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    Flash Evaporation Process: Semi-Analytical Model Development for Droplets and Laminar Thin Film Flow
    (Indian Institute of Technology Jodhpur, 2022-12) Chakraborty, Prodyut R.
    With the advent of miniaturization technology of electronic components and development of high energy devices, the cooling requirements of electronic systems has changed drastically. The localised high heat flux on micro level components has also become of the order of kW/cm2. For such a high heat flux, the conventional methods are unviable, as they need large flow rate of coolant to achieve tough temperature control. Due to the aforementioned reasons, the research in the field of Thermal Management System (TMS) for electronic systems becomes need of present to identify new cooling technologies. Flash evaporation cooling method is one of the potential contestants among futuristic thermal management technologies. Typically, flash evaporation process involves sudden depressurization of liquids below the saturation pressure corresponding to the liquid temperature. Due to the sudden drop in pressure, the whole energy cannot be contained in the liquid as sensible heat, and the surplus heat gets converted into latent heat of vaporization followed by a violent transition of liquid to vapor phase. During flash evaporation process, the latent heat of evaporation is absorbed mostly from the liquid itself, and temperature of the liquid falls very quickly. The commonly adopted mechanisms in industries are pool flashing, spraying of fluid in the form of droplets, flashing of flowing fluid and flashing of jets etc. Albeit being a fundamental cooling mechanism with numerous day today applications, there exists many a rarely studied problem description that involves evaporation cooling mechanism requiring suitable analytical treatment. Therefore, the present work focuses on investigating the flashing phenomenon with varying flow conditions? as droplet evaporation, flashing of film on vertical plane and convective heat transfer of falling film with emphasis on development of analytical and numerical models. The first part of the study is attributed to the development of a semi analytical transient heat diffusion model of droplet evaporation. The model is developed considering the effect of change in droplet size due to evaporation from its surface? when the droplet is injected into vacuum. Hertz and Knudsen formulation based on kinetic theory to evaluate evaporation mass flux from the free surface is considered. The study addresses the discrepancy in the values of obtained evaporation coefficients reported for diffusion based mathematical model and lumped heat model, where evaporation coefficient is termed as the ratio of actual evaporating mass flux rate to the maximum possible evaporating mass flux rate. The model shows strong dependence of evaporation coefficient on microdroplet size. Moreover, when the droplet radius is less than that of mean free path of vapor molecules at the evaporating surface, the evaporation coefficient is found to approach theoretical limit of unity and reduces rapidly for larger radii. Water has been considered as working fluid for the saturation temperature range of 295273.16K in the present study. The next set of analysis involves the development of a semi analytical model that addresses the hydrodynamic behavior of fluid film, falling on an adiabatic wall, under the effect of gravity with smooth laminar flow conditions. Although many researchers have carried out the hydrodynamic study of gravity driven vertical falling film in the last five decades, Reynolds Transport Theorem (RTT) has never been employed prior to the present work. The adopted approach is validated with the help of published literature, by comparing obtained parametric relations with the reported set of equations. A good agreement of the experimental results with obtained data provided an adequate confidence to use RTT for further study of convective heat transfer and flash evaporation. Thereby, the analysis led the foundation for heat transfer studies made further. With the shown conformity of previous investigations, the study is extended to convective heat transfer from the free surface of gravity driven vertical falling film. Unlike falling film evaporators, where fluid film gets heated from the wall on which it travels, the heat transfer takes place from the free surface to the film's interior in the present analysis. Consequently, an entirely new phenomenon has been considered, where thermal boundary layer develops at free surface, and thickens in the downstream flow direction towards wall. Therefore, the effect of thermal boundary layer on heat transfer mechanism from the free surface has rigorously investigated with the help of 1D heat transfer model. The developed model is based on the RTT. The model has further been extended by exposing the falling film in the vacuum, where pressure is maintained lower than the saturation pressure of liquid, corresponding to liquid temperature. A semi analytical 1D model has been developed considering RTT and Hertz and Knudsen formulation based on kinetic theory to evaluate evaporation mass flux from the free surface. Oneway coupling ( i.e hydrodynamic parameters effect the thermal behavior but reverses not true) has been employed. The rigorous study of the model involves the numerous parametric variations that have been checked for the physical consistency. The required parameters for the flash evaporation based thermal management system design have been evaluated minutely and distinctly. The detailed examination of thermal parameters like? surface temperature, bulk temperature, mass flux rate along with hydrodynamic parameters has been culminated in the form of unique unprecedented correlations. The correlations determined for local Nusselt number, surface temperature, bulk mean temperature and film thickness are validated with the set of data distinct from the data set through which the correlations are developed. Excellent agreement between the data obtained through proposed semi analytical model and data calculated through determined correlations is observed. The proposed analytical and numerical models along with the correlations, contribute towards heat transfer mechanism from the free surface of smooth laminar film under low pressure environment. The models further help to identify design parameters for flash evaporation based cooling. Moreover, the presented analysis provides an underlying basis for the development of two way coupling for thermal behavior and hydrodynamic analysis. Waviness of surface, temperature dependency of fluid properties, surface tension of liquid, buoyancy effect and roughness of adiabatic wall, may further be added in the present model at the cost of increasing complexity.
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    On Some Important Reliability Aspects of General Coherent Systems
    (Indian Institute of Technology Jodhpur, 2023-11) Hazra, Nil Kamal
    In practice, we use di?erent kinds of systems that are structurally equivalent to various well-established systems available in the literature, namely, ordinary coherent systems, ordinary r-out-of-n systems, sequential r-out-of-n systems, fixed weighted coherent systems, fixed weighted r-out-of-n systems, random weighted coherent systems, random weighted r-out-of-n systems, etc. In this thesis, we study di?erent reliability aspects of these systems under various scenarios. In most real-life scenarios, the components of a system work in the same environment and share the same load. As a consequence, there may exist two di?erent types of dependencies between the components of a system, namely, interdependency and failure dependency. The interdependency structure between the components of a system is usually modeled by a copula. The family of Archimedean copulas is commonly used to serve this purpose as it describes a wide spectrum of dependence structures. On the other hand, the failure dependancy for a system means that the failure of one component has an e?ect on the lifetimes of the remaining components of the system. This failure dependency is often modeled by assuming distributional changes in the lifetimes of the remaining components, upon each failure, of the system. The sequential order statistics (SOS) and the developed sequential order statistics (DSOS) are two models that are commonly used to describe the failure dependency of a system. There is a one-to-one relationship between order statistics and the lifetimes of systems. For example, the lifetime of an ordinary r-out-of-n system is the same as the (n ? r + 1)-th order statistic of the lifetimes of the components of the system. Similar relationships exist for SOS and DSOS. Thus, the study of order statistics is the same as the study of the lifetimes of systems. In this thesis, we study various ordering and ageing properties of ordinary r-out-of-n systems formed by dependent and identically distributed components, where the dependence structure is described by an Archimedean copula. Further, we study the ordering properties of the developed sequential order statistics (DSOS) with the dependence structure described by the Archimedean copula. Similar to the DSOS model, we introduce the notion of developed generalized order statistics (DGOS) which is an extended generalized order statistics (GOS) model formed by dependent random variables. This model contains all existing models of ordered random variables. We study various univariate and multivariate ordering properties of the DGOS model governed by the Archimedean copula. Further, we consider the SOS model with non-identical components and study several univariate and multivariate stochastic comparison results. The basic structures of many real-life systems match with random weighted coherent systems. The performance of a random weighted coherent system is usually measured by its total capacity. However, the major drawback of this measure is that it does not take into account the structure of a system. To overcome this drawback, we introduce a new structure-based performance measure, namely, the survival capacity. Based on this measure, we define three survival mechanisms (namely, Types-I, II and III) for random weighted coherent systems. We develop a methodology to evaluate the reliability of a random weighted coherent system, and provide a signature-based reliability representation for this system. Further, we study di?erent reliability importance measures for the components of a random weighted coherent system. We study the optimal allocation strategy of active redundancies and the optimal assembly method of random weights in a random weighted coherent system. By developing the results for random weighted coherent systems, we generalize many well-established results available for ordinary coherent systems and weighted coherent systems in the literature.
