Neural Network-Based Optimization of an Acousto Microfluidic System for Submicron Bioparticle Separation.

ABSTRACT: The advancement in microfluidics has provided an excellent opportunity for shifting from conventional sub-micron-sized isolation and purification methods to more robust and cost-effective lab-on-chip platforms. The acoustic-driven separation approach applies differential forces acting on target particles, guiding them towards different paths in a label-free and biocompatible manner. The main challenges in designing the acoustofluidic-based isolation platforms are minimizing the reflected radio frequency signal power to achieve the highest acoustic radiation force acting on micro/nano-sized particles and tuning the bandwidth of the acoustic resonator in an acceptable range for efficient size-based binning of particles. Due to the complexity of the physics involved in acoustic-based separati

SUBMITTER: Talebjedi B 

PROVIDER: S-EPMC9061962 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature