as 0.006%/Oe. By 3Drastering a mounted TMR sensor over our magnetic barcodes, we are able to characterisethe complex domain structures by displaying the real component, the amplitude and thephase of the sensor’s impedance. The modular design, incorporating a TMR sensor withan optical microscope, renders this set-up a versatile platform for studying and imagingimmobilised magnetic carriers and barcodes currently employed in biosensor platforms,magnetotactic bacteria and other complex magnetic domain structures of micron-sizedentities. The quantitative nature of the instrument and its ability to produce vector maps ofmagnetic stray fields has the potential to provide significant advantages over other commonlyused scanning magnetometry techniques. Full article
(This article belongs to the Special Issue Magnetic Biosensors)
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