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    Development of Green Multicomponent Reactions, Cascade Reactions and Direct Oxidation: Efficient Strategies for the Synthesis of Biologically Active Organic Scaffolds
    (Indian Institute of Technology Jodhpur, 2023-11) Erande, Rohan D
    The development of green multi-component reactions as an efficient synthetic methodology for the construction of biologically active molecules have received great attention in the last couple of decades. However, organic scaffolds such as 2,3-dihydrofurans and 2,3-dihydrofuro[3,2-c]coumarins (DHFC), despite possessing an extremely wide range of biological activities were yet to be succumb in greener way. Following the nature's footsteps, herein we reported an eco-friendly, inexpensive, and efficient one-pot green multicomponent approach to synthesize trans-2,3-dihydrofuro[3,2-c]coumarins (DHFC) catalyzed by imidazole in water under mild conditions. Applications of the developed catalytic process under a multicomponent strategy in a greener medium revealed the outstanding activity, productivity, and broad functional group tolerance, affording a series of newly designed DHFC in excellent yields. In addition, the biological study that was carried out by the collaborative group demonstrates the ability of the sthesized DHFC derivatives to bind to human serum albumin (HSA). Detailed in silico and in vitro structure-activity analysis has been performed, covering all the bases of this biological investigation. Furthermore, the developed strategy was implemented to synthesize bioactive heterocycles, namely dimedone fused 2,3-dihydrofuran derivatives, under mild conditions with excellent yields, using imidazole and water as green catalyst and solvent, respectively. The synthesized dimedone based 2,3-dihydrofuran derivatives have been found to inhibit SaTR in vitro at low to medium micromolar concentrations. On the other hand, the indole alkaloids are known as an epic family of natural products with structurally diverse architecture and a wide range of biological activities. In line, a BF3.OEt2 catalysed cascade strategy for the synthesis of highly substituted pyrrolo[1,2-a]indole core with high diastereoselectivity has been developed. Further, biological evaluation of synthesized derivatives was reflected in their excellent bioactivity. Further, oxidation of polycyclic aromatic hydrocarbons (PAHs) found to be an important area belongs to the biochemistry, astrochemistry, and chemical industries. In line, we have developed the one-pot oxidation of naphthalene, anthracene, pyrene and substituted PAHs in the presence of H2O2 and newly designed [CuIIL] complex derived from non-toxic transition metal and ligand based redox-active PLY backbone, that provided a route for their detoxification and conversion into industrially important compounds. Furthermore, transforming the alcohols and aldehyde groups to esters via oxidative coupling with alcohols has become an attractive target for organic chemists, due to the significance and omnipresence of ester group in chemistry. Thus, a new-designed V-catalyst [(L2)VIVO](ClO4) was synthesized and utilized for its potential catalytic activity towards direct oxidation of two different functionalities, alcohols and aldehydes to their corresponding esters in one-pot procedure using H2O2 and alcoholic medium. Moreover, cinnamate esters transformed to ester (via C=C bond breaking followed by oxidation of in-situ generated aldehyde) in single-step, which is found to be the first ever report to this end.
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    Towards More Realistic Shock Models with Applications in Optimal Maintenance
    (Indian Institute of Technology Jodhpur, 2023-02) Hazra, Nil Kamal
    In this thesis we study some generalized shock models with applications in optimal maintenance. Most of the systems used in reality are directly or indirectly a↵ected by some harmful “instantaneous” events (shocks of di↵erent nature), which either cause the system’s failure or decrease the system’s lifetime. Thus, the study of systems’ lifetimes subject to external shocks is one of the important problems in reliability theory. In a shock modeling, one has to answer two important questions, namely, “how the occurrences of shocks a↵ect or decrease the lifetime of a system” and “how one can model the occurrences of shocks on a system ”. In this thesis, we answer these questions in di↵erent setups. Existing shock models are usually classified into four broad classes, namely, extreme shock models, cumulative shock models, run shock models and !-shock models. The !-shock model, which is an object of our study, is di↵erent in nature from other aforementioned shock models. In all !-shock models developed so far in the literature, the recovery time ! was assumed to be constant. However, this assumption is too restrictive and unrealistic in describing many real-life scenarios. Indeed, ! can obviously depend on other parameters, namely, magnitude of shocks, arrival times of shocks, etc. This motivates us to introduce a new time-dependent !-shock model wherein the recovery time of a system is assumed to be an increasing function of arrival times of shocks. For this model, we assume that shocks occur according to the generalized P´olya process (GPP) that contains the homogeneous Poisson process (HPP), the non-homogeneous Poisson process (NHPP) and the P´olya process as particular cases. We further generalize this model to the general !-shock model by considering the recovery time ! as the function of both arrival times and magnitudes of shocks. We also consider a more general and flexible shock process, namely, the Poisson generalized gamma process (PGGP) that includes the HPP, the NHPP, the P´olya process and the GPP as the particular cases. With the same motivation, we study a history-dependent mixed shock model which is a combination of the history-dependent extreme shock model and the history-dependent !-shock model. As an application of the aforementioned new shock models, we study the optimal replacement policy. Although Poisson processes are widely used in various applications for modeling of recurrent point events, there exist obvious limitations. Several specific mixed Poisson processes (which are formally not Poisson processes any more) that were recently introduced in the literature overcome some of these limitations. We define a general mixed Poisson process with the phase-type (PH) distribution as the mixing one. As the PH distribution is dense in the set of lifetime distributions, the new process can be used to approximate any mixed Poisson process. We study some basic stochastic properties of this new process and discuss some relevant applications by considering the extreme shock model, the stochastic failure rate model and the !-shock model. We introduce and study a general class of shock models with dependent inter-arrival times of shocks that occur according to the homogeneous Poisson generalized gamma process (HPGGP). A lifetime of a system a↵ected by a shock process from this class is represented by the convolution of inter-arrival times of shocks. This class contains many popular shock models, namely, the extreme shock model, the generalized extreme shock model, the run shock model, the generalized run shock model, specific mixed shock models, etc. For systems operating under shocks, we derive and discuss the main reliability characteristics and illustrate our findings by the application that considers an optimal mission duration policy. Counting processes based on heavy-tailed distributions (namely, the fractional homogeneous Poisson process (FHPP), the renewal process of matrix Mittag-Leffler type (RPMML), etc.) have not yet been considered in the literature for modeling the occurrences of shocks. Thus, we study some general shock models under the assumption that shocks occur according to a renewal process with the matrix Mittag-Leffler (MML) distributed inter-arrival times. As the class of MML distributions is wide and well-suited for modeling the heavy tail phenomena, these shock models can be very useful for analysis of lifetimes of systems subject to random shocks with inter-arrival times having heavier tails. Some relevant stochastic properties of the introduced models are described. Moreover, two applications, namely, the optimal replacement policy and the optimal mission duration are discussed. Lastly, we consider coherent systems subject to random shocks that can damage a random number of components of a system. Based on the distribution of the number of failed components, we discuss three models, namely, (i) a shock can damage any number of components (including zero) with the same probability, (ii) each shock damages, at least, one component, and (iii) a shock can damage, at most, one component. Moreover, the arrivals of shocks are modeled using three important counting processes, namely, the PGPP, the Poisson phase-type process (PPHP) and the RPMML. For the defined shock models, we study some reliability properties of coherent systems. At the end, we discuss the optimal replacement policy as an application of the proposed models.
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    Islanding and Faults Detection in Utility Grid Integrated With Solar Renewable Energy Source Using Signal Processing and Machine Learning Algorithms
    (Indian Institute of Technology Jodhpur, 2022-07) Yadav, Sandeep Kumar
    The interfacing of renewable energy sources (RES) with the utility grid due to the growing demand for clean and cost-effective energy poses new challenges like power quality disturbances, unintentional islanding, change in fault levels, and fault current directions. These unpredictable events pose a significant threat to the continuous supply of loads, the safety of the equipment and personnel involved and also cause considerable economic losses. Hence, the proposed schemes must be able to tackle these challenges and to detect faults and islanding conditions at the earliest. In addition to fault detection and classification, fault location in the distribution system is also a challenging task due to short feeders, complex topology, various laterals, unbalanced operation, and time-varying load profile. Various signal processing techniques such as Wavelet Transform and S-transform, have been employed to extract time-frequency information to detect islanding and fault diagnosis. Empirical Mode Decomposition (EMD) is reported to be adaptive and overcomes the limitations of Wavelet transform (suitable wavelet selection) and S-Transform (non-adaptive selection of Gaussian windows). This thesis proposes high-speed protection algorithms based on Empirical Mode Decomposition of three-phase current signals collected at the substation of a distribution network for detecting islanding and discriminating the same from faults. Fault classification and location have also been accomplished, followed by detection. The three-phase current signals collected at a substation over a moving window are decomposed using the EMD method to extract residues at various levels. These residues are utilized to detect the faults and classify them as LG, LL/LLG, and LLLG (L: line, G: ground). The discrimination between LL and LLG faults is achieved with the help of a neutral current. The first algorithm utilizes the absolute mean (AM) value and Standard deviation (SD) of the first-level residue obtained from EMD to compute fault indices to detect and classify various faults and islanding by comparing with a threshold value within a half cycle. After fault detection and classification, the features of SD and AM from first-level residues are fed to a decision tree (DT) machine-learning algorithm to locate the fault. This algorithm has been successfully tested on IEEE 13 and 34 bus systems with DG penetration in the presence of noise with 20 dB signal to noise ratio (SNR). The second algorithm proposed is based on a combination of EMD and Hilbert Transform (HT), widely known as Hilbert-Huang Transform (HHT), which extracts instantaneous features like instantaneous frequency (IF), instantaneous amplitude (IA), Standard deviation of instantaneous frequency (SDIF), and standard deviation of instantaneous amplitude (SDIA) from the first level residue. A fault index computed based on SDIF is proposed to detect and classify the faults within a quarter cycle by comparing it with a predefined threshold without DG penetration. A machine learning algorithm is proposed to avoid multiple thresholds in the event of DG penetration that requires islanding detection. The instantaneous features are fed to DT to classify faults and islanding. Also, the faulty zone is located using various ML models to evaluate their performance with varying capacities of DG using quarter cycle post-fault data (PFD) in the presence of noise. In third algorithm, image-based fault diagnosis is accomplished by generating unique symmetrical dot patterns (SDP) with the help of monotonic residue after EMD. A novel protection algorithm based on SDP has been proposed with the alienation coefficient of SDPs after a fault and normal conditions as fault index to achieve fault detection and classification. These SDPs, when fed to Convolutional Neural Network (CNN), removed the feature extraction process involved in distribution system fault diagnosis. The proposed algorithms have been successfully tested by varying the type of fault, fault incidence angle, fault resistance, and fault location in the presence of noise. The selectivity of the proposed algorithms has been established by testing with non-faulty transients such as transformer excitation and de-excitation, feeder energization and de-energization, load switching, capacitor switching, and DG tripping in the presence of noise. Thus, the proposed algorithms using a combination of signal processing and machine learning methods can be implemented efficiently for the online monitoring of distribution systems.
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    Study of Organic and Quantum Dots-Based Resistive Memory and Synaptic Devices
    (Indian Institute of Technology Jodhpur, 2023-09) Sahu, Satyajit
    The data storage requirement in the digital world is increasing day by day with the advancement of the Internet of Things (IoT). The current generation of silicon-based memory technology is facing serious problems in terms of performance, data storage density, power consumption, data processing time, cost-effectiveness, and so on. Conventional flash memory is one type of non-volatile memory that relay on tunneling through the oxide layer, consumes high power, and response time is high. The hard disk drive (HDD) is a widely used memory in the current era, but the main disadvantage is finding the particular magnetic domain where the data is saved, which leads the memory response time to a few milliseconds. The limitations of conventional memories can be tackled by next-generation memories. Ferroelectric random access memory (FERAM), Phase change memory (PCM), Magnetic random access memory (MRAM) and Resistive random access memory (RRAM) are considered as next-generation memory and have the potential to solve the problem. Among the other memories, non-volatile RRAM is an option that provides high-density and low power data storage capabilities. The information is stored in terms of resistance, where the high resistance state (HRS) is 0 bit, and the low resistance state (LRS) is 1 bit. The computers are based on von Neumann architecture, where processor units are separated from the memory unit and connected via a data bus. This causes a delay in response time and cannot go beyond a certain size limit, called von Neumann bottleneck. The current resistive memory has the capability to solve the von Neumann bottleneck, where the memory can simultaneously process and store data similar to the biological brain. The small molecule-based RRAM device is a point of interest because of its capability to be used in high-density data storage devices. A small organic molecule 5-Mercapto-1-methyl tetrazole (MMT) has been used with a polymer poly (4-vinyl pyridine) (PVP) matrix for the active layer of RRAM device. The MMT molecule with a different weight ratio in PVP was studied for RRAM application which reveals the invariant RRAM property. The maximum on?off current ratio for all the devices is 105, suggesting that the MMT molecule does not show any change in its characteristic properties when surrounded by an insulating material. When the device was fabricated without the polymer matrix, the surface morphology of the device completely changed as it was filled with large holes. These holes provide short-circuited pathways for the current by forming the direct metal contact between the top and bottom electrodes. Size miniaturization of the electronic device can be done using organic small molecules as well as inorganic nanoparticle QDs. The synthesis of CdS QDs and the study of RRAM properties has been studied. Al/CdS+PVP/ITO like MIM structured device was fabricated which shows extremely good switching properties. The data retention capability of 60000 seconds and 300 endurance cycles were studied. The charge-trapping mechanism is associated with the RS property. With the development of artificial intelligence and ultra-high speed computing the solution of von Neumann bottleneck is needed. In this regards, resistive memory can provide solution as RRAM has the capability to act as biological synapse that can store, process and transfer data. This attracts researchers to study resistive memory devices. Here fabrication of a small organic molecule Trimesic acid (TMA) and PVP composite-based resistive memory device. It shows excellent resistive switching with a high on-off ratio, excellent stability and data storage capability. Pulse transient measurements on the device demonstrated the capability of neuromorphic computation. The gradual set and reset process and change of conductance with an applied pulse confirmed the neuromorphic application. Paired pulse facilitation shows that the device can behave like the human brain. The redox active molecule and its change in conformation are the reasons for the switching behaviour of the device th led to the neuromorphic application of the device. For an important application like RRAM, it is crucial to understand the mechanism in nanoscale and control the Resistive switching (RS) by various means. Different models have been proposed to explain the RS behaviour of the material. First, the electrode effect on the switching, which includes contact type, and charge trapping/de-trapping near the electrodematerial interface. The other mechanisms are conducting filament formation, electrochemical metallization, ionic diffusion, and oxidation-reduction of the materials. So, there are many disagreements on the proposed models of RS, and it requires understanding using different experimental techniques. STM is one of the best tools for understanding the surface property, as well as studying the local density of states (LDOS) of the material. So, using the scanning tunnelling microscopy (STM) technique to understand the RS in materials in the nanoscale range would be very helpful. The RS properties and capabilities of neuromorphic computing of single AgInS2 quantum dot with the help of STM and scanning tunnelling spectroscopy (STS) have been studied in this chapter. The bandgap of the material and its temperature dependency has been studied and it suggests a nonlinear and linear variation at lower and higher temperature than the Debye temperature respectively. The STS shows the change of conducting states after applying localized pulses. The devices made from the quantum dots replicate these properties as well. The neuromorphic application of the device was tested by using the pulse transient measurement that mimics the learning and forgetting of information through the gradual set and reset process. The localized ionic transport is involved in the RS mechanism.
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    Development of metal oxide based formaldehyde (HCHO) sensors using laser ablated nanoparticles
    (Indian Institute of Technology Jodhpur, 2023-07) Kumar, Mahesh| |Singh, Jitendra
    In this thesis, first time, we reported a state-of the art method for the synthesis of metal oxide nanoparticles in atmospheric air using laser ablation techniques for the rapid prototyping of formaldehyde (HCHO) gas sensor. Formaldehyde gas is most common indoor air pollutants which causes various adverse human health problems if its limit goes above 0.75 ppm as per OSHA (Occupational Safety and Health Administration (OSHA), USA) guidelines. It is also noticed that some dishonest fish merchants are using formalin solution (formaldehyde gas dissolved in water) to preserve freshly caught fish during their transportation to the fish selling market to prevent the spoilage. So, various health issues have been occurred due to the ingestion of formalin contaminated fish. Thus, we need a miniature, low cost, ultra-low sensitive formaldehyde sensor for the development of smart or IoT enabled portable system for the measurement of formaldehyde gas level in indoor area and as well, their presence in fish. Micro hotplate is an essential part of any metal oxide based gas sensors. Hence, in the first part of the study, co-planner Au microheater based gas sensor platform was fabricated by laser micropatterning using a 355 nm Q-switched solid state laser source. The heat distribution profile of the fabricated micro hotplate was observed via IR thermal imaging camera. Furthermore, the long-term reliability, power versus operating temperature of the microhotplate were systematically studied. In addition with this, heat distribuiton profile of a Nichrome heater based gas sensor platform having a hollow alumina tube on which two gold electrodes had been printed at each end, was also investigated. The next set of analysis, the formaldehyde gas sensing performance was studied using pristine SnO2 and ZnO metal oxide materials. Formaldehyde gas sensing behaviour was studied by depositing thin film of SnO2 layer onto the external surface of alumina tube based gas sensor platform. The sputtered deposited SnO2 thin film sensor exhibited gas response of 1.2 towards 1 ppm of formaldehyde vapor with a response time of ? 32 s and a recovery time of ?72 s at 300°C. Next, to explore the formaldehyde sensing capabilities of nanoparticles, we have synthesized pristine ZnO nanoparticles by scanning a high power laser beam on the top surface of ZnO pellet in open air atmosphere and the laser-ablated ZnO NPs were directly deposited onto the alumina tube based gas sensor platform. The gas-sensing properties of the ZnO NPs has been carefully investigated in the presence of formaldehyde gas molecules. ZnO NPs-based sensor exhibited the response of about 1.8 towards 50 ppm formaldehyde gas at 350°C with response time 25 s and recovery time 12 s. To further enhance the sensitivity and selectivity towards formaldehyde gas, we have fabricated n-ZnO/n-SnO2 n-n heterojunction by combined processes of physical vapor deposition (PVD) by sputtering SnO2 thin film on the alumina tube based gas sensor platform and decorated it with ZnO nanoparticles. After decoratif laser ablated ZnO nanoparticles on thin film SnO2 sensor, it exhibited high response of 20 towards 50 ppm of formaldehyde with quick response (4 s) and recovery time (30 s) at lower operating temperature (250°C) compared to that of pure SnO2. After obtaining good results from the previous investigations with heterojunction, the present research has further been extended. The p-type NiO NPs were synthesized in atmospheric air by laser ablation of cylindrical shaped solid Ni pellet. We have fabricated p-NiO/n-SnO2 p-n heterojunction via decoration of laser ablated NiO nanoparticles over sputtered deposited n-type SnO2 thin film. We have explored the formaldehyde sensing behaviour of NiO/SnO2 sensor and compared with pristine SnO2 senso. The NiO/SnO2 sensor exhibited higher response of about 29.8 towards 50 ppm formaldehyde with fast response and recovery time (3 s and 90 s) at lower operating temperature (about 210°C) with good selectivity. In the last part of the thesis, enhanced formaldehyde sensing mecsm of ZnO/SnO2 and NiO/SnO2 sensors has been described. From the experimental gas sensing performance data of NiO/SnO2 sensors, we have also extracted the various gas sensing parameters such as response time (??res), recovery time (??rec), surface coverage (??), adsorption (Ka) and desorption rate constant (Kd) using Langmuir gas adsorption-desorption model via curve fitting method.
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    Tin Oxide Based Nanomaterials for Gas/VOC Sensing
    (Indian Institute of Technology Jodhpur, 2023-09) Gupta, Ritu
    Extensive usage of toxic, flammable, and explosive Volatile Organic Compounds (VOCs)/ gases in industry induces tremendous environmental pollution leading to a threat to living organisms. Therefore, there is a requirement for continuous monitoring of VOCs/gases using cost-effective, highly selective, sensitive, environmentally stable sensors. So, our work focuses on different approaches to modify the SnO2 for developing low-temperature operable humidity tolerant VOCs/gases sensors. NO2, the most common toxic gas, induces various respiratory diseases even for short-term exposure at a low concentration of 5 ppm. Thus SnO2-rGO is synthesized at optimized conditions by the solvothermal method. In the SnO2-rGO nanohybrid device identified through a combinatorial approach, optimum morphology and structure along with the intrinsic Sn-C bond exhibited a significant response of ~3 to a low concentration of 80 ppm NO2 at room temperature operation and fluctuating humidity (20-50% RH) at much faster speeds ~5.6 s and recovered quickly in 14.1 s without heating. Xylene, one of the components of cigarette smoke, is a major contributor to indoor pollution and induces various respiratory diseases. We synthesized Sn-SnO2 as a sensing material with unique mesoporous nano-spherical morphology, providing a high specific surface area for Volatile Organic Compounds (VOCs)/gases adsorption. The sensor exhibits a repeatable response of 255% at 60 ppm xylene at room temperature with unprecedented ultrafast response and recovery time of 1.5 s and 40 s, respectively. The concentration of NH3 in the exhaled breath of healthy persons is about 0.4–1.8 ppm, while that in end-stage renal disease patients is around 0.8–14.7 ppm. Hence, disease state monitoring and environmental exposure assessment applications demand highly sensitive, faster, and more selective NH3 sensors that can operate under various environmental conditions. In our study, we synthesized SnO2 nanosheets using a solvothermal method and carefully optimized the pH conditions of the precursor solution for tuning the size, crystallinity, and thickness. The sensors fabricated using these samples exhibited a selective response to ammonia at 25 ºC and relative humidity (RH) of 70%. The pH 14 device demonstrated the highest sensitivity to ammonia (150% at 100 ppm) with fast response (8 s) and recovery kinetics (55 s). A theoretical LOD of 64 ppt implies superior sensitivity to all previously reported SnO2-based chemiresistive sensors. Triethylamine becomes explosive at concentrations above 10 ppm in the air and can induce headaches and difficulty breathing as well. The optimized substitutional fluorine doping in SnO2 film results in high conductivity, hydrophobicity, transparency, reduction in oxygen defects, and excellent electrochemical stability. Consequently, the fabricated F-SnO2 sensor showed a humidity-resistant nature with the highest response of 52% towards triethylamine at a relatively low operating temperature. Thus, the gas and VOC sensors developed in this work can be deployed for real-time sensing after miniaturization and integration with the AIoT platform.
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    Cascade Synthesis of Diverse Heterocycles
    (Indian Institute of Technology Jodhpur, 2023-06) Rana, Nirmal K.
    Heterocycles are the largest and most diversified families of organic compounds. They play significant roles in chemical synthesis as well as in bio-chemistry. Therefore, developing innovative and efficient methodologies for synthesizing multifunctional heterocyclic compounds, with the goal of achieving higher molecular complexity and improved functional group compatibilities from readily available starting materials under mild reaction conditions, is a significant area of today's research. Cascade approaches have long been acknowledged as they provide an admirable collection of strategies and tactics for developing novel and efficient routes with a minimum number of operations for synthesizing complex molecules. These classes of reactions represent not only the multiple bond-forming transformations but also the subsequent reactions in which the functionalities created in the earlier steps are manifested. One-pot approaches are used to increase the overall efficiency of processes by reducing physical efforts well as minimizing the use of solvents and chemicals. On the other hand, the use of supported catalysts/reagents has revolutionized the field of chemistry. The immobilization of the catalyst onto a solid support material prevents its loss during the reaction, increases its surface area, and enhances its selectivity and efficiency. It is an attractive field of research in organic synthesis due to several advantages over traditional catalysts/reagents i.e., simplified product purifications, reusability, reduction of side products, less waste generation, and economic process. These make the process more sustainable and greener as well. In this thesis, the research work encapsulated, is focused on the development of novel and sustainable cascade approaches towards the synthesis of diverse heterocyclic compounds. The thesis is divided into six chapters. Chapter 1 presents the importance of heterocycles and summarized the advancement of organocatalyzed methods towards the construction of diverse heterocycles such as tetrahydrothiophene, ?-pyrones, dihydroindoles and benzoxazoles. Next, we have discussed the objectives, scope and the structure of the thesis. Chapter 2 includes polymer-supported base-catalyzed synthesis of sulfur-containing heterocycles, trisubstituted tetrahydrothiophenes and spiro-thiazolone-tetrahydrothiophenes, via thia-Michael/aldol cascade approach. Chapter 3 deals with the synthesis of oxygen-rich heterocycles, ?-pyrones, through polystyrene-linked DMAP-catalyzed Michael-addition/lactonization/elimination reactions. In chapter 4, nitrogen-containing heterocycles, dihydroindoles, were synthesized utilizing supported-pyridinium ylide and sulfur ylide as a C-1 synthons. Chapter 5 represents the development of novel approach for the construction of 2-aryl benzoxazoles. These compounds seem to have potential activities as agonists for the biogenesis of utrophin. In the last chapter, we have concluded the thesis with future scope
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    Secrecy Analysis and Performance Improvement of FSO Communication Systems
    (Indian Institute of Technology Jodhpur, 2023-10) Mathur, Aashish
