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

The use of guided ultrasonic waves has been identified as a promising technology for continuous monitoring of pipes and tubes for the detection of corrosion damage defects of cross-sectional area ratio less than 5%, particularly in the process industry applications. Here, we present an approach to use torsional guided wave mode T(0,1) generated using leave-in-place magnetostriction patch sensors for the health monitoring of thin and small diameter stainless steel tubes operating at elevated temperatures in the range of 150°C. These tubes are used in the transportation of gas in the Silicon wafer manufacturing semiconductor industries. The detection of small pitting defects is demonstrated using both numerical and experimental approach. The phenomenon of scattering of the high frequency fundamental torsional guided wave mode T(0,1) from small pitting type defects in thin and small diameter tubes is closely examined, and its excitation parameters are selected using finite element (FE) simulations. The sensitivity of the reflected signal from defects as low as 2% of the cross-sectional area ratio was feasible even at high temperature. This work is of great interest to many processes in semiconductor manufacturing. © 2021 Korea Institute for Structural Maintenance and Inspection.

World University root node

Journal of Structural Integrity and Maintenance

In-situ pitting corrosion detection using high-frequency T(0,1) guided wave mode in gas distribution tubes at operating temperatures

Surface temperature mapping is crucial for the monitoring and control of an object of interest, such as furnace, reactor pipes carrying hot fluids, or a component under a temperature-dependent process. While the use of waveguides for temperature measurement is well documented in literature, the attachment of the waveguide to a metallic component poses challenges. These include the relationship between the local waveguide temperature and that of the metal component, and wave leakage into the component. In this paper, the authors study the propagation of shear horizontal (SH) guided wave in a strip waveguide and its interaction with the notch embodiments in the waveguide. The effects of the type of notch and its depth on the SH mode characteristics are investigated through simulation studies. The mode of attachment of the waveguide to the metal component is by means a slot made in the component. The area of contact between the waveguide and metal component is optimized such that there is minimum wave leakage into the bulk material. Based on the simulation results, a waveguide strip is fabricated and used to monitor the local surface temperature of a test metal component. The waveguide is calibrated by correlating the time of flight (ToF) shift in the waveforms against reference temperature values. Thereafter, the instantaneous temperature of the metal component is determined from the calibration equations. A set of experimental trials are performed to check for repeatability. The experiments are conducted in near steady-state conditions for better accuracy in the measurements. Copyright © 2021 by ASME.

Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems

Surface Temperature Mapping of a Metal Plate Using Ultrasound-Guided Wave Technique

Transition between stream and droplet regimes in a coflow is typically achieved by adjusting the capillary numbers (Ca) of the phases. Remarkably, we experimentally evidence a reversible transition between the two regimes by controlling exposure of the system to acoustic standing waves, with Ca fixed. By satisfying the ratio of acoustic radiation force to the interfacial tension force, , experiments reveal a reversible stream drop transition for , and stream relocation for . We explain the phenomenon in terms of the pinching, advection, and relocation timescales and a transition between convective and absolute instability from a linear stability analysis [P. Guillot, Phys. Rev. Lett.99, 104502 (2007)PRLTAO0031-900710.1103/PhysRevLett.99.104502]. © 2021 American Physical Society

Physical Review Letters

Reversible Stream Drop Transition in a Microfluidic Coflow System via on Demand Exposure to Acoustic Standing Waves

