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Review

A Review on the Role of Microflow Parameter Measurements for Microfluidics Applications

by
Sreedevi Lingadahalli Kotreshappa
,
Chempi Gurudas Nayak
and
Santhosh Krishnan Venkata
*
Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India
*
Author to whom correspondence should be addressed.
Systems 2023, 11(3), 113; https://doi.org/10.3390/systems11030113
Submission received: 12 January 2023 / Revised: 10 February 2023 / Accepted: 16 February 2023 / Published: 21 February 2023

Abstract

:
Microfluidics has risen to a new zone of exploration because of its application in numerous fields. The integration of microfluidics and sensor technology bridges gaps in heat transfer areas, the medical field, and the chemical industry at the microscale flow level. This paper reviews the latest work conducted in microfluidics with the help of microflow parameter measurements in microfluidic applications, microflow sensor inventions, novel microflow pathway design, and an assessment of the keyway of fluid behavior in microchannels. The emphasis is on highlighting a significant part of recent research on developing microfluidics applications using the previously explored microflow characteristic measurements. The details of heat transfer, blending, and sorting, along with different medical applications, including drug delivery, inferred that heat transfer is the most explored application domain. Comparing newly evolving microflow sensors will make the sensor selection easy for the user’s required microflow conditions. The effects of microchannel geometry and channel wall parameters on different microflow characteristic measurements are identified. This study will enhance the understanding of the performance of microflow systems by providing new flexibility in microfluidics. The study of microflow parameter measurements is reviewed in more depth, making its way for future microfluidic application developments.

1. Introduction

Many technologies require fluid flow computations in structuring the natural world and industrial scheme processes and activities [1]. The microfluidic innovation revolution offers a developing arrangement of tools for controlling small volumes of fluids in pathways with measurements of several micrometers [2,3,4]. Microfluidics started evolving with the microelectronics industry, with the first microfluidic device being developed in the 1970s [5,6]. Today, the field has risen to a new zone of exploration because of its application in numerous fields [7]. The microfluidics market was estimated at around USD 4632 million in 2020, and it is relied upon to arrive at USD 9538 million by 2026, enrolling a compound annual growth rate of almost 12.95% during the estimated time frame, 2021–2026. Microfluidics is an interdisciplinary research subject that provides precise liquid control and manipulation, empowering quick and high throughput test handling incorporated into small-size clinical frameworks.
Microfluidic components have been consolidated in various commercial instruments for bioanalysis [8]. These systems provide “point-of-care” analysis to the clinician [6,9]. Moreover, hence, including Lab-on-a-chip (LOC) and Organs on Chips (OOC) [10,11], this technology is giving rise to many new applications every day. Many of the fluids flow in the human body in the microscale environment. This fluid flow becomes disturbed under unusual health conditions of the human body when the flow rate, density, viscosity, temperature, pressure, or any other parameters of these fluids change. Moreover, this may, in turn, make related health conditions critical. Microfluidics technology is used to study these body fluid flows and treat the malfunctions and diseases related to the same. Microfluidics also extends its work to building artificial human organs that mimic any of the human body’s microenvironment systems. In all the said applications, keeping a check on the microfluid flow parameter measurements such as flow rate, density, viscosity, temperature, pressure, etc., during the process becomes crucial.
Moreover, all these advancements in microfluidics are possible only through the inventions and upgradation of sensors that could be used to sense and measure the microfluidic flow variables [12]. Alternatively, we could say that the microfluidics area is advancing mainly due to sensor technology. Another age of sensors and actuators for microfluidic control applications is becoming a reality. These new sensing components show further enhanced capabilities and functionalities [13,14]. The main thrust behind scaling down was the improved performance that could be acquired by down scaling analytical frameworks and the chance to coordinate many components inside a solitary device. The integration of microfluidics and sensor components is a booming area of research as it gives way to quick, proficient, and automated ways of analysis of any flow frameworks as compared to before. This lets us manipulate microflow volumes’ chemical, biological, and physical characteristics that apply to sensing, hence commanding the systems in those areas. The ongoing use of Computational Fluid Dynamics (CFD) simulations provides a compelling way to deal with different consequences for liquid streams without carrying out complicated experiments in microfluidics [15].
Hence, in all the above applications of microfluidics stated, the role of sensors is very crucial. So, it will be of great importance to see where this combination of microfluidic and sensor fields is today. Though many microflow properties have been explored to date, the usage of the same information should be put into understanding various microflow systems and the different applications that are being developed around these microflow properties. At the same time, many sensors are invented daily to sense microflow parameters, but selecting the suitable sensor for different microflow environment demands is still challenging. Microchannel geometry, wall parameters, and working fluids become essential aspects of the microflow environment. At the microscale level, the resulting laminar fluid flow undergoes a lot of fluid flow characteristic variations concerning the channel geometry of the channel through which the fluid is flowing. Microchannel geometry has shown its influence on the microflow parameter measurements. Hence, it becomes vital to study the effects of microchannel geometry, either to understand the existing microflow environments or to build any microflow environment in the future. Though the basic properties of microflows are already known, even then, these relationships vary over different microenvironments, and flow properties have a combined influence on one another. Moreover, this influence also changes for different kinds of flows, different flow parameter ranges, and micro pathway structures. Understanding such microflow parameters influences the choice of suitable microflow sensors; both together play a significant role in knowing the flow physics of natural living microsystems and in developing new applications in the microfluidic field.

1.1. Motivation

Microfluidics offers its application in biotechnological, clinical, and chemical synthesis fields [7], which was impossible from traditional methods. Additionally, studying microflow systems allows one to analyze bodily fluid flow at the micro level. Flow-related equipment can be made handier and the related process less tedious using microscale flow systems. Following the same, this review summarizes the most recent applications of microfluidics, highlighting its contribution to the medical field. Though many microflow sensors have been invented, selecting appropriate fluid flow sensors is still challenging. Work here helps in sensor selection along with stating the certainty in measurements. The microchannel geometry effects on microflow parameter measurements are noted. Though a lot of research work has been conducted on fluid flows, microfluidics has still not been entirely explored by researchers. Hence, it becomes essential to study different explored microflow characteristics in still more depth, and this paper reviews the same.
The dynamic role of sensor related microfluidic system applications in various essential aspects of day-to-day life serves as an incitement for the carried-out work.

1.2. Paper Organization

This paper is coordinated as follows. Section 2 in the paper accumulates the recently developed applications on microflows parameter measurements. It outlines the comparison between different sensors invented for measuring microflows. It helps us to understand the effect of microchannel geometry measurements and microchannel wall parameters on different microflow characteristic measurements. After covering the work conducted on various microflow characteristics in a nonporous medium, the section then focuses on the work conducted in the porous medium. A brief study on an orifice-type microflow meter is taken as a case study in Section 3 to realize the details of the presented review. Section 4 concludes the latest overall work conducted in the microfluidics field and sheds light on the research work that could be addressed soon.

2. Background

2.1. Inclusion/Exclusion Criteria

Inclusion criteria are characterized as the vital elements of the target population chosen for the investigation. Exclusion criteria are the elements that would disqualify a study from being included in the investigation. Inclusion/exclusion criteria are essential to favor future research investigators by decreasing the possibility of an unfavorable outcome. The inclusion/exclusion criteria considered when carrying out the investigations on microfluidic flows are listed below.

