Matter Industries required a detailed assessment of "High-Fidelity Simulation of Microplastic Capture Technology" in 2022. The work brought together computational fluid dynamics (CFD) and the project information supplied for this process and manufacturing application. The central objective was to connect local flow, thermal, transport or process behaviour with system-level performance, risk and design decisions that the client could implement.

An innovative self-cleaning microfibre filtration system developed by Matter.® was assessed and optimised using high-fidelity CFD simulations to support its scale-up toward industrial deployment. Designed to prevent microplastics entering waterways from washing machines and textile manufacturing processes, the Regen.® technology has since achieved international recognition as an Earthshot Prize finalist and has been commercially deployed through partnerships with Bosch and Siemens. A high fidelity LB-LES solver was used to investigate flow distribution, membrane behaviour, and particle transport under multiple operating and geometric conditions. Parametric studies examining flow rate sensitivity, geometric scaling, inlet configuration, and internal guide structures provided key insights into filtration efficiency, flow uniformity, and large-scale operational performance, helping optimise the design for industrial applications.

The methodology centred on a high-fidelity lattice-Boltzmann large-eddy CFD model of the self-cleaning microfibre filtration system. The representation retained the rotating impeller, air-water flow, membrane or filter region, guide structures and representative microplastic and fibre particles. Boundary and operating conditions covered flow-rate changes, geometric scaling, inlet configuration, internal guides and operating conditions relevant to industrial deployment, with material, fluid and equipment properties assigned from the available design information. Resolution was concentrated in regions where steep velocity, thermal, concentration or phase gradients were expected, while the overall model remained efficient enough to compare several credible configurations. This balance allowed system-level performance to be linked to the local mechanisms responsible for it.

The assessment compared scale-up and internal-flow modifications intended to preserve capture efficiency and uniform loading. Performance was judged using flow distribution, turbulence, membrane behaviour, particle trajectories and capture, pressure demand, uniformity and sensitivity to scale. Results were reviewed through quantitative summaries and engineering visualisations, such as contours, vectors, streamlines, sections and time histories, selected to suit the physics. Important assumptions and operating uncertainties were considered so that the recommendations relied on repeatable comparative trends rather than a single nominal case.

For Matter Industries, the principal value was a technically de-risked route from household-scale technology to robust industrial application. The final evidence linked each recommendation to the relevant model or process output, making it suitable for internal design reviews, supplier or contractor discussions and, where applicable, planning, safety or regulatory dialogue. The work also created a reusable baseline that can be updated as geometry, operating data or test results become available, reducing the cost and risk of later design iterations.

A disciplined quality-control workflow supported the analysis. Geometry, units, mass and energy balances, boundary-condition consistency and solver convergence were checked before options were ranked. Mesh or parameter sensitivities were used where they were most likely to affect the engineering conclusion, and limitations were documented explicitly. This ensured that the study remained traceable and reproducible rather than relying on isolated simulation images.