Department of Mechanical Engineering

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Microfluidics as a field has a plethora of applications in several fields. From heat transfer to biomedical applications, microfluidic techniques are used to deliver solutions. In the present chapter, we look into the basics of microfluidic techniques used to manipulate tiny volumes of fluids. Further, a detailed discussion on acoustofluidics, lab/organ-on-chip, biosensing, and cell manipulation follows. Section 2.4 focuses on the use of bulk and surface acoustic waves to manipulate particles and cells. Section 2.5 sheds light on the use of microfluidic chips mimicking an organ or its basic process and how the same is used to study the effect of drugs on the organs. Section 2.6 focuses on using microfluidic techniques for disease detection and prognosis monitoring. The part on Cell manipulation cuts through various active and passive techniques for cell trapping, focusing, and sorting. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

World University root node

Microfluidics and Multi Organs on Chip

Applications of Microfluidics

Nitric oxide (NO) is one of the vital gasotransmitters that takes part in many biological pathways such as infection, inflammation and ischemia, immune response, neurotransmission, and cardiovascular systems. Nitrite is one of the primary metabolites of NO and is considered to be a circulating storage pool for NO. Here, we report direct and rapid measurement of nitrite in human blood plasma using a fluorescence-based microfluidic method. The study revealed the factors that affect the endogenous concentration of nitrite in blood plasma, mainly the presence of blood cells, hemoglobin, and soluble proteins. We find that separation of blood plasma immediately after sample collection and subsequent dilution of plasma with buffer at a ratio of 1 : 4 eliminates the interference from cells and proteins, providing reliable measurements. The proposed method can measure plasma nitrite in the concentration range of 0-20 µM with a limit of detection of 60 nM and a sensitivity of 5.64 µM−1 within 10 min of sample collection. By spiking nitrite into plasma, a linear correlation between the nitrite concentration and FL intensity is obtained, which is utilized further to measure the endogenous concentration of nitrite present in the plasma of healthy volunteers and patients. The study revealed that the endogenous nitrite concentration in the blood plasma of healthy humans falls in the range of 0.4-1.2 µM. Furthermore, the study with blood samples obtained from patients showed that nitrite levels are inversely correlated with the total cholesterol and low-density lipoproteins levels, which is in good agreement with the literature. © 2022 The Royal Society of Chemistry

Analyst

Microfluidics-based rapid measurement of nitrite in human blood plasma

Particle reinforced polymer matrix composites (PMCs) are widely used in the military aviation industry as a stealth coating for incident radar attenuation. These coatings are made up of many layers of different materials with varying thicknesses. In this study, we used terahertz (THz) spectral range by means of time-domain spectroscopy (TDS) to examine the thickness of iron particle reinforced polyurethane radar absorbing paint (FE-PU-RAP) composite coatings non-destructively. For accurate estimation of the individual layer thickness in multi-layer coatings, precise knowledge of the material properties of the individual layers is a prerequisite. Hence, standalone samples of the individual layers have been initially employed to extract the material properties, such as the refractive index and absorption coefficient. Then, the accurate thickness estimation by the time-of-flight measurement principle has been carried out using the reflected THz pulses. Further, since the individual reflected pulses from the multi-layered sample are overlapping in nature due to the optically thin coating thickness, a sparse deconvolution technique has been utilized for extracting each individual reflected time instant. The scattering from the iron particles also provides a challenge to the identification of the interface signals. This was addressed by optimizing the regularization parameter in the sparse deconvolution algorithm. With this technique, accurate estimation of each of the individual layers in the multi-layer sample has been accomplished, otherwise difficult non-destructively. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Fulltext

Journal of Infrared, Millimeter, and Terahertz Waves

Material Characterization and Thickness Measurement of Iron Particle Reinforced Polyurethane Multi-layer Coating for Aircraft Stealth Applications Using THz-Time Domain Spectroscopy

