Predicting Cell Adhesion States on Nanopillar Arrays with a Nano‐Bio Interface Model: From Modeling to Functional Device Design

Nanopillar arrays (NAs) are widely employed as versatile nanostructures for biological applications. Cells on NAs adopt three adhesion states—“top”, “middle”, and “bottom”—each corresponding to distinct biological functions. Although these adhesion states are influenced by NAs geometry, existing models overlook the role of the membrane reservoir—an intrinsic cellular property—in regulating membrane tension during cell settling, resulting in an incomplete mechanistic understanding and limited predictive capability. In this work, a reservoir‐guided nano‐bio interface (RG‐NBI) model is introduced to quantitatively describe the adhesion process and the resulting adhesion states of cells on NAs. An automated design platform, NAs Designer, is developed to predict adhesion states based solely on geometric parameters, achieving 97.22% accuracy across 36 experimental cases. Nanopillar microelectrode arrays (NMEAs) with optimized geometries are fabricated, exhibiting enlarged effective electrode surface area and enhanced cell adhesion. The adhesion states of cells on NMEAs directly influence sensing performance: the “top” state supports highly sensitive electrochemical detection (353.86 nA/µM/mm 2 ), whereas the “bottom” state enables high‐signal‐to‐noise electrophysiological recordings (7.97). These NMEAs allow precise monitoring of dopamine release from dopaminergic neurons and choline consumption by glioblastoma cells. Overall, this integrated approach provides a coherent foundation for nanostructure‐mediated cell regulation and the engineering of advanced nano‐bio interfaces.