    Optical wireless communication (OWC) is a promising alternative solution to tackle the issues of spectrum scarcity and traffic congestion. The term OWC is defined as the transmission in an unguided propagation medium using optical carriers in the visible, infrared, and ultraviolet frequency bands. Outdoor terrestrial or free space optical (FSO) communication is one of the categories of OWC, which deals with the data transmission between two fixed points over several kilometers using optical carriers. FSO communication systems have many advantages, such as huge license-free bandwidth, high data rate, low latency, cost-effectiveness, and quick deployability. Despite the aforementioned merits, the performance of FSO systems is limited by atmospheric turbulence (AT), pointing errors (PEs), path loss, geometric loss, and background radiation. Conventionally, FSO systems utilize intensity modulation/direct detection (IM/DD) due to the low cost and ease of implementation; on the other hand, the heterodyne detection (HD) technique has a higher cost and is relatively difficult to implement, but it provides improved communication performance. FSO communication is inherently more secure than radio frequency (RF) communication because the optical beams are more directional than the RF beams, thus FSO communication systems are less subject to eavesdropping/intercepting. However, optical beams can still be intercepted particularly when the eavesdropper is close to the legitimate receiver or lies within the divergence angle. In recent years, the research on secrecy performance analysis has increased significantly. We evaluate the exact closed-form expression of the average secrecy capacity (ASC) and secrecy outage probability (SOP) under the composite effect of the generalized Malaga distributed AT and non-zero boresight PEs in this thesis. Through the detailed asymptotic analysis, it is revealed that the secrecy diversity order depends on the minimum of the main link parameters of the FSO system for the respective detection technique (HD or IM/DD). We incorporate hybrid-automatic repeat request (H-ARQ) in the FSO communication systems to improve their performance and communication link reliability. H-ARQ technique combines strong channel coding with retransmission request protocols to improve FSO system reliability. We derive novel closed-form expressions for the outage probability of the FSO systems under the combined impact of Gamma–Gamma distributed AT and PEs for HD and IM/DD techniques. We compare the FSO system performance for different H-ARQ protocols, such as at least once (ALO), chase combining (CC), and incremental redundancy (INR). Further, we calculate throughput for the FSO systems by utilizing outage probability expressions for the mentioned H-ARQ protocols. We also conduct an extensive asymptotic analysis for different H-ARQ protocols which reveals that the achieved diversity gain is the product of the number of transmission rounds and the minimum of the link parameters for the respective detection technique. To further enhance the FSO system coverage, we consider a mixed dual-hop FSO-RF communication system. The considered dual-hop FSO-RF communication system serves the end user via a decode and forward (DF) relay employing H-ARQ protocols on both hops. The intelligent reflecting surface (IRS) has been utilized on RF links for their merits, such as the capability to provide greater coverage, improved spectrum, and energy efficiency. We derive the outage probability and packet error rate (PER) of the proposed system by considering generalized detection techniques such as HD and IM/DD on the source-to-relay (S−R) link with H-ARQ protocol and IRS having phase error. The inclusion of IRS phase error in our analysis is essential for closely emulating a practical system model. To obtain more fruitful insights into the FSO communication systems, we develop an experimental setup of a 10 Gigabits/second (Gbps) FSO communication system in a laboratory-controlled environment. An AT chamber is designed to introduce the effects of turbulence, fog, and heat onto the transmitted signal. We experimentally evaluate the bit error rate (BER) and the received power profile fluctuations in the presence and absence of AT. Further, we also demonstrate the effect of heat and fog on the received power profile. Additionally, we exemplify the role of cyclic redundancy check (CRC) to mitigate the deteriorating effects of atmospheric conditions on the FSO link. We found that the BER values of approximately 4×10−8 at received powers of -19.29 dBm and -16.98 dBm are achieved for the framed and the unframed data, respectively, and the power gain is around 2.31 dB. This experimental result demonstrates that the BER performance of FSO systems can be improved with the use of CRC bits.
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    Education for the Embodied Human: An Enquiry into Human Nature and Education
    (Indian Institute of Technology Jodhpur, 2023-02) Hari Narayanan V
    The present work is a philosophical inquiry concerning the interconnection between theories of human nature and education. It is often argued that the current mainstream education has an underlying dualistic assumption that the mind-body and the human-world are distinct and, therefore, do not value embodied forms of knowing. This dualistic notion creates a rift between learners and their environments, substantially impacting their learning. It also results in an exam-oriented and achievement-based education system that is not conducive to developing children's critical thinking and an exploratory mindset. One major factor that gives rise to this condition is an inadequate understanding of human nature. It is evident that any educational activity presupposes one or another conception of human nature because a particular philosophy of human nature shapes and influences a particular philosophy of education. Therefore, understanding human nature is of paramount importance for designing or transforming education. An examination of several theories of human nature reveals that they are mostly the result of philosophical speculation and have underlying dualistic assumptions. However, recent empirical studies in cognitive science suggest that human beings are fundamentally embodied and embedded in the world. Being embodied means the mind is not separate from the body and the world, but it is dynamically coupled with both. Now, if human beings are fundamentally embodied, then education should also acknowledge this fact in its practices. But even though there is increasing evidence available in support of embodiment, we do not sufficiently appreciate it in our day-to-day lives or in educational discourse. This is the result of various psychological, neurological, and socio-factors. To address this problem, a two-way approach is presented, which is termed as the outer and inner curriculum. The outer curriculum employs an "outside-in" approach, in which pedagogies are designed and imparted as per embodied principles. However, only changing external pedagogies will not help much without realizing our own embodied nature. For this purpose, an inner curriculum is required to make changes "inside out". The inner curriculum fundamentally helps us to realize our own embodied nature, which has got significant salutary effects. Therefore, the inner curriculum is seen as complementary to the outer curriculum. The core content of the inner curriculum is mindfulness meditative practices, which help us to become self-aware of our thoughts and sensations, which in turn helps to embrace our own embodied nature and inextricable relationship with the world. This kind of embodied approach to education, having a focus on both outer and inner curricula, helps to create a more democratic, collaborative, and holistic learning environment, thereby fulfilling the vision of educational thinkers such as John Dewey, Paulo Freire, and Jiddu Krishnamurti.
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    Molecular Strategies Based Elevation of Protein Quality Control Mechanism: Rejuvenate Aberrant Proteins Aggregation Linked Defective Proteostasis
    (Indian Institute of Technology Jodhpur, 2023-11) Mishra, Amit
    Generation of new proteins and removal of damaged or old polypeptides is an uninterrupted mechanism essential for a healthy cellular environment. Impairment in the removal of misfolded proteins can disturb proteostasis; such toxic aggregation of misfolded proteins can act as a preliminary causative agent for neurodegenerative disorders and imperfect aging. Therefore, removal of such abnormal aggregates can ensure the re-establishment of proteostasis; the ubiquitin-proteasome system (UPS) actively participates in the specific clearance of aberrantly folded clients with the help of complex proteasome machinery. The critical challenge is to design effective protein quality control (PQC) based molecular tactics that could potentially eliminate aggregation-prone protein load from the cell. E3 ubiquitin ligases impart ability for identifying unique critical misfolded protein clients for targeting them towards proteasomal degradation. Several neurodegenerative and neurodevelopmental disorders are known to have compromised functioning of specific protein quality control E3 ubiquitin ligases. The work presented here involves use of Itraconazole and Resveratrol to improve critical protein quality control functions of the cell in order to improve the removal of toxic abnormal protein aggregates thus, increasing cellular resistance towards proteotoxic stress mechanisms. The results demonstrate specific potentials of Itraconazole to enhance proteasome activity for increasing the clearance of various model and neurodegeneration causative abnormal proteins. Furthermore, Resveratrol exposure was found to significantly enhance the LRSAM1 E3 ubiquitin ligase, found mutated during spongiform neurodegeneration, levels in the cell. The expression levels of LRSAM1 were also found to influence the proteasome chymotrypsin-like and post-glutamyl peptidyl-hydrolase like functions. Resveratrol being a plant based stilbenoid compound was able to stop the occurrence of toxic proteinaceous species in the cell. The present work implicates the potential of improving protein quality control as significant therapeutic measure against several protein aggregation-based disorders. Moreover, specific potentials of upregulating proteasome and quality control E3 ubiquitin ligase functions by Itraconazole and plant derived Resveratrol can help to increase cellular cytoprotection
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    From primary microcephaly-associated CPAP as centriole size/number regulator to microtubulestargeting novel chemotype
    (Indian Institute of Technology Jodhpur, 2023-07) Singh, Priyanka
    Centrioles are cylindrical microtubule-based structures, embedded in a proteinaceous matrix called pericentriolar material (PCM). Together, this structure is referred as the centrosome. In animal cells, the centrosomes play a crucial role in cellular functions such as cell division and motility. Abnormalities in centrosome-associated proteins have been linked to human diseases, including cancer and neurodevelopmental disorders. Mutations in the core centriole protein, Centrosomal P4.1-associated protein (CPAP), have been associated with primary microcephaly (MCPH6), a disorder characterized by reduced brain size and cognitive disability. This study focuses on understanding the impact of CPAP mutations on centrosome and spindle organization in primary microcephaly. Specifically, it investigates the effects of two MCPH-associated mutations, E1235V and D1196N, in the CPAP G-box domain. The study reveals that E1235V causes increased centriole length, while D1196N leads to an increase in centriole number. Interestingly, E1235V does not localize at the centriole, whereas D1196N maintains its centriolar localization despite reduced interaction with the upstream centriole protein, STIL, similar to E1235V. This suggests the involvement of an alternate route involving the proximal parent centriole protein, CEP152. Moreover, we demonstrate that centriole abnormalities result in multipolar spindle formation and decreased cell viability. These findings shed light on the importance of regions within CPAP outside the direct microtubule-interacting domains in influencing centriole organization, providing valuable insights into the molecular mechanisms underlying primary microcephaly. The second part of the thesis work explores the development of novel chemical scaffolds for chemotherapeutics. The cell division machinery, comprised of centrosomes and microtubules, is crucially regulated during the cell cycle. Dysregulation of these structures can lead to human diseases, including cancer. Paclitaxel, a microtubule-targeting anticancer drug, has clinical approval but faces challenges due to the development of resistance in many cancer types. Hence, there is a need to identify new chemical scaffolds for designing effective anticancer drugs. In this study, a novel S-aryl dithiocarbamate chemical scaffold is identified as a potent anticancer compound with promising pharmacophore properties. The lead compound exhibits an I*C_{50} of <0.5 µM in lung and cervical cancer cells. It stabilizes microtubules, resulting in p53-p21-dependent cell cycle arrest in the G_{2} / M stage and cellular apoptosis. Interestingly, the lead compound shows comparable docking parameters to paclitaxel in the taxol-binding pocket of ẞ-tubulin. These findings present a promising alternative scaffold that can be further modified to enhance efficacy and potency as an anticancer drug.
