ML-automated microfluidic circuit design.

ABSTRACT: Microfluidics enable high-precision and cost-effective processing of biological and chemical substances. However, designing and fabricating microfluidic chips typically requires substantial expertise and numerous design iterations, posing considerable barriers to entry for nonexperts. We introduce μFluidicGenius (μFG), an open-access, machine learning (ML)-augmented design tool that enables nonexpert users to rapidly create functional microfluidic circuits. Users simply define the spatial placement of reservoirs, specify the channel connections between them, and assign desired flow rates through this layout. Leveraging a hybrid algorithmic framework that integrates ML models with mathematical modeling, μFG automatically generates spatially coded maze structures that implement the precise f

SUBMITTER: Birtek MT 

PROVIDER: S-EPMC12851026 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature