Biomicrofluidics最新文献

Microfluidic systems capable of generating uniform droplets are gaining attention in food, cosmetics, biochemical, and materials applications. While conventional shear- or interfacial tension-driven nozzle devices can generate highly monodisperse droplets (CV < 5%), their scalability is limited by complex flow designs and clogging. Post-array devices have recently emerged as a high-throughput alternative, producing quasi-monodisperse droplets (CV > 12%) by sequentially breaking larger droplets using micro-post structures. These devices offer shear-dependent tunability of droplet sizes, greater resistance to clogging, and scalability. Notably, droplet size is strongly influenced by the dispersed phase fraction, enabling potential decoupling of droplet size and dispersed phase fraction. This study reviews the principles and performance of post-array devices, compares them with other droplet generation methods, and examines their similarities to droplet splitting in T-junctions and premix membrane emulsification. Challenges such as improving droplet uniformity and miniaturization are also discussed to highlight the potential of post-array systems for practical emulsification applications.

Particle-wall interaction is important in various applications such as cell sorting, particle separation, the entire class of hydrodynamic filtration and its derivatives, etc. Yet, accurate implementation of interactions between the wall and finite-size particles is not trivial when working with the currently available particle tracking algorithms/packages as they typically work with point-wise particles. Herein, we report a particle tracking algorithm that takes into account interactions between particles of finite size and nearby solid objects. A particle is modeled as a set of circumferential points. While fluid-particle interactions are captured during the track of particle center, interactions between particles and nearby solid objects are modeled explicitly by examining circumferential points and applying a reflection scheme as needed to ensure impenetrability of solid objects. We also report a modified variant of auxiliary structured grid method to locate hosting cells, which in conjunction with a boundary condition scheme enables the capture of interactions between particles and solid objects. As a proof-of-concept, we numerically and experimentally study the particles' motion within a deterministic lateral displacement microfluidic device. The results successfully demonstrate the zigzag and bump modes observed in our experiments. We also study a microfluidic device with pinched flow numerically and validate our results against experimental data from the literature. By demonstrating an almost 8 $\times$ speedup on a system with eight performance threads, our investigations suggest that the algorithm can benefit from parallel processing on multi-thread systems. We believe that the proposed framework can pave the way for designing related microfluidic chips precisely and conveniently.

Manipulation of red blood cells (RBCs) in microscale has proven to play a pivotal role in various applications, such as disease diagnosis and drug delivery. Over the past decades, the capabilities of microscale manipulation techniques have evolved from simple particle manipulation to cells and organisms, with numerous microfluidic-based research tools being developed for RBC manipulation. This review first introduces the reported microscale manipulation techniques and their principles, including passive microfluidic methods based on microstructures and hydrodynamics, as well as active methods such as acoustic, optical, and electrical techniques. It then focuses on the application scenarios of these micro-scale manipulation methods for RBC manipulation, including the investigation of RBC mechanical properties, the preparation of RBC carriers, the control of RBC rotation, and RBC lysis. Finally, the future prospects of microscale techniques in RBC manipulation are discussed. This review offers a comprehensive comparison of various techniques, aiming to provide researchers from different fields with a broad perspective and to guide the continued development of microscale manipulation methods for RBC applications. It seeks to help researchers from diverse backgrounds stay informed about the latest trends and advancements in the field.

Deterministic lateral displacement (DLD) is a popular technique for the size-based separation of particles. A key challenge in the design of DLD chips is to eliminate the fluid flow disturbance caused by channel sidewalls intersecting with pillar matrix. While there are numerous reports attempting to mitigate this issue by adjusting the gaps between pillars on the sidewalls and the closest ones residing on the bulk grid of DLD, there are only a few works that also configure the axial gap of pillars adjacent to the accumulation sidewall. Herein, we study various designs numerically to investigate the effects of geometrical configurations of sidewalls on the critical diameter and first stream flux fraction variations across the channel. Our results show that regardless of the model used for the boundary gap profile, applying a pressure balance scheme can improve the separation performance by reducing the critical diameter variations. In particular, we found that for a given boundary gap distribution, there can be two desired parameter sets with relatively low critical diameter variations. One is related to sufficiently low lateral resistance of interface unit cells next to the accumulation sidewall, while the other one emerges by reducing the axial resistance of the interface unit cells to an appropriate extent. This work should pave the way for designing DLD systems with improved performance, which can be critically important for applications such as the separation of rare cells, among others, wherein target species need to be concentrated into as narrow a stream as possible downstream of the device to enhance purity and the recovery rate simultaneously.

Silicon-based microfluidics enable the creation of highly complex, three-dimensional fluid networks. These comprise scalable channel sizes and monolithically integrated functionalities available from complementary-metal-oxide-semiconductor technology. On this versatile, solid-state platform, advanced manufacturing techniques exist that allow the channel walls to be directly electrified with one or multiple pairs of electrodes along the fluid-carrying channel. The electrodes have ideal electrostatic geometries, yielding homogeneous electric field distributions across the entire cross section of the microfluidic channel. As these are located directly at the channel, only low supply voltages are needed to achieve suitable field strengths. Furthermore, a controlled supply of charge carriers to the microfluidic channel is feasible. These configurations may serve numerous applications, including highly efficient mechanisms to manipulate droplets, cells, and molecular compounds, perform pico-injection or poration, trigger and control chemical reactions, or realize electrochemical and capacitive sensing modalities. In this perspective, we describe the generic design and fabrication of these electrodes and discuss their miniaturization and scaling properties. Furthermore, we forecast novel use cases and discuss challenges in the context of the most interesting applications.

