Physics-guided surrogate modeling for machine learning-driven DLD design optimization

Digital Discovery 2026 Open access

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Authors: Khayrul Islam, Mehedi Hasan, Yaling Liu
DOI: 10.1039/d6dd00051g
Cited by: 0

Abstract

A physics-guided machine-learning pipeline converts a measured cell deformation index into fabrication-ready DLD pillar geometries in under a minute, replacing weeks of microfluidic trial-and-error with an open web tool.

Fields of Study & Subjects

Cellular Mechanics and Interactions Advanced Materials and Mechanics Micro and Nano Robotics

Publication details

Journal / source
Digital Discovery
Volume
5
Issue
9
Pages
3883–3903
Publication date
1 January 2026
Language
EN