The development of predictive models for the accurate estimation of thermo-physical properties of the Thermal Barrier Coated (TBC) aero-engine components is critical in assessing component life and maintenance. TBCs are multi-layer systems applied on metallic structures operating at higher temperatures, such as aero-engine parts and gas turbine blades. These thermally insulating materials prolong the component life by limiting the thermal exposure of structural components. In this study, simulation-assisted Artificial Intelligence (AI) is developed to predict thermal conductivity (k), heat capacity (ρCp), and thickness measurement of TBC from thermal responses of samples with varying topcoat layer thicknesses. The dataset used in the AI model is a low-fidelity thermal profile from a multi-layer heat transfer model of the TBC system for training the neural network and high-fidelity thermogram from pulsed thermography experiments that are used for validation of the trained neural network. The proposed method demonstrated potential in the prediction of thermo-physical properties for real samples with a newly coated topcoat layer of thickness measurement varying from 24 to 120 μm, with a mean absolute percentage error (MAPE) for k and ρCp predictions of 1.71% and 1.37%, respectively, and for thickness prediction, MAPE ranges from 0.81% to 6.14%. This work explores the possibilities of merging a large set of low-fidelity simulation data and a small set of high-fidelity experimental data to train the deep neural network to achieve promising results in real-world thermography experiments. © 2022 Author(s).

Journal of Applied Physics

Simulation-assisted AI for the evaluation of thermal barrier coatings using pulsed infrared thermography

CFD analysis was performed in IHX to find the pressure drop and heat transfer between primary and secondary sodium flow using ANSYS 18.1. A similar anisotropic porous technique was used for both primary and secondary flow inside and outside the bank of tubes. A decoupled analysis was performed with prescribed heat source/sink distribution. The distributors and baffles are attached to achieve uniform flow and heat removal in secondary flow. A coupled analysis of the primary and secondary sodium heat exchange is also performed by using the flow field obtained with the distributor. The flow distributor reduced the radial temperature variation <20 K within the bundle region. A 3D sectoral model was analysed and estimated the effects of a mixing device in the secondary flow. The temperature difference again reduced to 7 K at the secondary flow exit, by mixing hot sodium of outer region with that of the inner region. Copyright © 2022 Inderscience Enterprises Ltd.

International Journal of Nuclear Energy Science and Technology

CFD analysis of primary and secondary sodium flows and associated heat transfer on performance of an intermediate heat exchanger in LMFBR

Solar-powered membrane distillation (SP-MD) technology has proven to be an ideal solution for providing fresh water in remote and off-grid locations. In this study, a novel solar energy-driven direct contact membrane distillation (DCMD) cycle is proposed in which a nanofluid-based volumetric absorption solar collector (VASC) is used to drive the DCMD process. The present work focuses on the use of volumetric collector instead of commercially available surface absorption-based solar collector in case of two-loop indirect SP-MD systems, which are installed to control the scaling and corrosion issues in solar collectors. The thermodynamic performance of this two-loop indirect solar-powered DCMD (SP-DCMD) system has been evaluated with the help of a mathematical model prepared in MATLAB. For modeling the DCMD unit, the ε-number of transfer unit (NTU) method used for designing heat exchangers has been employed. The performance of the overall system is evaluated by gained output ratio (GOR), thermal efficiency (η) of the membrane distillation, and water flux (Jw), and effects of various operating parameters related to both DCMD and VASC systems have been understood on the overall system performance. Finally, it has been shown that VASC-driven DCMD system has been approximately 4–15% higher gained output ratio compared to surface absorption-based solar collector (SASC)-driven DCMD system under similar operating conditions. Copyright © 2022 by ASME.

Journal of Thermal Science and Engineering Applications

Thermodynamic Analysis of the Volumetric Absorption Solar Collector-Driven Direct Contact Membrane Distillation System

