Numerical framework for simulating bio-species transport in microfluidic channels with application to antibody biosensors

Computational Fluid-Structure Interaction in Microfluidics

Micro elastofluidics is a transformative branch of microfluidics, leveraging the fluid-structure interaction (FSI) at the microscale to enhance the functionality and efficiency of various microdevices. This review paper elucidates the critical role of advanced computational FSI methods in the field of micro elastofluidics. By focusing on the interplay between fluid mechanics and structural responses, these computational methods facilitate the intricate design and optimisation of microdevices such as microvalves, micropumps, and micromixers, which rely on the precise control of fluidic and structural dynamics. In addition, these computational tools extend to the development of biomedical devices, enabling precise particle manipulation and enhancing therapeutic outcomes in cardiovascular applications. Furthermore, this paper addresses the current challenges in computational FSI and highlights the necessity for further development of tools to tackle complex, time-dependent models under microfluidic environments and varying conditions. Our review highlights the expanding potential of FSI in micro elastofluidics, offering a roadmap for future research and development in this promising area.

A Molecular Dynamics Model for Biomedical Sensor Evaluation: Nanoscale Numerical Simulation of an Aluminum-Based Biosensor

Metallic nanostructured-based biosensors provide label-free, multiplexed, and real-time detections of chemical and biological targets. Aluminum-based biosensors are favored in this category, due to their enhanced stability and profitability. Despite the recent advances in nanotechnology and the significant improvement in development of these biosensors, some deficiencies restrict their utilization. Hence a detailed insight into their behavior in different conditions would be crucial, which can be achieved with nanoscale numerical simulation. With this aim, an Aluminum-based biosensor is chosen to be analyzed with the help of all-atom molecular dynamics model (AA-MD), using large-scale atomic/molecular massively parallel simulator (LAMMPS). The surface properties and adsorption process through different flow conditions and various concentration of the target, are investigated in this study. In the future work, the results of this study will be used for developing a predictive model for surface properties of the biosensor. Clinical Relevance- The role of biosensors in clinical applications and early diagnosis is evident. This work provides a model for predicting the binding behavior of the target molecules on the biosensor surface in different conditions. Results demonstrate an increase in the adsorption of ethanol on the biosensor surface of 7% up to 80% with changing the velocity from 0.001 m/s to 1 m/s Although for cases with higher concentration this trend becomes complicated necessitating the implementation of machine learning models in the future works.

How molecular interactions tune the characteristic time of nanocomposite colloidal sensors

HYPOTHESIS

Mass transport critically controls the performance of colloidal metal-polymer sensors. We hypothesize that molecular-level pair interactions, such as electric, steric, and specific binding effects, govern the mass transport and, in return, the characteristic time of these sensors.

THEORY

Here we present a simple theory guided by experimental data to examine the sensing performance of two usually encountered archetypal metal-polymer sensors, namely (1) core-shell and (2) yolk-shell architectures. For this purpose, we use the static reactive density functional theory framework, determining how (i) charge, (ii) size, and (iii) non-covalent binding factors modulate the characteristic time.

FINDINGS

We show how an interplay between diffusivity and partitioning governs the sensing time of the sensors, where an anti-correlation cancellation between them renders the time non-trivial. Our study demonstrates that the convoluted substrate-hydrogel shell interaction controls the characteristic time of these colloidal sensors, especially when the sensors are in a collapsed state. Notably, the substrates with a high dipole moment tend to equilibrate greatly, but undesirably, at the shell-solution interface. With this, we encourage the formation of a metastable sorption state.