No abstract

Non-specific adsorption (NSA) is a persistent problem that negatively affects biosensors, decreasing sensitivity, specificity, and reproducibility. Passive and active removal methods exist to remedy this issue, by coating the surface or generating surface forces to shear away weakly adhered biomolecules, respectively. However, many surface coatings are not compatible or effective for sensing, and thus active removal methods have been developed to combat this phenomenon. This review aims to provide an overview of methods of NSA reduction in biosensing, focusing on the shift from passive methods to active methods in the past decade. Attention is focused on protein NSA, due to their common use in biosensing for biomarker diagnostics. To our knowledge, this is the first review to comprehensively discuss active NSA removal methods. Lastly, the challenges and future perspectives of NSA reduction in biosensing are discussed.

a b s t r a c tModeling and simulation of atomization is challenging due to the existence of a wide range of length scales. This multiscale nature of atomization introduces a fundamental challenge to numerical simulation. A pathway to comprehensive modeling is still to be found. The present study proposes a multiscale multiphase flow model for atomization simulations, where the large-scale interfaces are resolved by the Volume-of-Fluid (VOF) method and the small droplets by the Lagrangian point-particle (LPP) model. Particular attention is focused on the momentum coupling between LPP and resolved flow and the conversion between droplets represented by VOF and LPP. A series of multiphase flow problems are considered to validate the model. The results obtained by a number of simulations are compared against direct numerical simulation (DNS) results and experimental data. In particular, the model is applied to simulate the gas-assisted atomization experiment, and the numerical results are compared to the experimental measurements for a quantitative validation.