Indian Institute of Technology Roorkee
  • Roorkee, Uttarakhand, India
Recent publications
The city of Guwahati is one of the most rapidly growing cities in India, at the same time being the most important hub of Northeast (NE) India. According to the reported seismic activity in India, the entire Northeastern region, where Guwahati City falls into, is among the most seismically active parts of the Indian subcontinent and even of entire South Asia. The seismicity of NE India has been proven by many damaging earthquakes in the past and is also reflected by the seismic zoning map of India’s current seismic building code which classifies the entire region into Zone V, i.e. the country’s highest seismic zone. The present chapter describes the different technical aspects that were implemented for the development of an earthquake loss information system for the city of Guwahati. The development of the system has involved both extensive fieldwork and computational efforts including ground shaking modelling considering soil amplification effects, defining ground shaking scenarios for earthquakes on local active faults and significant historical earthquakes, demarcation of the Guwahati City area and its subdivision into geographical units, the definition of building typology classes and generating their vulnerability functions, collection of building inventory data and socio-economic information throughout the city and finally the computation of damage and loss scenarios. The developed earthquake loss information model for Guwahati City can be used as guidance to local authorities on future city planning and earthquake mitigation and response actions.
Earthquake early-warning system (EEWS) uses modern communication infrastructure and real-time seismology to estimate the size of the earthquake and gives warning to target cities well before arrival of damaging waves. For earthquakes originating from the central Himalayas, such a system can provide tens of seconds of warning to the adjoining plains and Delhi can get as much as 70 s of warning time. A successful EEWS, in the event of 7+ magnitude earthquake from the central Himalayas, can save millions of lives. This paper provides concept, methodology, algorithms, and other details of EEWS and its importance for India. The paper also presents details and performance of a pilot project of EEWS operational in Uttarakhand, India.
Building upon Social comparison theory (SCT), this study examined the mediating role of hard-work and moderating role of leisure in the association between trait-competitiveness and life-satisfaction. Using three-wave data from 415 postgraduate students from North Indian universities, we found that hard work fully mediated the linkage between competitiveness and life-satisfaction. Moreover, inclination towards leisure weakens the association between competitiveness and hard-work and the indirect effect of competitiveness on life-satisfaction via hard-work. This study highlighted the importance of hard-work and leisure in understanding the possible mechanisms between the association of trait-competitiveness and life-satisfaction which can be utilized to develop interventions to promote student satisfaction.
The sustainable petroleum supply chain (PSC) gradually became an indispensable part of the companies. Due to its complexity in nature, various sources of risk appear in the sustainable petroleum supply chain. Most of the previous research was less focused on the risk liaison of the risk interaction. This study aims to identify the prominent risk factors and causal relationships among them by considering the petroleum industry's upstream, midstream, and downstream. The literature was scrutinized, and the main criteria were identified, which were filtered by the expert's panel. Five main criteria and the fifteen sub-criteria were selected for the final assessment of the risk identification and interaction of risk factors. The study has implemented an integrated MCDM techniques rough set theory and DEMATEL. This integrated method uses a flexible rough number to control the impreciseness and ambivalence. The result shows that fluctuation in the crude oil price, quality of products, and inability to anticipate market change are the prominent risk factors for sustainable PSC. Moreover, the study might help practitioners, policymakers, and academicians to emphasize their effort toward risk assessment of sustainable PSC.
Herein, we have reported a highly selective electrochemical sensing of 2,4-dichlorophenol in water at room conditions. 1D hybrid nanostructure of ZnO/α-MnO2 nanowire by combining ZnO nanoparticles and α-MnO2 nanowire was developed using a facile ultrasound induced coprecipitation method. The developed hybrid nanostructured material has been characterized in detail using X-ray diffractometer, Fourier transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, and energy dispersive X-ray spectroscopy, which confirm a successful synthesis of the ZnO/α-MnO2 hybrid 1D nanostructure. A nano-enabled, label-free electrochemical sensor is fabricated by utilizing the synthesized ZnO/α-MnO2 hybrid 1D nanostructure on a printed contacts-based working electrodes. The sensor prominently showed high sensitivity (0.45 kΩ/nM/mm²) with an excellent limit of detection of 2 nM. The equivalent Randel circuit has been designed and modeled for understanding the evolution of electron transfer kinetics. The shelf life analysis of the fabricated sensor device revealed the stability and reproducibility of over 90 days. The sensor is found to be highly selective toward 2,4-dichlorophenol even in the presence of other organic compounds. The developed sensor provides a novel, fast, and economical approach to detect chlorinated phenolic pollutants in water at ambient conditions, beneficial for health and environmental safety.
Integration of renewable energy sources in distribution system inflicts new challenges to the conventional protection scheme by substantially changing the amplitude and direction of fault current. In this paper, a novel protection scheme for DC microgrid based on the characteristics of reactor voltage during transient operation in both grid-connected and islanded mode of operation is proposed. The proposed protection scheme incorporates both primary as well as localized back-up protection scheme. In order to detect and classify faults, primary protection scheme utilizes the polarity of the transient reactor voltage at both ends of the cable under different operating conditions. As the primary protection uses the polarity of reactor voltage at both ends, thus the proposed scheme doesn’t require high speed communication and synchronous data. In case of communication failure, localized back-up protection scheme based on the change in reactor voltage at one end of the cable is used to identify the faulty section. The efficacy of the proposed scheme is verified against various internal and external faults along with system transients such as AC side faults, load variation, DG outage, noisy environment and generation uncertainties due to change in solar irradiance and wind speed. Finally, a scaled down hardware setup is used to validate the proposed protection scheme, which further illustrates the feasibility and reliability of the proposed protection scheme.
Photovoltaic (PV) arrays are highly compatible with DC microgrids as they are DC sources. However, the uncontrolled penetration of PV power in a DC grid will lead to overvoltage problems. This paper proposes an Integrated Power Control (IPC) Module for multiple PV sources in a DC grid which allows PV sources to deliver maximum power in MPPT mode and also works as a voltage controller to maintain DC bus voltage in droop mode. Thus, the IPC module integrates MPPT and DC bus voltage regulation in a single controller, reducing the complexity of the system and avoiding the need for the controller to switch between MPPT and droop mode as in conventional methods. Further, during unequal shading conditions between the multiple PV sources, the proposed IPC module effectively shares the power and operating the PV sources to deliver the available power to the DC bus. Thereby, the total efficiency of the system is increased. The IPC module is implemented in simulation for multiple PV sources on a DC grid, and maximum power tracking and power-flow management are verified. The prototype hardware setup is developed, and the results are presented to demonstrate the simple and cost benefited IPC module.
Composite coatings based on nickel have recently become popular in the automotive and aerospace industries owing to their corrosion-resistant qualities. However, as many cases have shown, this coating is ineffective in chloride-containing environments. As remediation, a graphene oxide/conducting polymer (Polypyrrole) composite with nickel has been proposed as an effective corrosion protective layer for bare mild steel. Furthermore, electrodeposition is one of the popular methods for coating metals with anti-corrosion coatings. A simple, cost-effective, and environmentally friendly electrodeposition process has been employed for the deposition of graphene oxide/polypyrrole composite with nickel (Ni-GO-PPy) on mild steel. XRD, EDAX, FE-SEM, and FT-ATR were used to analyze this coating extensively. A coated mild steel sample was evaluated in a 3.5% NaCl solution utilizing the Potentiodynamic polarization ,electrochemical impedance spectroscopy and weight loss immersion test to determine the coatings' anti-corrosion characteristics. In all of the experiments, the Ni-GO-PPy coating outperformed bare nickel and Ni–GO coatings in terms of anti-corrosion capabilities. As a result of this research, a practical and scalable technique for using Ni-GO-PPy composite coating to protect mild steel surfaces against corrosion has been demonstrated.
