Geometry-free prediction of inertial lift forces in microfluidic devices using deep learning

This paper presents a novel deep learning approach for geometry-free prediction of inertial lift forces in microfluidic devices, eliminating explicit geometric parameters. The trained neural network model generalizes to unseen channel geometries while performing comparably to existing models.