Publication Date: 2025
Journal of Chromatography A (00219673)1757
Microfluidic lab-on-a-chip technologies are revolutionizing diagnostic processes by enabling High-purity particle separation in heterogeneous mixtures, like blood, crucial for swift and accurate diagnoses, particularly in common diseases like cancer or infections where effective pathogen isolation is required. Passive deterministic lateral displacement (DLD) and active acoustophoresis are prominent microfluidic separation methods, each with distinct advantages and limitations. A hybrid approach, combining both, allows simultaneous utilization of their benefits, and enhances separation efficiency and purity through optimal design. A groundbreaking versatile 3D finite element (FE) model of an innovative-designed hybrid microfluidic device, featuring I-shaped DLD arrays and acoustofluidic module based on tilted-angle standing surface acoustic wave (TaSSAW) with focused interdigital transducers (FIDTs), has been presented, accurately predicting particles' behavior and separation dynamics. Simulations of individual devices were also conducted to optimize hybrid device performance, revealing high-efficiency and high-purity separation of polystyrene particles and bioparticles, including circulating tumor cells (MCF-7 CTCs), RBCs, and Escherichia coli bacteria. In the optimized acoustofluidic device, 15 µm polystyrene particles were separated with 100 % purity and 94 % efficiency, while MCF-7 CTCs were separated with 100 % purity and 98 % efficiency. The optimized DLD device achieved 100 % purity and efficiency for 2 µm and 8 µm polystyrene particles, RBCs, and bacteria. In the hybrid device, due to unpredictable factors, MCF-7 CTCs were isolated with 100 % purity but 40 % efficiency, while RBCs and bacteria maintained 100 % purity and efficiency. The results highlight the potential for further geometrical and fluidic optimizations to improve performance, with the 3D model providing a superior predictive tool compared to 2D models, facilitating cost-effective modeling of complex lab-on-a-chip structures. © 2025 Elsevier B.V.