The development of a biosensor for rapid and quantitative detection of the dengue virus continues to remain a challenge. We report a lab-on-chip device that combines membrane-based blood plasma separation and a localized surface plasmon resonance (LSPR) based biosensor for on-chip detection of dengue NS1 antigen from a few drops of blood. The LSPR effect is realized by irradiating UV-NIR light having a spectral peak at 655 nm onto nanostructures fabricated via thermal annealing of a thin metal film. We study the effect of the resulting metal nanostructures on the LSPR performance in terms of sensitivity and limit of detection, by annealing silver films at temperatures ranging from 100 to 500 °C. The effect of annealing temperature on the nanostructure size and uniformity and the resulting optical characteristics are investigated. Further, the binding between non-targeted blood plasma proteins and NS1-antibody-functionalized nanostructures on the LSPR performance is studied by considering different blocking mechanisms. Using a nanostructure annealed at 200 °C and 2X-phosphate buffer saline with 0.05% Tween-20 as the blocking buffer, from 10 μL of whole blood, the device can detect NS1 antigen at a concentration as low as 0.047 μg mL-1 within 30 min. Finally, we demonstrate the detection of NS1 in the blood samples of dengue-infected patients and validate our results with those obtained from the gold-standard ELISA test. © 2021 The Royal Society of Chemistry.

RSC Advances

LSPR based on-chip detection of dengue NS1 antigen in whole blood

For defense applications, rapid X-ray inspection of propellant samples is essential for the identification and assessment of defects. Automation of this process using artificial intelligence is possible by properly training a neural network model. Convolution Neural Networks (CNNs) have recently demonstrated excellent success in both the tasks of image recognition and localisation using an adequate amount of data. In real-world, it’s not an easy task to produce the correct amount of experimental data required for the deep neural network to operate. In this work, we propose a method for producing synthetic radiographic data that is supported by ray tracing based radiographic simulations for the deep learning algorithms to automatically detect anomaly in X-ray images. The simulation results, which are then supplemented by noise extracted from the experimental data, show a good comparison with the measurements. This Simulation assisted Automatic Defect Recognition (Sim-ADR) system simultaneously perform defect detection and defect instance segmentation. The accuracy of the defect detection system is more than 87% on a testing set included 416 images. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.

Department of Humanities and Social Sciences

Journal of Nondestructive Evaluation

Automated Defect Recognition on X-ray Radiographs of Solid Propellant Using Deep Learning Based on Convolutional Neural Networks

To avoid excessive tissue removal and collateral damage, the high-power density laser is apt for dental surgery also need to have high precision. For high-precision dental surgery with minimal tissue damage, the present work frames a method to predict laser ablation profile based on surface morphology and chemical composition of dentin. The surface morphology and chemical composition were studied on different dentin samples using scanning electron microscope (SEM) and Energy Dispersive X-ray Analysis (EDAX), respectively. The key laser ablation parameters (ω0, Deff, and Fth) were determined by laser irradiation study using 800 nm, Ti:Sapphire femtosecond laser at processing condition of 100 fs, 10 kHz and 10 mm/s. The dentin samples show a strong linear correlation between physiochemical characteristics and laser ablation parameters. The surface morphology exhibits a negative linear correlation with threshold fluence, whereas the converse is true for chemical composition. The laser ablation parameters of a random dentin sample are derived from the knowledge of linearity data. From the obtained laser ablation parameters, the complete theoretical ablation profile is constructed and validated with experimental ablation profile. Even though the surface morphology of dentin shows high linearity, the concentration of Ca and P can be used as the most feasible probe in clinical settings. Furthermore, the laser ablation rate and ablation efficiency are predicted by the method to optimize the laser processing condition for any specific teeth. The versatility of the method overcomes the problem of heterogeneity on various teeth and simplifies the method of finding optimal laser processing condition for immaculate laser surgery. © 2020 Wiley Periodicals LLC.

Journal of Biomedical Materials Research - Part B Applied Biomaterials

Physiochemical characteristics: A robust tool to overcome teeth heterogeneity on predicting laser ablation profile