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    Role of Scene text in Image Semantics
    (Indian Institute of Technology Jodhpur, 2022-08) Harit, Gaurav
    Since the advent of the printing press, text has slowly made inroads into the world we have built for us. The symbolic nature of text allows it to explain ideas more succinctly. Thus scene text content is often naturally occurring in images ( street or storefront images). Further, they are also embedded into images to drive home clear takeaway points (e.g., printed posters, advertisement images). In both cases, though, they bring in crucial contextual information that aids in interpreting such images. However, despite this pervasion of scene text in our everyday images [Dey et al., 2021] and the rich information source they entail, early works in visual understanding tasks like Image Classification, Captioning, and Visual Question Answering (VQA) [Antol et al., 2015] did not leverage the scene text content of images. This can be attributed to the challenges of detecting and recognizing scene text in the wild. However, maturing research in Scene text recognition has improved their ability to read the text in natural images, thus making the scene text content more accessible. This easy accessibility of scene text content, coupled with the recent advances in multimodal architecturesHu et al. [2020], provides a unique opportunity to incorporate scene text into visual understanding tasks. As our first point of the investigation [Dey et al., 2021], we propose to jointly use scene text and visual channels for robust semantic interpretation of images. We not only extract and encode visual and scene text cues but also model their interplay to generate a contextual encoding with rich semantics. The contextual encoding thus generated is applied to retrieval and classification tasks on multimedia images with scene text content, to demonstrate its effectiveness. In the retrieval framework, we augment the contextual semantic representation with scene text cues to mitigate vocabulary misses that may have occurred during the semantic embedding. To deal with irrelevant or erroneous scene text recognition, we apply query-based attention to the text channel. We show that our multi-channel approach, involving contextual semantics and scene text, improves upon the absolute accuracy of the current state-of-the-art methods on Advertisement Images Dataset by 8.9% in the relevant statement retrieval task and by 5% in the topic classification task. Our results confirm our initial hypothesis that scene text plays an essential role in the semantic understanding of images. These results encourage us to extend our framework to more challenging tasks, like Text-VQA Singh et al. [2019a], that explicitly require us to read and reason with the scene text of an image. However, the scene text words come from a long-tailed distribution, giving such tasks zero-shot characteristics. We hypothesize that the zero-shot nature of these tasks can benefit from leveraging external knowledge corresponding to the scene text. The open-ended question answering task of Text-VQA often requires reading and reasoning about rarely seen or completely unseen scene text content of an image. We address this zero-shot nature of the task by proposing the generalized use of external knowledge to augment our understanding of the scene text. We design a framework Dey et al. [2022] to extract, validate, and reason with knowledge using a standard multimodal transformer for vision language understanding tasks. Through empirical evidence and qualitative results, we demonstrate how external knowledge can highlight instance-only cues and thus help deal with training data bias, improve answer entity type correctness, and detect multi-word named entities. We generate results comparable to the state-of-the-art on three publicly available datasets under the constraints of similar upstream Optical Character Recognition (OCR) systems and training data. Through our experiments, we observe that this external knowledge not only provides invaluable information about unseen scene text elements but also augments the understanding of the text in general with detailed verbose descriptions. Our knowledge-enabled model is robust to novel text, predicts answers with improved entity type correctness, and can even recognize multi-word entities. However, the knowledge pipeline is susceptible to erroneous OCR tokens, which can lead to false positives or complete misses. This also explains how our performance on the datasets is correlated with the particular OCR systems used. Our investigation highlights the challenges and benefits of incorporating scene text into image understanding tasks. We validate our various hypotheses through empirical evidence across five different publicly available standard datasets. We conclude with a discussion on the implicit bias in these datasets for scene text, and propose data augmentation and a novel training scheme to deal with it.
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    Development of Computational Methods for Multi-omics Data Analysis
    (Indian Institute of Technology Jodhpur, 2022-07) Paul, Sushmita
    Holistic understanding of human health and disease demands interpretation of molecular complexity and variations at multiple levels such as the genome, epigenome, transcriptome, proteome, metabolome, and others. High-throughput technologies have revolutionized medical research. The field of biology has become increasingly dependent on data generated at the above mentioned levels, which together is called �multi-omics� data. An abundance of multi-omics data has transformed the discipline of biology and medicine and generated opportunities for integrated system-level approaches. Multi-omics studies are based on data-driven scientific interrogations that help analyze a wide range of multi-dimensional datasets at various levels that can be scaled to unravel cellular complexity. With the advancement in high-throughput technologies, cancer research has also observed a paradigm shift toward multi-omics approaches, expanding initiatives in comprehensive research collaboration and progression of computational pipes and algorithms. An in-depth understanding of cancer�s pathological phenotype can only be achieved by adequately integrating the myriad of related biological information. Cancer genomics programs like The Cancer Genome Atlas have generated a considerable amount of multi-omics data for multiple cancer types that can be utilized for the analysis. Therefore, the thesis aims to develop computational algorithms that utilize more than one omic data at a time to understand the etiology of cancer. The thesis�s two principal objectives are (1) To identify miRNA-mRNA regulatory modules in cancer and (2) To identify cancer subtypes. The computational objectives associated with these biological objectives are (1) Simultaneous clustering of miRNAs and mRNAs (clustering of features) whose expression is measured across the same set of cancer patients and (2) Clustering of cancer patients (clustering of samples) by integrating multiple levels of biological information coming from different omic platforms. Multi-omics ination and clustering have the potential to uncover subsequent systems-level knowledge but raise biological and computational challenges. The major challenges associated with multi-omics integration and clustering are (a) Selection of informative, appropriate, and meaningful omics (aligned to the biological objective) for the integration task. (b) Capturing the regulatory interactions between the multi-omics layers that can reflect the holistic nature of multi level data. (c) Careful handling of data heterogeneity across the omics having different distributions. (d) The problem of high-dimension low sample size, a situation where the variables significantly outnumber samples, leading to model overfitting. (e) Avoiding the transmission of redundant and noisy information from the individual omics while multi-omics integration. The computational approaches proposed in this thesis address the above issues and integrate multi-omics data for miRNA-mRNA regulatory module identification and cancer subtyping. The approaches designed in this study are based on four paradigms, specifically, Simultaneous clustering, Feature weighting-assisted information fusion, Subspace-based multi-kernel information fusion, and Latent space-based information fusion. The simultaneous clustering algorithm groups co-expressed miRNAs and mRNAs together into a module. An optimization function is designed to simultaneously maximize the relevance between a miRNA and an mRNA and the functional similarity between a module�s mRNAs. The feature weighting-assisted information fusion approach integrates transcriptomics data to identify cancer subtypes. The method assigns a weight to every biomarker prior to data integration and sample clustering. The weights take care of the inherent variance present in each transcriptomics data and are further utilized to calculate sample similarities. The impact of weights on the sample similarity network is observed during sample stratification when homogeneous groups of cancer patients are identified having distinished molecular characteristics. The subspace-based multi-kernel integration approach utilizes two graph-based representations for each omic data to capture the inherent data heterogeneity. It captures the best possible synergism between multiple representations using heuristics. Later, relevance-based integration of the synergistic graphs is performed to combine the multi-omics information and sample clustering. The recursive multi-kernel integration is performed to combine only the relevant and de-noised subspace. Here, relevant subspace refers to that subspace of the matrix that purely encodes the cluster information, which in the case of synergy matrix is its eigenspace corresponding to best eigenvalues. The latent space-based information fusion approach performs early integration of multi-omics data for sample clustering. Dimensionality reduction and simultaneous data integration are performed by learning neural networks in an unsupervised setting. It helps to create an information bottleneck by capturing the non-linear relationships in the data and denoising them simultaneously. The compressed integrated data representation holds the global cluster structure that is explored for sample clustering.
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    Realization and Stability Analysis of Perovskite Oxide-Based Thin Films for Memory Applications
    (Indian Institute of Technology Jodhpur, 2023-03) Kumar, Mahesh
    In the past few decades, with the rapid digitalization and extensive use of the internet of things and artificial intelligence, non-volatile memories have received a lot of attention for their use in electronic devices and logic storage units as current silicon-based memories are hitting the downscaling limits. In such a scenario, resistive switching random access memory (RRAM) seems to be a good candidate for the next-generation memory technology due to its low power consumption, high-density integration, and fast switching operation. Resistive switching random access memory has been studied for different types of memory characteristics such as write once read many (WORM), dynamic random-access memory (DRAM), and flash memory. Various perovskite oxides have been investigated for memory applications and neuromorphic computing. This work includes the synthesis of perovskite oxides like Barium Titanate (BaTiO3 i.e., BTO), Strontium Titanate (SrTiO3 i.e., STO) and Lanthanum Orthoferrite (LaFeO3 i.e., LFO) using solid-state reaction method, deposition of thin films and device fabrication for memory applications. BTO is a very well-explored ferroelectric material for different applications. Initially, we synthesized the BTO powder to prepare a sputtering target. We deposited the BTO thin film on FTO coated glass substrate using RF sputtering. The circular silver (Ag) top contacts were deposited to form memory cells to analyze the resistive switching properties. The Ag/BTO/FTO devices were characterized to optimize the thickness of the BTO layer in the memory device using BTO layers of different thickness. The memory characteristics are investigated as a function of the thickness of the amorphous-BTO layer, which is determined by varying the deposition time. Devices with all deposited thicknesses show data retention for more than 4000 seconds and 300 reading cycles. We get a high on-off ratio of the order of 106 of the devices having a thickness of 180 nm. The fabricated WORM devices exhibit good reading endurance and data-retention characteristics. Further, the switching performances are investigated for different devices with different deposition temperatures, varying from room temperature (RT) to 450°C. All the devices are characterized for a voltage sweep of ?1.5 V to 1.5 V with 12,000 pulses for retention and 300 write-read erase read cycles. Shifting in the switching voltage to a lower value from 1.31 to 0.49 V (450°C) is recorded with the increased deposition temperature. To verify the radiation stability of BTO thin film WORM devices, we irradiated the RT-deposited 180 nm BTO thin film with a different fluence of Ar+6 ions. The characterizations show a negligible shift in forming voltage and read current after irradiation which confirms that the BTO WORM devices show very high tolerance towards radiation and can be used in a harsh atmosphere. RRAMs have been explored for a long back due to their potential to replace the existing non-volatile memory technologies. We synthesized SrTiO3 (STO) for the realization RRAM using these layers. The SrTiO3 based RRAM devices were exposed to swift heavy ions and the stability and performance of the devices were analyzed. We observed a reduced memory window with reduced read current. The abrupt switching behaviour of the devices change to soft switching as the fluence of Au ions increased. Further, the LFO thin film-based memory devices were investigated for RRAM characteristics and synaptic behaviour analysis. The LFO powder was synthesized using a conventional solid-state reaction method to prepare the sputtering target. Ag/LFO/FTO structures were fabricated and investigated for RRAM for different thickness and deposition temperatures of LFO thin film. The resistive switching properties are investigated using macroscopic I?V measurements, showing low voltage switching with a high on-off ratio (?300) and long retention (?9000 seconds). The fabricated devices show stable, low voltage and high switching speed operation. Furthermore, in this work, we demonstrate the synaptic behaviour of the LFO thin film memory devices, as it exhibits analogue memory characteristics, potentiation and depression. Further, the LFO thin films were irradiated to 180 MeV Ar+6 ion for different fluence and analysed the effect of radiation. The increment in reset voltage was observed as we increased the fluence of Arions while the devices were able to maintain the RRAM characteristics. These studies show, that the BTO, STO and LFO-based memory devices have the potential to be used as memory devices.
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    Role of Multiqubit Entanglement and Correlations in Quantum Information Processing
    (Indian Institute of Technology Jodhpur, 2022-01) Kumar, Atul
    The inception of Einstein-Podolsky-Rosen (EPR) paradox ensured quantum correlations to take a center stage in the investigations of foundations of quantum theory. The creative discussions in this direction led to the advent of quantum information and computation (QIC)- a computing paradigm based on the fundamental aspects of quantum mechanics. Clearly, the last three decades have been instrumental in establishing quantum correlations as fundamental ingredients to achieve potential applications which are otherwise not possible using classical resources. Nonlocal correlations exhibited by entangled systems have been utilized for several efficient and optimal applications in quantum information and computation. In fact, discorda measure of quantumness in an underlying state- captures nonlocal correlations even in a separable state. Therefore, classification and quantification of nonlocal correlations in quantum systems not only support the description of foundations of quantum information but also help to identify new and efficient resources. With the increase in number of qubits, description of entanglement and nonlocality, becomes much more difficult even in pure states. For example, the nonlocal properties of two qubit pure states are well established in terms of violation of the Bell inequality but the description of nonlocality for three qubit pure states still requires a better physical interpretation using Bell-type inequalities. Although the Mermin inequality captures nonlocal correlations in a set of three qubit pure entangled states, it fails to distinguish between bipartite and genuine tripartite correlations. Further, the three-qubit Mermin inequality also fails to identify nonlocal correlations in a set of partially entangled three qubit pure states. The Svetlichny inequality, however, confirms the presence of genuine three qubit nonlocal correlations by effectively distinguishing between bipartite and tripartite nonlocality, but fails to characterize nonlocal correlations in a large set of three qubit entangled pure states for a given range of the state parameter. As one further increases number of qubits to the system, the complexity also increases with an increase in number of different entangled classes. The analysis of entanglement and nonlocality becomes much more involved considering real conditions and mechanisms to protect nonlocal correlations for obtaining better efficiencies of entangled resources. Surprisingly, for three-qubit or multiqubit systems, no generic inequality is found to identify nonlocal correlations in all entangled states. Moreover, one can also find two qubit mixed states which may be entangled but would still not violate the Bell inequality. It is probably the characteristic trait of theory complexity that makes the discussion much more challenging and interesting. The measures of nonlocality do not agree with the measures of entanglement and if we consider the presence of noise then the situation becomes even more intricate. The role of correlations in quantum information and communication is, therefore, far from well established. A generic approach to classify nonlocal correlations in multiqubit systems would further ascertain the usefulness of such systems for quantum communication and information processing and would certainly lead us to have a better insight into the subtle nature of quantum correlations. The Thesis is an attempt towards establishing a general description of nonlocal correlations in bipartite and multiqubit pure and mixed states. A simple description that can be obtained analytically or numerically to distinguish the quantum and classical boundary would definitely be of great value. For this, we propose a new measure of nonlocality based on many-body statistical mechanics to map out the behavior of nonlocal correlations in entangled resources. We systematically establish analytical relations between the optimal expectation values of the proposed operators, degree of entanglement, noise and state parameters for bipartite and multiqubit systems considering the inevitable presence of noise. We further extend our analysis to protect and study robustness of nonlocal correlations in presence of noise. Our results show that the proposed and modified operators successfully identify nonlocal correlations in multiqubit pure states. In fact, our study further demonstrates the presence of nonlocality in mixed and separable states where even the Bell or Bell-type inequalities fail to capture nonlocal correlations. The results successfully address issues of bipartite vs tripartite vs multiqubit nonlocality and further identify all pure multiqubit entangled states for the complete range of state parameters. The discussion is extended to quantify nonlocality in different classes of four and five qubit entangled pure states. Furthermore, the analytical results obtained in this Thesis are in complete agreement with numerical results. Based on our studies for bipartite and multiqubit systems, we readdress the of partially entangled multiqubit states for quantum information and computation. For this, we revisit the question of analyzing efficiencies of four different sets of partially entangled states in three qubit classes under real conditions. In the presence of noise, we show that maximum entanglement and nonlocality in the input state do not always guarantee maximum efficiency in a protocol. For example, our analysis suggests that efficiencies of a set of partially entangled states are much more robust to noise than those of maximally entangled states in Greenberger–Horne–Zeilinger (GHZ) class of states. For a set of partially entangled states in presence of noise and weak measurements, efficiencies of communication protocols achieve the optimal value independent of the state and decoherence parameters. We further generalize our study to address efficiencies of (N + 2)-qubit partially entangled states for the presence of N controllers in a noisy environment from the perspective of controllers’ authority and average fidelity. These values are obtained by designing a generalized circuit using single and two-qubit gates and studying different cases of two sets of partially entangled multiqubit states. Our analysis identifies a set of partially entangled states for which the average fidelity is independent of the state parameter and measurements performed by (N − 1) controllers thereby facilitating the experimental set-ups to worry about a smaller number of parameters in the protocol when dealing with a multiqubit network. Interestingly, even in the presence of noise and weak measurement operations, we find the efficiency of a set of (N +2)-qubit partially entangled states to be independent of the measurements performed by (N−1) controllers. The efficiencies of these states are consistent with the analysis of nonlocal correlations using our modified operators and quantum discord.