2.1.1. Inclusion

  • Year of research article considered in this study is 2016–2021;
  • The focus of this study is on microflow parameter measurements;
  • Types of flows explored for flow measurements are laminar flow, turbulent flow, homogeneous flow, steady flow, pulsating flow, and backflows;
  • Types of microfluids used in this study are Newtonian fluids, non-Newtonian fluids, incompressible fluids, and viscoelastic fluids;
  • Refrigerants and other fluids are part of this study;
  • Single phase and multi-phase flows were studied. Two-phase flows included in the study are liquid–liquid and liquid–gas phases;
  • The study in the mentioned period focused on normal fluid flows, droplet flows, continuous resign flows, pulsatile flows, segmented flows, slip-transition flows, plug flows, froth flows, slug flows, minimal slug flows, Taylor flows, slug annular flows, annular flows, smooth annular flows, translation flows, slip flows, curving of party lines and protrusion-contract-squeeze-release stages of bubble flows;
  • Porous and nonporous mediums are part of this study;
  • Heat sinks, Polydimethylsiloxane (PDMS) wall membrane microchannel, micro pump, single-channel, pin-fin microchannel, a narrow channel that imitates blood vessels, aged copper microchannel, circular tube, a channel that mimics artery, aluminum wall microchannel, quartz microchannel, T-type bifurcations with four branches, parallel microchannels, and microtubes are different micro pathways of microflows;
  • Boundary conditions considered for fluid flow measurements at the micro level are kinetic boundary schemes, analytical solutions of Navier stroke equation, vorticity stream boundary formulation, electro magneto hydrodynamic stream with the no-slip limit condition, grid Boltzmann technique, two asymmetric boundaries, and local thermal nonequilibrium environment, 3D hydrodynamic environment, homogeneous flow model, separated flow model, lattice Boltzmann model, 2D flow model, 3D flow model, Lee interfacial face change model and environment flow models such as constant heat-thermal boundary condition;
  • Fluid–structure interaction, adiabatic systems, diabetic systems, microparticle image velocimetry, exothermic reactions and endothermic reactions were analyzed in the review;
  • Microflow parameter measurements formed inputs and outputs for considered microfluidic systems;
  • Micro flow parameters considered for measurement are flow rate, pressure drop, velocity, viscosity, speed, temperature, thermal property, thermal resistance, heat flux, heat capacity, mass velocity, heat transfer, liquid refraction index, wall shear stress, rheological parameters, fluid wall temperature distribution axial heat conduction, vorticity, Lorentz force, viscous drag, electric field, entrainment friction, void fraction, slip ratio, liquid entrainment fraction, hydraulic diameters, pulsating frequencies, mass fraction, mass flux flow morphologies, bypass ratio, shear-thinning, vapor quality, volume flux, relative permeability, cell acceleration, radio frequency electromagnetic field, relative permittivity, electrical conductivity, axial velocity, adhesion rate, mass flux, share rate, hydrodynamics, Mas exchange, cell volume, phase distribution, volume, mass transfer, volume fraction, medication permeability, magnetic field, volumetric flow rate, electric field force, particle radius, mass, magnetic field, viscoelastic property, lift force, flow ratio, viscosity ratio, and volumetric flow-rate ratio. Different correlations on pressure drop and entertainment factors were also identified;
  • Various softwares were used to compute microfluid flows, namely, Fast Fourier Transform algorithms were implemented using MATLAB software to measure and plot microflow parameters. Simulations for microflow were carried out using computational fluid dynamics, and environments were mimicked using COMSOL and ANSYS FLUENT;
  • Micro flow-rate sensors and microflow temperature sensors are considered for sensing;
  • Sensors included in study are stream rate sensor for drug-infusion with range (0.1–100) mL/h and certainty >~95%, droplet flow-rate sensor with range (10–650) μL/min, thermal flow sensor with range (1–10) kS/s, calibration-free microflow sensor, passive microflow sensors with range (1000–7000) μL/min, molecule-based temperature sensors with range (0.66–10.6) mm/s, fiber flow-rate sensors with range 0–0.020 nm/(μL/min), calorimetric on-chip Ni thermal flow sensor where thermal bubble sensor employing thermal conductivity with detection range (0–200) μL·min−1 with an accuracy of 30 nL min−1 are the different sensors designed to sense microflow-rate temperature;
  • Shapes including circular, square, triangular, rectangular, cylindrical, and serpentine microchannel designs are covered in study;
  • The Nusselt number, Reynold’s number, Poiseuille number, Knudsen number, Dean number, and Capillary number are dimensionless numbers that showed influence on microflows;
  • Heat transfer coefficient, fractional coefficient, compliance parameter, pressure flow controlling compliance variable, volumetric mass exchange coefficient, design variable, tangential momentum convenience coefficient, pulsating pressure gradient, and different design variables were analyzed in this study;
  • Different microflow applications exploit different properties of fluid flows at the micro level, and such applications include flow boiling applications, microfluidic chip designs, refrigeration, particle focusing, particle separating, particle sorting, particle manipulation, label-free DNA, biosensors, microfluidic structure, microfluidic chips, nanopore technology, point of site detection, biological research, environmental monitoring, biosensing approaches, quick blending/mixing, cell culture application, drug delivery, platelet adhesion, and convective boiling applications;
  • Worldwide research is considered for the present study.
For the past few years, throughout the world, microflow variables have been sensed in different fluid flows through non-identical micro pathways in various microfluidic systems.

2.1.2. Exclusion

  • LOC structures designs and OOC designs are not considered for the study;
  • Microchannel fabrication, LOC structures fabrication and OOC fabrications are excluded from the study;
  • Innovation of constituents that are used to embed practically complex microfluidic frameworks are not included in the present study;
  • Material science is not a focus of the present study;
  • Microflow actuation is not considered for microflows in this study;
  • Electrical charges of fluids are not analyzed in this study;
  • Microfilters, micro pumps, micromixers, microvalves, and micromotors are not covered in this study;
  • Chemical reactions of fluids are neglected in this study;
  • Communication between microflow sensors and other parts in the microflow systems are excluded in this study;
  • Microflow system-related circuit designs are not highlighted in the presented work;
  • Cost of microchannels, cost of microflow systems, cost of LOC, and cost of OOC are excluded from this study.

2.2. Objective of the Work

A literature study is carried out in the microfluidic field to study the microfluid flow characteristics and sensing microflow parameters, especially for the developing applications in microfluidics by using the previously explored microflow characteristic measurements and to analyze/compare the sensors invented for measuring microfluidic flows. Additionally, we identified the effect of microchannel geometry and channel wall parameters on different microflow characteristic measurements. Additionally, for the study of microflow parameter measurements, more depth is still considered. Following the same, the presented paper reviews the latest work conducted in microfluidics concerning microflow parameter measurements to check the present status of research and to find the research gaps.

3. Discussion on Microfluidics

3.1. Applications of Microflows

Heat transfer and microflow manipulations are the major zones that microfluidic research work has been revolving around for the past few years. In addition, the research interest in the medical field has become the center of attention, as the combination of both microfluidics and related sensed flow measurements is highly facilitating clinical analysis and their potential to become a solution to the most complex medical conditions. An insight into the same follows below.