Recent advances in microfluidic technology have shown the importance of precise temperature control in a wide range of biological applications. This perspective review presents a comprehensive overview of state-of-the-art microfluidic platforms that utilize thermal modulation for various applications, such as rapid nucleic acid amplification, targeted hyperthermia for cancer therapy, and efficient cellular lysis. We detail various heating mechanisms-including nanoparticle-driven induction, photothermal conversion, and electrothermal approaches (both external and on-chip)-and discuss how they are integrated within lab-on-a-chip systems. In parallel, advanced multi-modal sensing methods within microfluidics, ranging from conventional integrated sensors to cutting-edge quantum-based techniques using nanodiamond nitrogen-vacancy centers and suspended microchannel resonators, are highlighted. By integrating advanced multi-modal sensing capabilities into these microfluidic platforms, a broader range of applications are enabled, including single-cell analysis, metabolic profiling, and scalable diagnostics. Looking ahead, overcoming challenges in system integration, scalability, and cost-effectiveness will be essential to harnessing their full potential. Future developments in this field are expected to drive the evolution of lab-on-a-chip technologies, ultimately enabling breakthroughs in precision medicine and high-throughput biomedical applications.

Remote health monitoring has the potential to enable individuals to take control of their own health and well-being and to facilitate a transition toward preventative and personalized healthcare. Sweat can be sampled non-invasively and contains a wealth of information about the metabolic state of an individual, making it an excellent candidate for remote health monitoring. An accurate, rapid, and low-cost biofluid characterization technique is required to enable the widespread use of remote health monitoring. We previously introduced microfluidic impedance spectroscopy for the detection of electrolyte concentration in fluids, whereby a novel device architecture, measurement method, and analysis technique were presented for the characterization of cationic species. The purely electrical nature of this measurement technique removes the intermediate steps inherent in common rival technologies such as optical and electrochemical sensing, offering a range of advantages. In this work, we investigate the effect of temperature on microfluidic impedance spectroscopy of ionic species commonly present in biofluids. We find that the impedance spectra and concentration determination are temperature-dependent; remote health monitoring devices must be calibrated appropriately as they are likely to experience temperature fluctuations. Importantly, we demonstrate the ability of the method to measure the concentration of anionic species alongside that of cationic species, enabling the detection of chloride and lactate, which are useful biomarkers for hydration, cystic fibrosis, fatigue, sepsis, and hypoperfusion. We show that the presence of neutral species does not impair accurate determination of ionic concentration, thus, demonstrating the suitability of microfluidic impedance spectroscopy for non-invasive biofluid characterization.

Acoustic holography offers the ability to generate designed acoustic fields, enhancing the versatility of acoustic micromanipulation. However, the quality of the generated holograms depends on the nature of the iterative algorithm that is utilized, where the iterative angular spectrum approach (IASA) has been the standard method to date. Here, we introduce a novel approach that categorically improves IASA performance, where we apply the principles of simulated annealing for the generation of high-quality acoustic holograms. We utilize this to realize significant improvements in hologram quality via simulations, fabricated holograms, experimental particle patterning, and high-resolution 2D hydrophone scans. Comparing holograms produced from IASA and/or simulated annealing, we demonstrate that the use of simulated annealing in acoustic holography results in sharper reconstructions and improved hologram outputs across a range of evaluation metrics.

Thanks to their softness, biocompatibility, porosity, and ready availability, hydrogels are commonly used in microfluidic assays and organ-on-chip devices as a matrix for cells. They not only provide a supporting scaffold for the differentiating cells and the developing organoids, but also serve as the medium for transmitting oxygen, nutrients, various chemical factors, and mechanical stimuli to the cells. From a bioengineering viewpoint, the transmission of forces from fluid perfusion to the cells through the hydrogel is critical to the proper function and development of the cell colony. In this paper, we develop a poroelastic model to represent the fluid flow through a hydrogel containing a biological cell modeled as a hyperelastic inclusion. In geometries representing shear and normal flows that occur frequently in microfluidic experiments, we use finite-element simulations to examine how the perfusion engenders interstitial flow in the gel and displaces and deforms the embedded cell. The results show that pressure is the most important stress component in moving and deforming the cell, and the model predicts the velocity in the gel and stress transmitted to the cell that is comparable to in vitro and in vivo data. This work provides a computational tool to design the geometry and flow conditions to achieve optimal flow and stress fields inside the hydrogels and around the cell.

Despite the widespread application of microfluidic chips in research fields, such as cell biology, molecular biology, chemistry, and life sciences, the process of designing new chips for specific applications remains complex and time-consuming, often relying on experts. To accelerate the development of high-performance and high-throughput microfluidic chips, this paper proposes an automated Deterministic Lateral Displacement (DLD) chip design algorithm based on reinforcement learning. The design algorithm proposed in this paper treats the throughput and sorting efficiency of DLD chips as key optimization objectives, achieving multi-objective optimization. The algorithm integrates existing research results from our team, enabling rapid evaluation and scoring of DLD chip design parameters. Using this comprehensive performance evaluation system and deep Q-network technology, our algorithm can balance optimal separation efficiency and high throughput in the automated design process of DLD chips. Additionally, the quick execution capability of this algorithm effectively guides engineers in developing high-performance and high-throughput chips during the design phase.