Description
Magnetic microbeads are a key tool in automated immunoassays, where they enable selective capture, concentration, and purification of low‑abundance analytes.
On microfluidic platforms, magnetophoretic bead collection remains a major performance bottleneck, demanding precise control within microfluidic environments and repeated execution during binding, washing, and dilution steps. Consequently, the system is highly sensitive to microfluidic design and selected operating parameters and often requires extensive empirical tuning. To overcome these limitations, we present a comprehensive, experimentally validated computational framework designed to predict and optimize magnetic bead collection processes in rotating lab‑on‑a‑disc systems.
The core of this work is a finite‑element multiphysics model that resolves the coupled interactions governing bead motion, namely magnetic- and centrifugal forces, viscous drag, magnetophoresis‑induced convection, and cooperative bead aggregation into chains.
Two‑way coupling between bead motion and fluid flow enables the emergence of convection driven by bead slip velocity. This effect is known to significantly accelerate particle transport but remains rarely included in microfluidic design tools. The model additionally incorporates realistic bead–wall flux conditions, allowing direct prediction of bead surface accumulation and collection fractions. Finally, it accounts for bead aggregation into chains and adjust both the drag and magnetic force accordingly to the number of beads within a chain.
To establish quantitative accuracy, the simulations are validated using a dedicated rotating platform with real‑time imaging of Dynabeads™ M‑270. The model reproduces experimentally measured concentration fields, temporal collection curves, and characteristic timescales with high fidelity, despite relying solely on physically grounded parameters without any empirical fitting. This predictive capability enables systematic exploration of geometric and operational parameters that are challenging to assess experimentally.
In this work, we highlight the investigation of magnet field intensity by varying magnet–fluid distance, a critical geometric variable with direct implications for instrument design. Simulations performed for distances between 2.0 and 6.0 mm reveal a robust and approximately linear relationship between magnet–fluid spacing and collection time: larger distances weaken magnetic field gradients, reduce bead slip velocities, delay chain formation, and diminish induced convection. As a result, increasing the gap from 2mm to 6mm roughly triples the time required to reach a given collection fraction. This result is valid for the 95% threshold commonly targeted for reliable immunoassay workflows. This simple and transferable scaling rule offers immediate practical value for designers of centrifugal microfluidic instruments and cartridges.
Similarly, we show that for a fixed design, varying the rotational speed from 300 rpm to 800 rpm decreases the collection time of a given fraction exponentially. This result offers another immediate practical guide for selecting the rotational speed of a fixed design.
By combining detailed physics‑based modeling with experimental validation, this work provides a generalizable in‑silico tool that reduces reliance on costly trial‑and‑error prototyping and supports data‑driven optimization of magnetic separation modules. The computational framework is broadly applicable to platform architecture, disc‑magnet alignment, bead selection, and rotational protocol design, contributing to more efficient and robust microfluidic immunoassays.