Background
Type:

Tunable acoustic streaming-driven micropump for integration into lab-on-chip platforms for biomedical assays

Journal: Expert Systems with Applications (09574174)Year: 1 February 2026Volume: 297Issue:
DOI:10.1016/j.eswa.2025.129491Language: English

Abstract

An integrated pumping module is a crucial component in lab-on-a-chip (LOC) and organ-on-a-chip (OoC) devices, as it enables fluid transport and control for biomedical assays. In this study, an acoustomicrofluidic pump is proposed as a compact and integrable solution compatible with LOC platforms. The reference structure of the micropump is initially parameterized, and a design is established based on two primary variables: the inclination angle of the sharp-edge structures and the applied peak-to-peak voltage. Merits of performance were considered to be pumping rate and Maximum shear stress, latter of which is proposed as an objective function to assess acoustic micropump bio-compatibility. To analyze the functional behavior of the system, a surrogate model is constructed using a face-centered central composite design (CCD), enabling predictive assessment of the objective functions under different design configurations. It is demonstrated that by decreasing the inclination angle from its maximum to minimum value, the pumping rate increases by more than 79%, and maximum shear stress is decreased by more than 95%. Surrogate predictive model is then utilized within a Particle Swarm Optimization (PSO) algorithm to identify optimal design parameters. The resulting optimized designs exhibit an enhancement in system efficiency more than 68% compared to the reference configuration. This modeling and optimization methodology enables effective tuning of the acoustomicrofluidic pump's performance for adapting the system to application-specific requirements. Potential biomedical uses of the optimized device include on-chip cell lysis and biofilm analysis, along with bio-nanoparticle synthesis, where controlled and efficient microfluidic pumping is essential. © 2025 Elsevier Ltd