Polymeric gels, when made into thin films, are reported to depict a reversible folding behavior on exposure to favorable solvents as a result of the coupled diffusion–deformation mechanism. In this work, we develop a model based on the coupled diffusion–deformation mechanism which can predict the large deformation caused during this reversible folding behavior of a polymeric thin film. The formulation incorporates a concentration dependent Young's modulus variation. It is found that the incorporation of concentration dependent Young's modulus of the film in the formulation is essential to predict the folding curvatures accurately. The results obtained using this model are validated with the experimental results of the Chitosan–Water system by comparing the folding characteristics — intermediate folding stages and curvature, while accurately explaining the mechanism of reversible folding. The model is applied to other material systems such as PVA–Water and PDMS–Hexane systems. Furthermore, we demonstrate that the developed model successfully predicts the buckling and wrinkling phenomenon observed experimentally in stimuli-responsive polymer thin films. © 2020 Elsevier Ltd

Department of Applied Mechanics

Mechanics of Materials

Coupled diffusion–deformation behavior of stimuli-responsive thin polymer films

We propose an outlier detection-based statistical approach to identify and locate a defect in composite plates using far fewer number of sensing points compared to conventional imaging techniques. The key steps involved in this computationally inexpensive approach are the random sparse selection of the sensing points through Poisson disk sampling, followed by a two-step outlier detection process based on thresholding and computation of median absolute deviation. The robustness of the proposed technique is explored through extensive simulations involving different defect sizes, random locations on flat plate structures, and various values of signal to noise ratio (SNR). We experimentally demonstrate the feasibility of detection of delamination, whose size is comparable to the ultrasonic wavelength with probability of detection (PoD) better than 90% using <1% of the total number of samples required for conventional imaging, even under conditions wherein the SNR is as low as 5 dB. © 2021 John Wiley & Sons, Ltd.

Department of Electrical Engineering

Structural Control and Health Monitoring

Outlier analysis for defect detection using sparse sampling in guided wave structural health monitoring

Nacre, a composite layer present in sea-shells, exhibits a remarkable combination of toughness, strength, and stiffness through its brick–mortar micro-structure, acting as a template for novel materials. Strength, one of nacre's important properties is highly variable due to distribution of underlying material's properties as well as various defects present in its micro-structure. Presently, researchers assume the Weakest-link hypothesis and consequently use the Weibull distribution to model this variability. However, this assumption is theoretically unproven for biological materials such as Nacre and extrapolation of the same to predict rare but catastrophic behavior would be incorrect. In this article, the suitability of Weibull distribution to account for the variability of strength in nacre is tested, using multi-scale models, developed using FEM. Through Monte Carlo based numerical experiments and Renormalization Group (RG) based arguments, it is shown that the Weakest-link hypothesis, which is commonly used to justify the use of the Weibull distribution, does not seem to hold for nacre. Micromechanics and non-local homogenization based distributions such as the one suggested by Luo and Bazant (2019) might be more appropriate for accurate extrapolation to the low probability tail. © 2021 Elsevier Ltd

Testing Weibull as a viable statistical strength distribution for Nacre

Transdermal drug delivery using hollow microneedle enables creating small, wearable and minimally invasive closed-loop system. Polymer hollow microneedles are preferable because they are cost-effective and easy to manufacture. SU-8 is chosen for creating the hollow microneedles as it is a biocompatible photopolymer with robust mechanical properties. Previously reported SU-8 microneedles either use melt casting process for coating SU-8 which is laborious or do not have monolithic structures, thereby making these mechanically weak and difficult to integrate. To the best of our knowledge, for the first time, we report the use of a single-step spin coating process to achieve the desired thickness of SU-8 while using UV lithography to create a monolithic microneedle array. Three types of microneedles were fabricated with outer dimensions varying from 90 to 180 μm, and lumen dimensions ranging from 60 to 80 μm and needle height of 600 μm. These needles are fabricated in a 10×10 array with a platform thickness of 300 μm. Geometrical, mechanical and fluid flow characterisations are carried out for the fabricated arrays. We report the use of a non-destructive evaluation method to characterise the lumen of the fabricated microneedles. The fabricated needles are robust and offer low resistance to fluid flow. The triangular needles can withstand a bending load of 0.2 N and an axial load of 0.7 N. The needles with circular lumen offer least resistance to fluid flow of 0.2 Pa-min μL−1. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.