The main purpose of this article is to monitor the natural frequency of stainless steel (SS304) with and without defect by spray-coated smart graphene nanoplatelet (GNPs)-doped poly (methyl methacrylate) (PMMA) nanocomposite strain sensor and human health by smart Lycra denim textile sensor. Methods such as impact hammer test and NI-daq, finite element method (FEM) simulation by Abaqus 6.12, and fast Fourier transform (FFT) study were applied for frequency monitoring of SS304. For human health monitoring, edema disease inspection, cough, and biceps locomotion were studied by graphene sol–gel textile sensor. We report eight sensors fabricated by scotch tape exfoliation method and their sensitivity was checked in terms of gauge factor (GF). The highest and lowest GF-based sensors were checked for sensitivity in the defect (hole) specimen. These sensors were used to sense the natural frequency of SS304 at three different positions in the cantilever beam. The same quantity of GNPs was used for making Lycra denim textile sensors for human health monitoring. The Lycra denim textile sensor showed a 216% change in resistance in the left calf muscle, which is less than right leg flexibility, indicating good sensitivity. In addition, the textile sensor helped in sensing coughing and biceps monitoring. The ease in fabrication and high sensitivity demonstrate the potential ability of GNPs for futuristic smart material for structural and human health monitoring. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Materials

Smart Graphene Nanoplatelet Strain Sensor for Natural Frequency Sensing of Stainless Steel (SS304) and Human Health Monitoring

This work explores the generation of Lamb waves and their higher harmonics using a pattern source. An array of laser sources, when used with a short-pulsed laser, generate multiple Lamb modes in a plate-like component. The variation in duty ratio of the pattern source is found to influence the generation of fundamental modes and their harmonics. A two-dimensional finite element model is developed to simulate the narrowband Lamb wave generation process, and validated against targeted experiments. For a ‘square-like’ spatial profile of energy distribution, the second harmonic of the fundamental wave modes is fully suppressed at the duty ratio of 0.5, and the third harmonic of the fundamental wave modes is fully suppressed at duty ratios of 1/3 and 2/3. As the duty ratio increased from 0.2 to 0.8, the variation in amplitude of the fundamental modes is greater than that of the higher order modes. For duty ratio values less than 0.25 and greater than 0.75, the second harmonic component of the fundamental waves had approximately the same amplitude as the fundamental wave modes. Similarly, the third harmonic of the fundamental wave modes had the same amplitude or slightly higher amplitude than the higher order Lamb modes for duty ratio values less than 0.25 and greater than 0.75. © 2022

NDT and E International

Influence of duty ratio of a pattern source on laser generation of Lamb waves

Acoustic handling of dense suspension of microparticles has relevance in lab-on-a-chip, food, and pharmaceutical technologies. So far the studies on acoustic focusing of dense suspensions treat the particles to be of the same size, i.e., monodisperse. Here, the flow of dense bidisperse suspensions of microparticles in a microfluidic channel flow exposed to a standing acoustic wave field is studied. Experiments show selective enrichment of the larger particles along the channel center where the smaller particles are depleted. A continuum-based model reveals that the particle migration is governed by the combined influence of shear-induced migration and acoustic radiation forces. The migration behavior of the suspended particles along the channel length is quantified in terms of the degree of focusing, relating to the particle migration toward the center of the channel, and the degree of segregation, relating to the separation of larger and smaller particles. It is observed that both the degree of focusing and segregation varies directly with the intensity of the acoustic field and the ratio of particle sizes and inversely with the suspension volume fraction. © 2022 American Physical Society.

Physical Review Fluids

Flow of bidisperse suspensions under the effect of standing bulk acoustic waves

We study particle trapping driven by the axial primary radiation force (A-PRF) in shaped traps exposed to standing bulk acoustic waves (S-BAW) using numerical simulations and experiments. The utilization of the stronger A-PRF as the main retention force is a consequence of standing-wave formation along the flow direction, instead of the orthogonal direction as in the case of traditionally used lateral-PRF S-BAW trapping setups. The study of particle dynamics reveals that the competition between A-PRF and viscous drag force governs particle trajectory. The ratio of the acoustic energy to the viscous work (β) provides a general criterion for particle trapping at a distinctive off-node site that is spatially controllable. Particles get trapped for β≥βcr at some distance away from the nodal plane and the distance varies as β-c (c=0.6-1.0). The use of A-PRF as the retention force could potentially allow traditional S-BAW trapping systems to envisage high-throughput advancements surpassing the current standards in cell-handling unit operations. © 2022 American Physical Society.