3.1.1. Heat Transfer Applications

Heat transfer is the trading of heat between physical frameworks. At the microscale, heat transfer measurements in both single-phase [16] and two-phase [17] flows have always been a matter of consideration for industrial manufacturers. Regular applicable areas in microfluidics related to heat transfer measurements are cooling applications [16,18,19,20,21,22,23,24,25,26,27] with the cooling systems needed for refrigerators, air conditioners, and microelectronics [28,29]. Research has been continuously carried out to provide better heat transfer performance to accommodate all these mentioned applications, to make them outstanding in their performance. The plan optimization of micro pin-fin shapes is also in the picture for cooling applications [30].
In the literature, productive work has been conducted in the field of refrigeration. Refrigerant flow is where the fluids are used as coolants, and these coolants are made to flow in micro pathways to collect the heat from around the refrigerator. Various fluids such as FC-72 dielectric fluid [17], R245fa [31], R134a [25,32,33,34,35,36], R32 [31,35], R410A [31], R600a [34], R290 [34], R1270 [34], R1234ze(E) [37] and R410a [38] are employed for the same. The local heat transfer coefficient can be estimated from the local wall temperature and liquid saturation temperature [39]. Different concentrations of graphene oxide particles-water nanofluids impact heat transfer for pin-fin microchannel and pulsating inlet velocity. For different Reynolds numbers (272, 407, and 544) and mass fractions (0.02%, 0.05%, 0.1%, 0.15%, 0.2%), the pulsating flow (pulsatile frequencies (0–5) Hz) has a greater impact on heat transfer at a lesser averaged Reynold’s value [40]. Microscale heat transfer is carried out using different newly fabricated microchannels [41], microchannels with branch spacing [42], heatsinks with multiple channels varying in microchannel dimensions [43], and an Interconnected microchannel Net (IMN) [41]. IMN yielded higher heat transfer than that of the rectangular microchannel. When it comes to mall distribution and instabilities in the parallel channel in a two-phase heat transfer, flow excursion between channels is the main reason for maldistribution, and maldistribution is the reason for a higher level of pressure down in two-phase heat sinks [23,44,45,46,47,48]. Heat transfer coefficient investigations are carried out under extreme operating conditions of heat flux, mass flux, and micro gap [49]. The heat transfer coefficient is strongly dependent on the mass flux [41], heat flux [49], and vapor flume quantity [49]. Heat transfer coefficient varies for both single-phase and two-phase. It also varies for gravitational aspects such as horizontal and vertical [39,50] orientations of microchannels and the direction of flows. Adding ethanol into the water upgraded heat transfer resulting in higher heat transfer coefficients than for either of its pure components [39]. Additionally, the heat transfer coefficient upgrades with an increase in the oblique angle of microchannel fins [17]. The heat transfer coefficient enhancement by applying magnetic quadrupole is decreased with increasing the Reynolds number [51]. Nanofluids flow along by application of magnetic field has come to the picture for enhancement of heat transfer coefficient, and enhancement depends on Reynolds number and magnetic field applied for Fe3O4/water magnetic nanofluid flow in the presence of the quadrupole magnets located at different axial installation positions [52]. Heat transfer coefficients of fluids such as R134a [49], R1234ze(E), R1234yf, and R600a are affected by vapor qualities [53]. The two-phase heat transfer coefficient of the pin-fin micro gap (after accounting for the additional surface area of the fins) is four times greater than the bare microcap under extremely high conditions of heat flux, mass flux, and the confined path of 10 µm [49]. Both microchannel geometry and microflow Reynold’s number will influence the heat transfer measurement [54].
Flow boiling is where the fluid flow is forced over a surface by external means such as pumps and buoyancy effects and is implemented as one of the most promising cooling methods. Flow boiling can be studied by using fluids such as R134a [49,55], and Hożejowska et al. developed a flow boiling heat transfer model based on the Trefftz method for better analyzing the flow boiling in rectangular, vertical, and asymmetrically heated mini channels with varying aspect ratio measurements [56]. Segmented finned channels overtake uniform cross-section microchannels with low response time and magnified heat transfer. The response time is less for inflow boiling (regimes) conditions compared to the single-phase flow of coolant [16]. The effects of applying a magnetic field on the pressure drop and heat transfer of Fe3O4/water magnetic nanofluid (ferrofluid flow) along the length of the tube resulted in maximum enhancements of 23.4%, 37.9%, and 48.9% in the local heat transfer coefficient [51]. Orientation of microchannel [57] and heatsinks [58] was also found to be influencing the flow boiling process. In different flow boiling investigations, the chaotic pressure oscillations flow pattern sequences relied upon the mean worth of the pressure drop [59]. Universal correlations are also created utilizing many data sets and heat transfer anticipating tools for the condensing and stream boiling process in a microchannel for annular stream and the other for slug and bubbly streams [60].
Different windows—W1, W2, W3, W4, W5, W6, W7, W8, W9, and W10—are considered for various ranges of heat flux and mass flux for investigating heat transfer measurements, as highlighted in Figure 1 and Table 1. W1 to W10, shown in Figure 1, is in the increasing order of window sizes, where W1 represents the smallest window and W10 represents the largest window explored in the literature. The W1 window, being the smallest window, is explored for the dynamics and heat transfer characteristics of the flow boiling bubble train using R134a flow, where a nonequilibrium phase change model provides a way to measure the interface temperature and heat flux jump [61]. Heat transfer differs in both horizontal and vertical directions of flow. Window W2 is checked for the measurement of heat transfer in a single 5 mm inner hydraulic diameter square channel in a vertical orientation and provides the heat transfer coefficient measurement with the uncertainty of ±20 in measuring the heat transfer coefficient [39]. In window W3, half-corrugated micro-channels with bottom sinusoidal structured surfaces affected temperature and two-phase heat transfer. Channels with higher wavelength (0.5 mm) and larger wave amplitude (0.3 mm) showed better heat transfer measurement with little pressure drop [62]. Concerning the convective heat transfer coefficient, the newly fabricated interconnected microchannel net (IMN) yielded higher heat transfer than that of the rectangular microchannel for the window W4 [41].
Window W5 is used to investigate the flow boiling of R134a in a 10 µm micro gap to assess its capability to dissipate ultra-high heat fluxes [49]. Other than Window W2, Window W6 is also utilized for the vertical flow orientation with a 1 mm diameter microchannel being aligned in gravitational aspect horizontal, vertical upward, and downward orientation with R-134a. The heat transfer coefficient and pressure drop measurements increased when the refrigerant flowed vertically downward [50]. Segmented finned channels overtake uniform cross-section microchannels with less response time and enhanced heat transfer measurements in window W7 for deionized water flowing through microchannels [16]. The flow of FC-72 with absolute pressure measurement in the range (1.16–1.84) bar flowing through rectangular, vertical, and asymmetrically heated mini channels is explored in window W8 with a high aspect ratio of 40, 20, and 13.3. The heat transfer coefficient correlation using the Trefftz method helps attain a 10.1% Mean Absolute Error (MAE) for flow boiling [56]. Window W9 is explored for the heat transfer coefficient for the flow of R134a, R1234ze(E), R1234yf, and R600a through mass velocity range (200–800) kg/m2 s and vapor qualities range (0.05–0.95) for the temperatures of 31 and 41 C during flow boiling inside a circular microchannel with an internal diameter of 1.1 mm [53]. W10 is the largest window explored in heat flux and mass flux ranges for the flow of FC-72 dielectric fluid through three different microchannel fins oblique angles, such as 10, 30, and 50 [17].

3.1.2. Microflow Manipulation Applications

Microfluidics technology is used in flow manipulation, such as mixing flows [63,64] and sorting particles [65,66,67,68], based on flow parameter measurements at the micro level. Work conducted in these scopes is provided below.
(a)
Mixing/Blending applications
Mixing time, length, throughput, and mixing index/mixing efficiency are the different parameter measurements that were found to influence microfluidic blending for varying microfluidic techniques. Table 2 provides the idea of efficiency parameters achieved for various efficiency boosting parameters, along with highest mixing efficiency achieved and time taken for the same. The pore array tube in a tube microchannel reactor allows intense micromixing performance, high throughput, and optimal micromixing time [69,70]. When studies were carried out for spiral channels, higher aspect ratio measurements showed better mixing, and higher Reynolds numbers showed the least mixing efficiency. Frequent curving of the path lines is additionally recognized to influence blending and prompts a reliance on blending on aspect ratio. The highest mixing efficiency for the spiral microchannel with 25 × 50 × 800 (1,000,000) grid cells is 90.56%. Furthermore, 99.5% is the highest mixing efficiency for the variation of Reynolds number at Re = 140 while mixing uncertainty is ±10% [63]. Almost 100% mixing efficiency is achieved at a mixing time of 167 ms [63]. In a further study, implementing a soft microchannel wall of width 0.5 mm and a height of 35 μm resulted in ultra-quick blending for Reynolds numbers as small as 226. Complete cross-stream blending is accomplished within 10 ms. Hence, the blending time becomes littler by a factor of 100,000 in contrast with that required for diffusive blending (250 s) [64]. With these parameter measurements, which are essential in serving microfluidic blending, chemical synthesis is one of the applications that employs the mixing of flows [64].
(b)
Sorting applications
Sorting is isolating the same kind of particles in the fluid flows. Sorting is implemented with the flow of nanoparticles and the application of an external magnetic field, by adding a sheath or by pumping fluids with different flow rates, etc. Microchannel designs and their measurements influence particle migration and separation behavior [71]. Inertial focusing on planar layouts has also been investigated, which favors sorting [72]. Various segregation processes provide different measurements of accuracy, error, selectivity, throughput [73], separation efficiency [74], recovery [74], enrichment ratio [74], and purity [73]. Many research works are conducted to realize more functional geometries, varying in measurements to reduce the extensive laborious requirement in the traditional fabrication process, with more particles focusing on efficiency [74]. The spiral microchannel becomes one of the most explored microchannel geometries used to initialize segregation. A spiral microchannel provides a new dimension to the segregation process by increasing the segregation’s efficiency, where micro-sized particles switch to multiple locations at a flow rate of 4.2 µL/h [75] while viscoelastic fluid flows [63,70,76] allow size-dependent segregation.
The sorting efficiency achieved for 1 µm, 10 µm and 20 µm size particles is presented in Table 3 and Table 4. Segregation efficiencies achieved by different methods in the literature for different particle sizes are highlighted in Figure 2. Table 4 showcases the highest segregation efficiencies achieved for varying microparticle sizes. For 1 µm, size-dependent separation [68] and crossflow micro filter layouts [77] resulted in 90% of the segregation efficiency, while inertial focusing in spiral microchannels, followed by particle deflection in the straight channel [67], resulted in 99.7%. Polystyrene particles of sizes 2 µm and 3 µm in Newtonian and viscoelastic fluids co-flows attained 90% efficiency using size-dependent separation [68]. Inertial focusing in curved channels resulted in 94.5% separation efficiency for 5 µm particles [78], while inertial focusing in spiral microchannels led to 98.3% for 5.55 µm particles. For 10 µm particles, segregation efficiency varied between 94.5%, 100%, and 100% for inertial focusing in curved channels [78], passive inertial focusing with active magnetic deflection [79], and simultaneous separation [80] methods, respectively. Inertial focusing in curved channels resulted in 94.5% separation efficiency for 15 µm particles [78]. For 20 µm particles, segregation efficiency was 100% for both passive inertial focusing with active magnetic deflection [79] and simultaneous separation [80] methods. Considering the highest segregation efficiencies for each particle size, 10 µm and 20 µm particles reached 100% efficiency.
New microchannels were fabricated to improve the segregation process. Inertial focusing is influenced by many 2D layouts such as straight and spiral square spiral channels at the flow rates 1 mL/h, 5 mL/h, 10 mL/h,15 mL/h, and 20 mL/h. The tape’n roll method helped to configure helical and double-oriented spiral channels to check the unexplored inertial migration characteristics [72].

3.1.3. Medical Applications

The contribution of microfluidics in the medical field has tremendously increased in the past two decades. Presently, the research is focusing on biosensing and microfluidic integration. Advancements are happening in label-free DNA biosensors, with a specific spotlight on the combination with microfluidic structures for point-of-site detections [9]. Dissipative particle dynamics (DPD) simulation mimics dynamic and rheological characteristics of different soft matters such as red platelets, vesicles, polymers, and bio macro atoms in microchannels [81]. It is seen that flow change and platelet adhesion significantly influence one another [82]. Currently, microfluidics applications cover DNA detection [83], cellular flow manipulation [9,84], reactants synthesis, biopharmaceutical productions such as drug synthesis [83], epithelial cell adhesion [85], in-vitro applications [69,86] and in-vivo applications [86]. Additionally, microfluidic droplet applications include DNA analysis [87], DNA arraying [88], blood analysis [87], and chemical reactions [87]. Nevertheless, as stated below, significant work has been conducted in medical applications about drug delivery and sorting/isolation applications.
(a)
Drug delivery applications
The application of microfluidics also lies in drug delivery for treating cancer [69] and other diseases. Nowadays, chemotherapy has received less attention because of its low efficacy and adverse side effects in treating tumors that are close to the major blood vessels of the liver [89]. Drug delivery is creating a great buzz in treating arterial diseases such as atherosclerosis, tumors, and infections, and removing blood clots without the requirement of surgery, thereby avoiding post-surgical complications and hence decreasing treatment costs.
The fabrication of nanocarriers for oral drug delivery uses different approaches involving drugs/plasmids and nanocarriers flowing from different inlets into a single microchannel, mixing both using a staggered herringbone mixer in the microchannel, microfluidic droplet generator, and microfluidic processor [86]. The flow of biocompatible nanoparticles in blood flow is controlled by a magnetic field so that they can carry the drugs to the region of the disease, such as the stenosed artery, and release the drugs at that point for treatment [90,91]. Shear stress decides the residing duration of nanoparticles at the targeted points while creating the way for these medical applications [90]. Nanoparticle concentration is a function of axial velocity and temperature. Furthermore, the concentration and size of nanoparticles increase wall heat transfer and favor drug delivery [90]. Electrokinetic force and pulsatile pressure gradient are the other factors that influence nanoparticle flow [91]. Microfluidics work with the effective and minimal expense creation of different miniature and nanoparticles is on focus. This is carried from various materials and therapeutic agents, with high stacking limit and controlled delivery at a limited scale, which limits the measure of required reagents.
The nature of synthesized nanocarriers, such as morphology, drug stacking limit, and kinetic delivery boundaries, can be effectively and successfully altered and advanced by changing the microchannel geometry and stream rate [86]. Nanotube/pH-responsive polymer composite safeguards the stacked meds from unfavorable release until their pH comes to 7.4 [92]. Another drug delivery system that falls in the category is when high-intensity focused ultrasound-induced mild hyperthermia allows drug release and acoustic streaming pushes temperature-sensitive liposome particles from the vessel wall to the target area; this results in effective drug penetration into the tissue increasing by 56% compared to conventional drug delivery approaches [89]. A carrier can also utilize its properties to enter the desired intracellular compartment and release the payload at appropriate times and conditions. Two types of intracellular delivery are carrier-based methods and membrane disruption techniques [93]. Features of an ideal intracellular drug delivery system are scalability, minimal cell perturbation, suitability to cell types, safety biocompatibility, control mechanism, and cost [93].
In the drug delivery process, microfluidic technology plays different roles at different stages, from the fabrication of nanocarriers and drug encapsulation to the drug intercellular entry.
(b)
Sorting/isolation in the medical field
The control of miniature and nanoparticles in complex biofluids is exceptionally requested in many biomedical applications and micro-level biological environments. Detection is carried out using biomarkers [74], while the isolation of live cells [94] and cancer cells (ex: colon cancer cells) traveling in the bloodstream in various parts of the body is handled with inertial microfluidics and the design of different microchannels [95]. For instance, microchannel geometry with a fishbone shape increased the performance of separation of three different sized (2 µm, 3 µm and 13 µm) microparticles and segregation of MCF-7 from human erythrocyte mixture, with recovery efficiency greater than 98% [96]. Compared to circular, rectangular, and trapezoidal channels, a 3D-printed river meander-such as cross-section facilitated inertial particle focusing and sorting of MDA-MB 231 cells (26 µm) in whole blood, achieving 85.4% recovery [74]. The use of curved channel walls decreases cell damage, and the introduction of fabric filters resulted in ≈86% capture efficiency and ≈92% retrieval efficiency for epithelial and mesenchymal cancer cells [97]. Size-dependent separation of staphylococcus bacteria (1 µm) and platelets ((2–3) µm) with polystyrene in water and polyethylene oxide co-flow achieved >90% of separation efficiency and purity [68]. The needle-like Cytosensor is newly designed to detect and capture colon cancer cells with a detection span of (102–106)/mL for a flow speed of 10 mL/min [95], as shown in Figure 2.
In the literature, the highest segregation efficiencies attained for MDA-MB 231 [98], staphylococcus bacteria [68], platelets [68], epithelial [97,99], mesenchymal [97,99], and MCF-7 [98] circulating tumor cells are 81.2%, 90%, 90%, 93.81%, 95.13%, and 96.3%, respectively. The same is shown in Figure 2. MDA-MB 231 has attained the least segregation efficiency, and MCF-7 circulating tumor cells have attained the highest.
At the same time, the percentage of recovery achieved for exomes is at least 80% [100], and for RBC/WBC, it is the highest, with 99.5% recovery [73]. The same is plotted in Figure 3 and Figure 4, which show the purity attained by different methods in the literature for biological cells/bacteria, where EpCAM -ve circulating tumor cells have attained the lowest purity of 81.2% [98,101] and WBC/RBC cells have attained the highest purity percentage of 99.8% [73]. Besides these live-cell separations, sorting also applies to blood plasma [73,102,103] and enzymes [71].
This study states that WBC/RBC attained the highest segregation purity. Additionally, the segregation efficiency and recovery factors for cells/bacteria vary differently for different cells/bacteria size ranges depending upon the technique of segregation undertaken.

3.2. Sensors Invented for Microflow Measurements

Many sensors were fabricated or developed for microflow environments using different principles [104,105,106,107,108,109,110,111,112] and groups of sensing modules [110], and using other parametric sensors [104] to sense and measure the parameters such as flow rate [104,105,107,108,109,110,111], velocity [112] and droplet size [106], etc., as shown in Figure 5, and these sensors form a part of Lab-on-chip [111]. Flow rate has been calculated as a function of temperature [104] and time [109,112]. Work has also been conducted in enhancing the microflow-rate sensor performance. Variations in microchannel geometry provided a way to vary the range of flow-rate measurement [107]. Bypass channels [107] provided a new dimension to flow-rate sensing by introducing the flow-rate measurement range increase. The sensor’s sensitivity varies with the fluids’ density [107]. Table 5 provide the details of the invented microflow sensors, their sensing range, and added features.
In Figure 5a,b, s1, s2, s3, s4, s5, s6, and s7 are different microflow-rate sensors invented in the literature, and these are in increasing order of the range of measurements covered by these sensors. The plot here shows the flow-rate measurement ranges covered by them in the increasing order of ranges.
Determining the certainty curve is very important in choosing the flow-rate sensor in microscale flows for selecting the suitable sensor according to the application needs. In Figure 6, s3, s4, s5, and s6 are the microflow-rate sensors in the increasing order of the range of measurements covered by these sensors. The certainty in the microflow-rate sensor measurement increased as the range of flow rate covered increased.

3.3. Effect of Extrinsic Parameters in Microflows

3.3.1. Effect of Microchannel Geometry on Microflow Measurements

Microchannels, a critical aspect of the microflow environment, vary in shape, size, openness [113], and closeness [113]. Different microchannels are continuously being designed and used by researchers in different areas of microfluidics. The aspect ratio of a microchannel is the ratio of its width to its height. At the microscale, considering the Reynolds number and hydraulic diameter, aspect ratio measurements impacted water flow, friction factor, and velocity profile slope [114]. At the same time, microchannel shapes influence heat transfer performance [114,115] and pressure drop. Some shapes are suitable for smaller heat fluxes, and others are good for higher heat fluxes [115]. Microchannel aspect ratio measurements have a linear impact on fluid mixing performance. A higher aspect ratio equal to 1.2 showed superior mixing efficiency compared to a lower aspect ratio microchannel [63].
The uniformity of the phase distribution can be greatly improved with the decrease of the branch microchannel diameters for gas–liquid two-phase flow in micro-impacting T junctions with different branch channel diameters [116]. On the other hand, Wei Liu et al. showed that, in a 2D rarefied pressure-driven gas flow, microchannels bent and their cross-sectional area measurements impacted mass flow rates [117]. Aly maherabourabia and Sara aliabdel Moneim. (2019) worked on electrically conducting 1 M NaCl solution, where the channel measurements affect the dimensional velocity profile, the average flow velocity, and the volumetric flow rate in the 2D laminar model. Additionally, they stated that excessively applied fields resulted in a velocity drop for the deepest channel design [118]. The microchannel does not only show its influence in single-phase flows or closed channels. For the two-phase ethanol slug and helium bubble-oriented Taylor stream, the channel junction angle shows the variation of unit cell volume changes remarkably, with rising gas stream rate (helium flow rates are 180 mL/min and 260 mL/min) or diminishing liquid stream rate [119]. Currently, active and passive manipulations of particles in viscoelastic fluids (VEFs) are very progressive in terms of organic applications that incorporate molecule centering, partition, and arranging. For such applications, channel geometry also plays a role in deciding the final position of the particles [76].
Hence, microchannel geometry influences different microfluid flow parameters, making microchannel geometry an important unit when dealing with any microflow process.

3.3.2. Effect of Microchannel Wall Parameters on Microflow Measurements

Microchannel walls vary in terms of surface roughness, wall corrugation, and wall deformation. Microchannel wall parameters [68,120,121,122] affect different flow parameters such as fluid flow, flow regime, flow velocity, pressure, temperature, and heat transfer.
A study on the arrival and transit of biological cells such as HeLa and MDA-MB-231 in restricted compliant microchannels showed the formation of protrusion and contact, squeeze, and release regimes, and these regimes are sensitive to channel flexibility, channel compliance, and cell acceleration [123]. Meanwhile, in another study of two-phase flows, microchannel sinusoidal half-corrugated wall surface affected pressure, temperature, and heat transfer measurements [62]. In rectangular deformable microchannels, high flow rates also result in a decrease of pressure drop of 28% in comparison to the pressure drop for non-deformable microchannels [121]. As described in [124], the compliance parameter is another parameter that controls the pressure-flow characteristics as well as the deflection profile of the channel wall. The authors of the study concluded that, for the flow of non-Newtonian fluid through the compliant microchannels (of thickness ~100 μm) and a given change in the flow rate, a change in the pressure drop exists. Additionally, according to Munib Qasim Ansari and Guobing Zhou (2020), microchannel roughness width affects the fluid flow and heat transfer. Surface roughness peaks ((15–45) µm) impact laminar airflow, and heat transfer measurements in rough microchannels and performance depended more upon the roughness width in contrast to pitch [122].
Kiran Raj M et al., fabricated cylindrical polydimethylsiloxane microchannels varying in softness and analyzed the non-Newtonian, steady, pressure-driven, and blood analog nature, mimicking Xanthan gum solution. They found the occurrence of less flow-induced deformation in comparison with that of the channel diameter measurements [120]. Therefore, microchannel wall parameters also serve as an important unit to be considered while handling the flow in any microfluidic system.

3.4. Microflow Characteristics

Microflows could be single-phase or multiphase flows. Single-phase microflows are easy to handle, while multiphase microflows deliver high throughput [125]. Exercising the same benefits, these two kinds of flows are explored as explained below.

3.4.1. Single-Phase Flows

Studies have been carried out to check the influence of microflow characteristics on one another, as shown in Figure 7. At the microscale, due to turbulence and compressibility impacts, velocity profiles rely upon Reynolds and Mach numbers, and velocity profile, in turn, affects dynamic pressure and bulk temperature [126]. Turbulent flow with Reynolds numbers (860–1300) shows an increase in flow irregularity with an increase in Reynolds number when wall shear stress is read by a micro-pillar sensor [127].
The study concludes that while analyzing any microfluid flow parameter, care must be taken about the influence of other microflow parameters.

3.4.2. Two-/Multiphase Flows

Depending upon the microflow parameter measurement values, two-phase and multiphase flows result in different flow regimes. Figure 8 shows the formation of flow regimes formed in two-phase and multiphase flows utilizing different microchannel structures. The basic fraction of the flow rate of gas to fluid is vital to achieving perfect flow circulation and ideal mass exchange execution [128]. Phase distribution in two-phase gas–liquid slug flow with six concurrent rectangular microscale channels varying in the branch spaces in the range of 0.8 mm–12 mm, with varying liquid and gas inlet superficial velocity of ranges (0.008–2.52) m/s and (0.28–33.3) m/s, respectively, resulted in slug, slug-annular, bubbly, and annular flow regimes [42]. At the same time, a tree-molded microchannel built by T-type bifurcations produced flow regimes such as bubble flow, slug-froth flow, slug flow, and minimal slug flow [128]. Flow rate and junction angle affect two-phase, ethanol slug, and helium bubble-oriented Taylor flow at different angles (20 degrees–160 degrees) and gas and liquid flow rates [119]. The study is also carried out for the plug stream of a non-Newtonian and a Newtonian fluid flow, which resulted in higher viscosity at the centerline of the quartz microchannel [129]. Therefore, different kinds of flow regimes can be designed by deciding the velocity for each fluid in combined fluid flows.
(a)
Frictional pressure drops
Multiphase microflows are widely used to study frictional pressure drops. Fluid refrigerants and microchannels with different shapes influence the frictional pressure drop in the two-phase stream through microscale channels for different mass velocity ranges, saturation temperatures ranges, and vapor quality ranges [130]. Correlations could be developed to predict two-phase frictional pressure drop using Reynolds number, viscosity number, vapor quality, etc. [131]. Correlations developed on the database (with laminar–liquid laminar, gas turbulent–liquid laminar, and gas laminar–liquid turbulent flows) could predict the measured frictional pressure drop, with a Mean Absolute Percentage Error (MAPE) of 18.9% for the two-phase frictional pressure drop in the range (5–150) kPa for the channel measurement range (0.2–2.13) m [132]. In contrast, correlations developed by adding gas turbulent–liquid turbulent as one more category for the classifications resulted in a MAPE of 17.4% [131]. Sempértegui-Tapia and Ribatski [130] forecasted the frictional pressure drop of the database, estimating 89% of the outcomes below the error band ±20% with an overall MAE (mean absolute error) of 12.7% [130], while Cristiano Bigonha Tibiriçá et al. developed correlations of two-phase flow for flow boiling conditions in microchannels and predicted the frictional pressure drop with an MAE of 18.8%, and the level of information that error falls underneath was 30% [133]. Henceforth, various multiphase flows revolve around the frictional pressure drop study and its predictions.
(b)
Droplets
Droplet generation at the micro level takes place using two or more phase flows with different flow rates, as stated in Table 6, leading to its use in many clinical applications. In liquid–liquid two-phase flow in a coaxial micro-channel, the absolute valued swirling strength is the function of interfacial tension and continuous phase viscosity [134]. Additionally, the transformation from squeezing to dripping relies, more importantly, on the capillary measure of the continuous phase [87]. Droplets were also studied at different channel structures such as the T-junction of the microchannel, where three types of droplet coalescence were observed: tail coalescence [135], slipping coalescence, and unsteady coalescence behaviors along with a new droplet formation [136]. H. Shahin and S. Mortazavi found that, in a co-flowing immiscible elliptic jet stream structure, the microdroplets formed in an elliptic jet are smaller than in a circular jet [137]. The reaction rate is improved for the internal vortex of adhered droplet flow, and the capture process is controlled by the adopting fluorescence reaction and suspended particle capture [138].
The study states that the flow-rate ratio in the combined microfluid flow forms the critical factor that decides the size of droplets formed.
(c)
Bubbles
In the literature, work is conducted in terms of bubble formation [61,139], bubble expansion [61], bubble sorting [140,141], and sensor development to detect bubbles [104]. Bubbles can be formed in different ways, as shown in Table 7. The two stages of the bubble formation process are the expansion and breakup stages. The growth rate in the breakup stage is always greater than that in the expansion stage. Additionally, the bubble expansion rate is high at the start, nose, and tail [61]. A thermal bubble sensor uses four temperature sensors placed at different positions between two ends of the channel. These will check heat conductivity changes between liquid and air, as and when the bubble crosses the path [104]. Bubble length varies inversely proportional to the concentration of PAAm (aqueous solutions of polyacrylamide) and liquid inlet velocity [139]. Finally, the On-chip bubble sorter technique has been produced, whose functionality depends on the jet flow generated by the spark-induced cavitation. A micro-bubble takes a switching time of 250 µs and has advantages such as simple structure, continuous sorting, effortless control, good cell efficiency, fast switching, and steady fluorescence signals [141].

3.5. Porous Medium

Reviews conducted until now have focused on research on measurements of microflow parameters in the nonporous medium. Microfluid flow in permeable media is omnipresent in numerous natural and industrial operations [142]. Different inspections have been carried out to manipulate these flows for deriving the benefits. As an example, for the same and considering the apparent gas permeability and gas slippage factor in micro-and nano-porous media, it was found that the derived fractal model is a function of different parameters such as the relative roughness, the porosity, the fractal dimension for tortuosity, pore size, and gas intrinsic properties [143]. In a single-phase water flow and two-phase flow in the tight porous medium, solid–liquid interactions will raise the flow resistance of confined water and reduce the liquid permeability of tight porous media to about 64.6% of the intrinsic [144]. Additionally, the solid-to-fluid effective thermal conductivity ratio and the internal heat sources play a significant part in exothermic or endothermic reactions related to fuel reforming processes for fluid flow through porous non-uniform thick walls [145].
A microscale multi-relaxation-time lattice Boltzmann model with the regularization technique supports analyzing gas flows in different porous media [146], and the multi-relaxation-time lattice Boltzmann method can efficiently model the miniaturized scale gaseous stream in a complex porous medium in slip and early transition streams, taking the Knudsen number into account [147]. Considering the same medium and regime, Hong Zuo et al., modeled methane gas flow accounting for local Knudsen number, viscosity correction model, and local pressure gradient measurements [148]. Additionally, velocity slip and temperature jump conditions have their counter effects on the volume flow rate and heat transfer rate for a fully developed magnetohydrodynamic and electrically conducting fluid flow in a vertical micro-porous channel [149]. Droplet sizes [150] and multiphase interaction [151] have also been studied in porous mediums. Ultimately, the microflow parameters in the non-porous medium are also part of a study in a porous medium.

4. Case Study on an Orifice-Type Microflowmeter

The review showed that the aspect proportion estimations of microchannels impact the microflow-rate estimations. After understanding these exploration works, a case analysis is carried out to examine the impact of microchannel measurement values on miniature stream attribute estimations, such as miniature flow-rate estimations. The same is examined here and checked to determine if it holds good for all the different fluids with varying densities. Miniature stream rate estimations are considered through a miniature rectangular orifice in a rectangular microchannel in the present case study. A microorifice meter is a kind of stream meter used to gauge the pace of the microflow of fluid or gas, utilizing the differential pressure estimation guideline. The rule expresses that the pressure drop across the meter is relative to the square of the stream rate. This type of stream meter is utilized chiefly for robust application needs, as it is known for its strength and is extremely inexpensive. At the point when the orifice plate is set in a line, differential pressure is created across the orifice plate. This drop is linear and is in direct proportion to the microflow pace of the fluid or gas. Since there is a drop, it is involved where a drop in pressure or head is permissible.
A fundamental rectangular orifice microflowmeter [52,152] using the Bernoulli obstruction approach with the Venturi effect is shown in Figure 7. This flowmeter is simulated using MATLAB. Pressure difference versus flow-rate characteristics was measured across the orifice for various microchannel configurations and liquids. The flow rate is varied in the range (0–190) mg/s. The orifice plate dimensions are (width × height) = (60 µm × 60 µm). The working fluids chosen for simulations are ethanol, kerosene, ethylene oxide, water, and xanthan gum. The microchannel dimensions vary in length, as shown in Table 8. All three microchannel configurations shown in Table 8 are simulated for the considered working fluids. The discharge coefficient is taken as 0.5.

Combined Representation of Pressure Difference versus Flow Rate Characteristics for Five Different Liquids and Three Different Microchannel Configurations

The combined representation of pressure difference versus flow-rate characteristics for ethanol, kerosene, ethylene oxide, water, and xanthan gum for all three microchannel configurations of Table 8 are plotted and shown in Figure 8a–c. Observations made for the same are as follows:
(a) For the first microchannel dimension configurations of Table 8, the results showed that the pressure difference measurement increases as the flow rate increases and shows higher sensitivity at higher flow-rate values. The same is observed for each of the liquids considered in Figure 8a. Additionally, the density of the liquid influences the flow-rate measurements at the microscale-level flow. Hence, the slope of the characteristics varied for all the liquids considered in the plot. Ethanol showed higher pressure difference measurements, and xanthan gum showed the lowest.
(b) For all the liquids, the pressure difference versus flow rate varied for the second and third microchannel dimension configurations, also referring to Table 8, and are shown in Figure 8b,c.
(c) Comparing the combined representation of pressure difference versus flow-rate characteristics in Figure 8a–c for five different liquids and three different microchannel dimension configurations of Table 8. As microchannel dimensions (length) increase, pressure difference measurement peaks increase, i.e., microchannel geometry influences pressure difference versus flow-rate characteristics.
Hence, this case study showed that aspect proportion estimations of microchannels impact the microflow-rate estimations. Additionally, this analogy came true for all the different fluids with varying densities. The case study agreed with the reviewed work.

5. Conclusions

As a byproduct of the microfluidic field and sensor field integration, microfluidics, which is a multidisciplinary subject, has been explored in developing different applications by considering its advantages related to small volumes. The paper has reviewed heat transfer applications, flow manipulation applications, and medical applications that have been developing in multiple directions by exploiting microfluidic flow characteristic measurements. It is evident from the pie chart shown in Figure 9 that out of the overall work conducted in the literature, 61% of the vast amount of work is covered by microfluidic applications alone. Among 61% of microfluidic applications, heat transfer work covers a maximum of 31%, flow manipulation application covers 13%, and medical application development work covers 17%. Most heat transfer applications are covered by cooling requirements that rise in electronics and refrigeration.
Flow boiling has proven to be a promising cooling method. The heat transfer coefficient strongly depends on mass flux, heat flux, and vapor fume quantity. It is found to change for different microchannels, different microchannel orientations, different fluid flows, different Reynolds numbers, and magnetic fields applied. The largest window is investigated as far as heat flux, and mass flux ranges are concerned for the progression of FC-72 dielectric liquid through three different microchannel fins with different slanted angles. The smallest window explored for dynamics and heat transfer characteristics of flow boiling bubble train using R134a flow where a nonequilibrium phase change model provides a way to measure the interface temperature and heat flux jump. Microchannel designs influence both blending and sorting. Almost 100% mixing efficiency is achieved at a mixing time of 167 ms, and by considering the highest segregation efficiencies for each particle size, 10 µm and 20 µm particles have reached 100% segregation efficiency. Concerning the medical field, apart from DNA detection, study, and the manipulation of blood flow in the body, drug/reactant synthesis, and in vitro/in vivo application, more studies have been performed on drug delivery and isolation of living cells. Drug delivery is becoming an essential part of clinical applications and is improvised with better accuracy and dedicated intercellular drug delivery using micro and nanotechnologies.
Microfluidics plays an essential role in different processes of targeted drug delivery, as in the nanoparticle fabrication process, drug encapsulation process and the intercellular entry of drugs. In the studies documented to date, the highest segregation performances reached for MDA-MB 231, Staphylococcus bacteria, platelets, epithelial, mesenchymal, and MCF-7 circulating tumor cells are 81.2%, 90%, 90%, 93.81%, 95.13%, and 96.3%, respectively. Seeing the speed and efficiency with which microfluidics is extending its work in medical diagnostics and treatments with so much reliability, convenience, portability, and cost-effectiveness, there is no doubt that microfluidics will be the future of medical diagnostics.
Different microflow-rate sensors were designed to measure the microflow rate in different measurement ranges. Five percent of the overall literature work has focused on microflow-rate sensor inventions. Among these, a microflow-rate sensor with temperature sensors covered the lowest measurement range of (0.1–100) mL/h, and a thermal time-of-flight flow sensor covered the highest measurement range of (1–20) mm/s. A promising and good sensor performance in a high microflow-rate measurement range is seen, while microflow-rate sensors with a low measuring range must compromise with uncertainty in measurement. The discussion has also provided new ideas, such as microchannel geometry selection and the introduction of bypass channels, to the sensor designer to improve further the performance of microflow-rate measurements in related devices.
Additionally, this part of the review helps select an appropriate sensor for varying microflow environments and microflow-rate ranges. Sensor performance improvement in handling different liquids by the same sensor has yet to be addressed. Sensor calibration and the positioning of sensors could be improved to make the same sensor efficient for wide flow-rate ranges and a wide range of applications.
Approximately 12% of the literature relates to the effects of extrinsic parameters on microflows. Choosing the right microchannel design will ease the microflow system complexity and facilitate microflow-related processes. Hence, care must be taken in designing different microchannels for different applications, as microchannel influence can either increase or decrease microflow system performance.
Again, studies on microfluidics characteristics such as velocity profile, dynamic pressure, bulk temperature, flow regimes, frictional pressure drop, droplet formation, and bubble formation/expansion/sorting/detection are analyzed in more depth for both porous and nonporous mediums. In addition, a combined influence of these microflow properties on one another is noticed. This part of the review covers 22% of the review work. Having observed such microflow parametric quantity impacts and decisions of the suitable microflow sensors, both assume an extraordinary part in knowing the stream physics of regular living microflow systems and in growing new applications in the microfluidic field. Microfluidics is a vast and multidisciplinary subject, and research on the same subject is continuously serving different areas of life with high potential. Additionally, the learning of relationships between microflow parameters in more and more depth will help in broadening its application areas in the future.
After understanding these research works, a case study was undertaken to check the influence of microchannel geometry measurements on microflow characteristic measurements, such as microflow-rate measurements. Microflow-rate measurements were considered through a micro rectangular orifice in a rectangular microchannel. The study showed that the aspect ratio measurements of microchannels influence the microflow-rate measurements. In addition, from the case study, it is significant that this analysis is good for varying liquids with any density.
The advantages of microfluidic technology increase the control over the heat transfer process. The diagnosis of the patient, creation of drugs (chemical industry), and treatment of the patient are carried out simultaneously with the use of microfluidics-sensor technology. The innovation creates a drive for researchers to integrate microfluidics and sensor combinations. Robustness is another criterion that is being addressed for microfluidic product evolution. This magnified progression in microfluidic-sensor technology would lead to its methodical and scheduled use in educational and industrial customs. This will also result in the use of microfluidic products, starting from day-to-day life, for example, in regular patient diagnosis, to off the shelf, for example, in custom-made LOC that could be carried to outer space for medical and microelectronics maintenance purposes.

Author Contributions

S.K.V. conceived the idea and designed the article. S.L.K. performed the literature search and data analysis and wrote the manuscript. C.G.N. and S.K.V. supervised the whole work, polished the manuscript, and drafted and critically revised the work. All authors discussed the results and reviewed the manuscript. All the authors have equal contributions to the work. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

No Human or Animals were used in the study.

Data Availability Statement

All the data used for the work are included in the paper.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Heat transfer window investigated for different ranges of heat flux and mass flux.
Figure 1. Heat transfer window investigated for different ranges of heat flux and mass flux.
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Figure 2. Variation in segregation efficiency (represented in increasing order for each cell) for different methods adopted in the literature plotted for different kinds of cells.
Figure 2. Variation in segregation efficiency (represented in increasing order for each cell) for different methods adopted in the literature plotted for different kinds of cells.
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Figure 3. Biological cells/bacteria recovery (represented in increasing order) for different methods adopted in the literature.
Figure 3. Biological cells/bacteria recovery (represented in increasing order) for different methods adopted in the literature.
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Figure 4. Segregation purity attained (represented in increasing order) for different methods adopted in the literature plotted for different kinds of biological cells/bacteria.
Figure 4. Segregation purity attained (represented in increasing order) for different methods adopted in the literature plotted for different kinds of biological cells/bacteria.
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Figure 5. (a) Invented flow-rate sensors cover lower flow-rate ranges. (b) Invented flow-rate sensors covering higher flow-rate ranges.
Figure 5. (a) Invented flow-rate sensors cover lower flow-rate ranges. (b) Invented flow-rate sensors covering higher flow-rate ranges.
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Figure 6. Certainty in microflow-rate measurements plotted for different microflow-rate sensors.
Figure 6. Certainty in microflow-rate measurements plotted for different microflow-rate sensors.
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Figure 7. Rectangular orifice microflowmeter used in the microchannel.
Figure 7. Rectangular orifice microflowmeter used in the microchannel.
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Figure 8. Measured pressure difference for various microflow liquids under (a) First microchannel configuration (b) Second microchannel configuration (c) Third microchannel configuration.
Figure 8. Measured pressure difference for various microflow liquids under (a) First microchannel configuration (b) Second microchannel configuration (c) Third microchannel configuration.
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Figure 9. Pie chart showing a literature study for the combination of the microfluidics field and sensor technology.
Figure 9. Pie chart showing a literature study for the combination of the microfluidics field and sensor technology.
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Table 1. Different heat flux-mass flux windows explored for heat transfer studies.
Table 1. Different heat flux-mass flux windows explored for heat transfer studies.
Heat Flux-Mass Flux WindowStudy Carried Out On
W1 [61]Dynamics and heat transfer characteristics of flow boiling bubble.
W2 [39]Heat transfer in a single 5 mm inner hydraulic diameter square channel in a vertical orientation.
W3 [62]Temperature and two-phase heat transfer in half-corrugated micro-channels with bottom sinusoidal structured surfaces.
W4 [41]The convective heat transfer coefficient in Interconnected Microchannel Net (IMN) and rectangular microchannel.
W5 [49]The flow boiling in a 10 µm micro gap.
W6 [50]Heat transfer coefficient and pressure drop measurements in vertical flow orientation with a 1 mm diameter.
W7 [16]Heat transfer measurements in segmented finned microchannels and uniform cross-section microchannels.
W8 [56]Absolute pressure measurement in the range (1.16–1.84) bar flowing through rectangular, vertical, and asymmetrically heated mini channels.
W9 [53]Heat transfer coefficient during flow boiling inside a circular microchannel with an internal diameter of 1.1 mm.
W10 [17]Flow of FC-72 dielectric fluid through three different microchannel fins oblique angles such as 10, 30, and 50.
Table 2. Blending efficiency and time taken for various efficiency boosting parameters and micro pathways considered.
Table 2. Blending efficiency and time taken for various efficiency boosting parameters and micro pathways considered.
Microfluidic Pathways/Systems ChosenEfficiency Parameters Achieved for BlendingEfficiency Boosting Factors Highest Mixing Efficiency Achieved in Blending %Time Taken for Blending
Tube microchannel reactor [70]Intense micromixing performance, high throughput, and optimal micromixing timePore array tube
Spiral microchannels [63]Better mixingHigher aspect ratio measurements, variation of Reynolds number at Re = 140 and frequent curving of path lines90.56 to 100%167 ms
Soft microchannel wall of width 0.5 mm and a height of 35 μm [64]Ultra-quick blending (Complete cross-stream blending and Diffusive blending)Reynolds number 226 10 ms and larger by a factor of 100,000 in contrast to 10 ms
Table 3. Sorting efficiency achieved for 1 µm, 10 µm and 20 µm size particles.
Table 3. Sorting efficiency achieved for 1 µm, 10 µm and 20 µm size particles.
Size of Particles in µmMethods UsedSorting Efficiency Achieved in %
1 Size-dependent separation and cross-flow micro filter layouts [68,77]90
Inertial focusing in spiral microchannel followed by particle deflection in the straight channel [67]99.7
10Inertial focusing in curved channels [78]94.5
Passive inertial focusing with active magnetic deflection [79]100
Simultaneous separation [80]100
20Passive inertial focusing with active magnetic deflection [79]100
Simultaneous separation method [79]100
Table 4. Highest segregation efficiencies achieved for varying microparticles sizes.
Table 4. Highest segregation efficiencies achieved for varying microparticles sizes.
Particle Size in µmMethods UsedHighest Segregation Efficiency in %
1 [67]Inertial focusing in spiral microchannel followed by particle deflection in the straight channel99.7
2 [68]Size-dependent separation90
3 [68]Size-dependent separation90
5 [78]Inertial focusing in curved channels 94.5
10 [79,80]Passive inertial focusing with active magnetic deflection and simultaneous separation methods100
15 [78]Inertial focusing in curved microchannels 94.5
20 [79,80]Passive inertial focusing with active magnetic deflection and simultaneous separation methods.100
Table 5. Different flow sensors invented along with their sensing range and added features.
Table 5. Different flow sensors invented along with their sensing range and added features.
Sl. No.Microfluidic Sensor TypeSensing RangeFeatures and the Added Advantage
s1Calorimetric thermal On-chip Ni stream rate sensor [111](0–200) µL/minSensor positioning flexibility on the microfluidic device, average error is <5%, power-efficient, no-hysteresis, no dead volumes, high resolution of <30 nL·min−1, implicit calibration, no trapped bubbles, and accuracy at lesser working temperatures (50 °C).
s2Flow-rate sensor using PET thin film [107](10–650) µL/minDisposable bypass microchannel and reusable sensing substrate prevents biological contamination and increase the range of flow-rate measurement
s3Flow-rate sensor by with three temperature sensors [104](0.1–100) mL/hAccurate compared to the conventional drop-counting technique sensor. Application: drug infusion
s4Passive micro stream sensor that uses diamagnetic levitation [105](1000–7000) µL/minZero mechanical contact and low power consumption with the elimination of friction
s5Optical flow metering fronts tracking techniques [110](0.05–50,000) µL/minUncertainty in the camera and displacement sensor systems is less than 4% and less than 3%, respectively.
s6Flowrate sensor using double cascaded bowknot-kind tapers [109](0.66–10.6) mm/sLiquids with a refractive index range of 1.33–1.43
s7Thermal time-of-flight flow sensor [112](1–20) mm/sApplication in detecting liquid refrigerant velocity range
Table 6. Droplet generation methods.
Table 6. Droplet generation methods.
Fluids Used for Droplet Generation WaysThe Principle behind Droplet’s Size MeasurementDroplet’s Size
  • Silicone oil, pure water, xanthan gum aqueous solutions, and water with tween 20 fluids [87]
  • Droplet size depends on the flow-rate ratio and capillary number
  • Nondimensional droplet generated with a diameter of range (0–5)
  • Water stream and corn oil [106]
  • Droplet size measurement is a function of the phase change of the microwave signal and relative permittivity.
  • Droplet sizes as small as 150 µm in radius are sensed
  • Carrier oil and PBS [107]
  • The droplet size was controlled by the oil and buffer flow rates
  • Using disposable microchannel, droplets varying in diameter for less than 1.25% and droplets volume for less than 4%.
  • Elastic Boger fluids and the mineral oil [135]
--
  • Glycerol aqueous solution and mineral oil [136]
  • The final droplet size degraded (upgrades) with the upgraded capillary number when the flow rate of the dispersed (continuous) phase was fixed.
-
Table 7. Bubble formation methods.
Table 7. Bubble formation methods.
BubblesMixtures Used for Bubble Formation
Taylor bubble [139]Power-law liquids such as aqueous solutions of polyacrylamide (PAA) flowing through a circular co-flow microchannel
N2 bubble [140]Highly viscous glycerol water mixtures in a flow-focusing device
A series of bubbles [61]Convective boiling microchannels where R134a fluid flows with an initial constant mass flux of 335 kg/m2·s; through a channel having Aluminum as wall material whose constant heat flux is 14 kW/m2
Table 8. Microchannel dimension configurations.
Table 8. Microchannel dimension configurations.
Configuration NumberLengthWidthHeight
First2500 µm2000 µm2000 µm
Second3000 µm2000 µm2000 µm
Third3500 µm2000 µm2000 µm
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Lingadahalli Kotreshappa, S.; Nayak, C.G.; Krishnan Venkata, S. A Review on the Role of Microflow Parameter Measurements for Microfluidics Applications. Systems 2023, 11, 113. https://doi.org/10.3390/systems11030113

AMA Style

Lingadahalli Kotreshappa S, Nayak CG, Krishnan Venkata S. A Review on the Role of Microflow Parameter Measurements for Microfluidics Applications. Systems. 2023; 11(3):113. https://doi.org/10.3390/systems11030113

Chicago/Turabian Style

Lingadahalli Kotreshappa, Sreedevi, Chempi Gurudas Nayak, and Santhosh Krishnan Venkata. 2023. "A Review on the Role of Microflow Parameter Measurements for Microfluidics Applications" Systems 11, no. 3: 113. https://doi.org/10.3390/systems11030113

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