Governing the physical and chemical characteristics of contact area among solid substrate and liquid droplets is a widely used strategy to fabricate superhydrophobic and superhydrophilic surfaces. While both surface morphology and surface free energy of a solid substrate conclude its wettability, designing the surface with right topology has reserved immense focus by researchers in last few decades. In the pursuit to achieve such goals of immaculate surfaces, some intriguing question need to be answered, for instance, what will happen if one takes same material for the solid substrate but having different morphological features? Irrespective of chemical nature, how the physical appearance of a rough surface controls the wettability? To unravel these questions, we examine the wettability of different surrogate models using coarse-grain (CG) simulations. Interesting results were obtained for apparent contact angles on varying the morphology of a particular surface with different geometrical shapes. Different surface geometries such as square, nail, solid sphere, hollow sphere, rod, and hollow sphere of hydrophobic (poly(dimethylsiloxane)) (PDMS) and hydrophilic (poly (vinyl alcohol)) (PVA) polymers were created. In hydrophobic case, the square followed by nail shape corrugated surface demonstrated least wettability by restricting the penetration of water beads inside the grooves. Whereas, for hydrophilic case, the shell shaped surface showed excellent wetting condition due to maximum availability of unoccupied volume. It was concluded from the present study that hollow cylinder and square shaped corrugated surface could be respectively used to obtain the maximum and the least surface wettability possible. This investigation, through the evolved understanding of the role of surface geometry at the nano level could guide researchers and materials scientists to develop effective materials with desired wetting conditions.
Machine learning and deep learning models are increasingly being used in building the predictive models for the materials property prediction as a function of fundamental materials properties as well as structural and process parameters. Usually, these models predict the absolute value of the property of interest without considering the error or uncertainty involved in the values. However, when dealing with a database of experimentally measured properties, there is an inherent error involved in the experimental measurements. The source of this error could be instrumental accuracy limit, variability of experimental conditions as well as human observation error. Often the contribution of different sources of error is also difficult to determine. Therefore, it becomes essential to consider the source of uncertainty to build a prediction model with reasonable accuracy and trust. In the present study, we applied regression and interval predicting machine learning models on a dataset of experimentally measured thermal conductivities of high entropy alloys for thermoelectric application. The highest cross validation (CV) - R² value of 0.81 was reported when different regression models were built on the dataset containing alloys with four or more elements. However, the accuracy was significantly lower (CV-R² = 0.65) when the regression models were built on the entire dataset containing alloys with three or more elements. CV-R² and other parameters used for assessing the performance of regression models do not give a good idea of the accuracy of the interval prediction models. In the present study, we have proposed a novel confusion matrix, which gives a fair idea of the performance of interval prediction models. We have further validated our earlier hypothesis that the models built on the targeted dataset provide better accuracy due to smaller variance in the dataset.
Perovskite solar cells (PSCs) have been popular in the photovoltaic (PV) community, owing to their ease of processing and high efficiency. In order to improve their device performance, the interfaces are believed to play a vital role. In this regard, the interfacial energies and the associated physical processes such as charge transport, accumulation and recombination have been the focus of the research community. Despite the rise in power conversion efficiency (PCE) and all development, PSCs still suffer from the charge carrier recombination. As a result, highly efficient PSCs cannot meet the theoretical values of fill factor (FF) and open-circuit voltage ( VOC). Therefore, to reach out to the theoretical limit of performance for PSCs, carrier recombination needs to be controlled both in the bulk and at the corresponding interfaces. Herein, we have systematically studied the recombination in PSCs by establishing the role of different layers of PSCs using electrochemical impedance spectroscopy (EIS). To get insights into the role of different layers in recombination we fabricated PSCs with n-i-p configuration and changed the thickness of TiO 2 electron transport layer (ETL), absorber layer, and spiro-OMeTAD hole transport layer (HTL). Our results suggest that the recombination is reduced in case of devices with thicker HTL and is trap-assisted recombination. These results are in good agreement with impedance spectroscopy analysis. The value of recombination resistance (extracted by fitting of Nyquist response) is higher at VOC, which is consistent with higher VOC in these two cases. In case of the increased ETL thickness, the performance of the device is dropped since the increased interfacial resistance encourages the recombination. Our study presents a simple and effective approach to elucidate the dominating recombination sites in PSCs and improve the device performance.
This study investigated unsteady pressure pulsations in a low-head Francis turbine under the effects of strong cavitation for different plant discharge factors and submergence levels of the draft tube at normal water temperature. The effect of the submergence water level of the draft tube at a dominating frequency was found to be negligible underrated-load and upper-part-load plant-operating conditions. However, the amplitude increased as the submergence of the head of the draft tube increased. At a high plant discharge coefficient, i.e., under overload conditions, the maximum amplitude was found at the blade-passing frequency. Additionally, a cavitation region was observed in the vicinity of the blades of the Francis runner, indicating the start of cavitation damage. Moreover, the results revealed the characteristics of low-frequency high amplitudes, which were predominant in the draft tube for the lower-part-load condition. According to the relevant literature, such amplitudes can cause instability in the hydraulic system of a powerplant, potentially resulting in fatigue-related damage to the turbine during operation. This study's predicted numerical results indicated the potentiality of cavitation damage in low-head Francis runners for different plant-operating conditions.
This research work presents the Pt functionalized ZrN and TiN nanostructured composite thin film sheet-electrodes synthesized on SS-304 flexible current collector via in-situ co-sputtering technique. Incorporation of small amount of Pt in nanostructured electrodes vastly improves the electrical conductivity, capacitive performance, and electrochemical stability of the electrodes. These improved performances of the electrodes enhance the efficiency of the contrived flexible asymmetric supercapacitor (Pt-ZrN//Pt-TiN FASC). To achieve superlative performance, these electrodes are alternately stacked in an asymmetric configuration separated by filter paper (glass microfiber GF/C) soaked in 1 M KOH aqueous solution. The series stacking helps in widening the working voltage window and enhancing the specific energy. The alternate stacking (Pt-ZrN//Pt-TiN//Pt-ZrN) of FASC works on a wide range of voltage from 0 V to 3.2 V and offers high specific-capacitance (60.2 F/g) with higher specific energy (85 Wh/kg). The fabricated cell also displays good capacitance retention of 76.8 % for a large number of charging cycles (40,000). SS-based sheet type FASC can be used as a body panel of any electronic device to provide vital protection and energy storage system. These astonishing outcomes with ideal bending performance of the FASC promise a potential candidate of energy storage for futuristic flexible electronic devices.
The present study focuses on supercritical fluid extraction (SFE) of essential oil from turmeric root waste. It is an analytical extension of our previous experimental work (Priyanka and Khanam, 2018a, Priyanka and Khanam, 2018b). As one of the objectives, a physico-chemical characterization study shows that turmeric root oil is rich in oleic acids, making it suitable for use in the pharmaceutical and cosmetics industries. The other objective is to gain more insights into the experimental observations through two analytical methods – Mathematical Modelling (MM) and Artificial Neural Network (ANN). Through MM, it is seen that the SFE of turmeric root has an initial fast extraction followed by a slow extraction phase, and the solid phase mass transfer resistance dominates the process. The most optimized conditions for maximum oil yield OY are found through ANN since ANN can predict OY values for conditions for which experimental results do not exist. Phenomena like solute-solvent repulsion, volatility, and the role of intra-cellular structures are investigated through optimization of pressure, temperature, solvent/ co-solvent flow rates, and particle size. Through this work, the significance of turmeric root oil is established, a method of extraction is proposed, the physics involved in extraction is investigated, and optimized parameters for the extraction are suggested.
In the present work, a computational fluid dynamic simulation has been performed to investigate the movement of free-floating objects in wavy water. The movement of objects of different shapes, namely rectangular, trapezoidal, and hemisphere, has been simulated using the volume of the fluid model, and a satisfactory match between the simulated data and experimental results has been obtained. It is observed that the nature of vortices influences the movement of different shapes of the same mass. The rectangular shape has more vertical displacement as compared to the other two shapes. With the increase in characteristic dimension, power absorption efficiency increases and become constant, indicating a critical value of characteristic dimension for a given wave condition. On the other hand, with an increase in wave height, power absorption increases, but efficiency decreases. Trapezoidal shape with fin found to be optimum float shape.
