Model-Guided Design of Paper Membrane Architectures for Controlled Flow and Enhanced Diagnostic Sensitivity

Lateral flow assays (LFAs) rely on capillary-driven transport through porous paper membranes, yet their sensitivity is often limited by poorly controlled flow dynamics within these materials. While geometric and structural membrane modifications have been shown to improve assay performance, such strategies are typically selected empirically due to the difficulty of quantitatively modeling flow in heterogeneous porous substrates. Here, we introduce a model-guided framework for the rational design of paper membrane architectures in LFAs. A numerical flow model, parameterized using two reference experiments, enables quantitative extraction of key membrane properties and prediction of transport behavior under architectural modification. Using this approach, we demonstrate that targeted geometric and structural changes to paper membranes provide precise control over liquid front velocity and antigen–antibody interaction time, resulting in enhanced diagnostic signal. Specifically, selected designs reduce flow velocity by up to 61% and increase signal intensity by up to 33%. By establishing a predictive link between membrane architecture, flow dynamics, and assay sensitivity, this work advances engineered paper membranes as tunable materials for high-performance lateral flow diagnostics.