Biomass is a promising renewable source that can reduce fossil fuel consumption and associated greenhouse gas emissions, but some of its characteristics make it difficult to use in its raw form. Torrefaction has been proposed as a thermochemical pretreatment to upgrade biomass for direct applications such as combustion and gasification, biochar and chemicals production, while reducing its transportation cost and increasing its shelf-life. Research, development, and demonstration of biomass torrefaction technologies have advanced during the last few decades, but many science and engineering fundamentals as well as technological challenges remain, especially in the areas of reaction thermodynamics and kinetics, reactor models and design, large-scale implementation, and environmental performance. In this paper we present a comprehensive review of recent developments in biomass torrefaction research and technology focusing on kinetics, particle and reactor scale models, and reactor designs. The impacts of torrefaction as a pretreatment of biomass on subsequent conversion processes, and the novel applications of torrefied biomass are discussed. The energy management, environmental impacts, economic and market potential of the technology as well as the deployment options are also addressed. There is no best universal torrefaction reactor and hence the choice should be made based on the biomass feedstock and the expected production rate and application. To reduce process costs and competition with other uses of biomass, the utilization of either waste or environmentally sustainable, more abundant, and faster growing biomass should be targeted for this technology. Torrefied biomass produced at higher temperatures resemble pyrolysis biochar in several properties thereby making it suitable for most biochar applications. Finally, considering the need to identify the bottlenecks that potentially could limit the use of torrefaction, and its preceding or subsequent processes, the future prospects, challenges, and opportunities of torrefaction technology are presented.
Cellulose Nanocrystals (CNCs) play a vital role in modern science & nanotechnology evolution. In this study, non-wood, i.e., Lagenaria siceraria peels, a food-industry waste was used as a source of CNCs. CNCs were successfully isolated from Lagenaria siceraria peels, and detailed characterization has been performed. The Fourier Transform Infrared Spectroscopy (FTIR) was performed to confirm the successful removal of other components from the waste peel. It holds a crystallinity index of 83% examined by X-ray diffraction (XRD). The rod-like morphology is established by Transmission Electron Microscope (TEM), Field Emission Scanning Electron Microscope (FESEM), and Atomic Force Microscope (AFM). CNC acquired excellent thermal stability (>220 °C) established by Thermogravimetric analysis (TGA). The zeta potential value of − 28.77 mV leads to the stability of the suspension. The birefringence of the anisotropic liquid crystalline CNCs proves that Lagenaria siceraria peels as an invaluable source for the production of CNCs for photonic and other advanced applications.
Chromium is detected in most ecosystems due to the increased anthropogenic activities in addition to that developed from natural pollution. Chromium contamination in the food chain results due to its persistent and non-degradable nature. The release of chromium in the ecosystem accretes and thereafter impacts different life forms, including humans, aquatic and terrestrial organisms. Leaching of chromium into the ground and surface water triggers several health ailments, such as dermatitis, eczematous skin, allergic reactions, mucous and skin membrane ulcerations, allergic asthmatic reactions, bronchial carcinoma and gastroenteritis. Physiological and biological treatments for the removal of chromium have been discussed in depth in the present communication. Adsorption and biological treatment methods are proven to be alternatives to chemical removal techniques in terms of cost-effectiveness and low sludge formation. Chromium sensing is an alternative approach for regular monitoring of chromium in different water bodies. This review intended to explore different classes of sensors for chromium monitoring. However, the spectrochemical methods are more sensitive in chromium ions sensing than electrochemical methods. Future study should focus on miniaturization for portability and on-site measurements without requiring a large instrument provides a good aspect for future research
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10,537 members
Sudeb Dasgupta
  • Department of Electronics and Computer Engineering
Tapas Mandal
  • Department of Chemistry
Sanjeev Kumar Prajapati
  • Hydro and Renewable Energy Dept.
Manoj Kumar B V
  • Department of Metallurgical and Materials Engineering
Paritosh Mohanty
  • Department of Chemistry
IIT Roorkee, 247667, Roorkee, Uttarakhand, India
Head of institution
Prof. Ajit K. Chaturvedi