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    Colloidal Quantum Dots Nanocomposites Based Resistive Switching for Low-Power Resistive Random Access Memory
    (Indian Institute of Technology Jodhpur, 2022-12) Sahu, Satyajit
    Memory is one of the most essential parts in human body or machine. Conventional memory technologies such as HDD, USB Flash drive, SSD etc. which are being used as the data storage devices over past few decades, are failed to store the huge amount of data generated by explosion of digital information and internet of things (IoT). The silicon-based technologies are facing several theoretical and practical limitations upon downscaling. Also, the Von Neumann architecture used in the current computers, has separate processing unit and storage unit. As the processing unit and storage units are separated and connected by buses, the data transfer speed is limited and this architecture consumes lot of power. Therefore, it is essential to design universal memory with high density data storage, fast operation speed, capacity of in memory computing and low power consumption. Emerging memory technologies such as phase change memory (PCM), ferroelectric random-access memory (FERAM), magnetic random access memory (MRAM) and resistive random access memory (RRAM) have drawn much attention to be used as universal memory. RRAM is one of the most promising for universal memory candidates owing to its simple architecture, high stacking density, fast operation speed, capability of in memory computing, long retention time, high endurance cycles and low operational power. The working principle of RRAM is based on the change in the resistance of the device modulated by electrical stimulation. High resistance state is the off state which can be considered as bit 0 and low resistance state is the on state which can be considered as bit 1 in RRAM. Depending on the number of different resistance state, multibit can be stored in RRAM. Semiconducting quantum dots (QDs) embedded in polymer matrix or sandwiched between thin oxide layers can be used as an active material for high performance RRAM device. QDs having the particle size in the range between 2 to 10 nm show quantum confinement effect. Various surface trap states are present in the QDs. These surface trap states can be modified by encapsulating the surface with different ligands. In the composite of QDs with polymers, QDs act as charge trapping centers. Colloidal CdSe QD by the hot injection method was synthesized and these QDs were blended with poly(4-vinylpyridine) (PVP) polymer to prepare the active layer of a RRAM device. For device fabrication, the CdSe QDs-PVP nanocomposite was spin coated on an ITO substrate and finally Al top electrode was deposited using a thermal evaporation unit. The Al/CdSe QDs-PVP/ITO device exhibited excellent bipolar resistive switching (RS) behavior with maximum on-off ratio (ION/IOFF) of 105, long retention time (> 3700 s), high endurance. The SET and RESET voltage of this device was +1.6 V and -1.7 V respectively. Another device using CdSe QDs-PVP nanocomposites as an active material with slightly different ratio from previous one was fabricated with Al as both top and bottom electrodes. This Al/CdSe QDs-PVP/Al device also showed excellent resistive switching with less SET and RESET voltage as compared to previous one. The SET and RESET voltages of Al/CdSe QDs-PVP/Al device were +0.6 V and -0.5 V respectively. The ultimate power consumption of this device is 4.16 ?W in the on state and 80 pW in the off state, which are sufficiently low to be considered as a low power memory device. Also, the Al/CdSe QDs-PVP/Al device has data retention time larger than 35,000 s which is much better than previous Al/CdSe QDs-PVP/ITO device. The resistive switching in CdSe QDs-PVP nanocomposites-based device is ascribed to charge trapping and detrapping in QDs while the polymers act as charge blocking layer. Though CdSe QDs based RRAM shows excellent resistive switching behavior with low power consumption, CdSe is toxic and found to be human carcinogens. Therefore, in search of less toxic and non-carcinogens materials, we have synthesized colloidal Molybdenum disulfide (MoS2) QDs. The MoS2 QDs were blended with PVP and used as active material in Al/MoS2 QDs-PVP/ITO device. The Al/MoS2 QDs-PVP/ITO device also exhibited excellent RS with high value of ION/IOFF (~ 105), long retention time (> 25,000 s), high endurance over 250 cycles and very fast response time (~ 28 ns). The operating voltage of the device was less than states. In fact, our study further demonstrates the presence of nonlocality in mixed and separable states where even the Bell or Bell-type inequalities fail to capture nonlocal correlations. The results successfully address issues of bipartite vs tripartite vs multiqubit nonlocality and further identify all pure multiqubit entangled states for the complete range of state parameters. The discussion is extended to quantify nonlocality in different classes of four and five qubit entangled pure states. Furthermore, the analytical results obtained in this Thesis are in complete agreement with numerical results. Based on our studies for bipartite and multiqubit systems, we readdress the usefulness of partially entangled multiqubit states for quantum information and computation. For this, we revisit the question of analyzing efficiencies of four different sets of partially entangled states in three qubit classes under real conditions. In the presence of noise, we show that maximum entanglement and nonlocality in the input state do not always guarantee maximum efficiency in a protocol. For example, our analysis suggests that efficiencies of a set of partially entangled states are much more robust to noise than those of maximally entangled states in Greenberger–Horne–Zeilinger (GHZ) class of states. For a set of partially entangled states in presence of noise and weak measurements, efficiencies of communication protocols achieve the optimal value independent of the state and decoherence parameters. We further generalize our study to address efficiencies of (N + 2)-qubit partially entangled states for the presence of N controllers in a noisy environment from the perspective of controllers’ authority and average fidelity. These values are obtained by designing a generalized circuit using single and two-qubit gates and studying different cases of two sets of partially entangled multiqubit states. Our analysis identifies a set of partially entangled states for which the average fidelity is independent of the state parameter and measurements performed by (N − 1) controllers thereby facilitating the experimental set-ups to worry about a smaller number of parameters in the protocol when dealing with a multiqubit network. Interestingly, even in the presence of noise and weak measurement operations, we find the efficiency of a set of (N +2)-qubit partially entangled states to be independent of the measurements performed by (N−1) controllers. The efficiencies of these states are consistent with the analysis of nonlocal correlations using our modified operators and quantum discord.states. In fact, our study further demonstrates the presence of nonlocality in mixed and separable states where even the Bell or Bell-type inequalities fail to capture nonlocal correlations. The results successfully address issues of bipartite vs tripartite vs multiqubit nonlocality and further identify all pure multiqubit entangled states for the complete range of state parameters. The discussion is extended to quantify nonlocality in different classes of four and five qubit entangled pure states. Furthermore, the analytical results obtained in this Thesis are in complete agreement with numerical results. Based on our studies for bipartite and multiqubit systems, we readdress the usefulness of partially entangled multiqubit states for quantum information and computation. For this, we revisit the question of analyzing efficiencies of four different sets of partially entangled states in three qubit classes under real conditions. In the presence of noise, we show that maximum entanglement and nonlocality in the input state do not always guarantee maximum efficiency in a protocol. For example, our analysis suggests that efficiencies of a set of partially entangled states are much more robust to noise than those of maximally entangled states in Greenberger–Horne–Zeilinger (GHZ) class of states. For a set of partially entangled states in presence of noise and weak measurements, efficiencies of communication protocols achieve the optimal value independent of the state and decoherence parameters. We further generalize our study to address efficiencies of (N + 2)-qubit partially entangled states for the presence of N controllers in a noisy environment from the perspective of controllers’ authority and average fidelity. These values are obtained by designing a generalized circuit using single and two-qubit gates and studying different cases of two sets of partially entangled multiqubit states. Our analysis identifies a set of partially entangled states for which the average fidelity is independent of the state parameter and measurements performed by (N − 1) controllers thereby facilitating the experimental set-ups to worry about a smaller number of parameters in the protocol when dealing with a multiqubit network. Interestingly, even in the presence of noise and weak measurement operations, we find the efficiency of a set of (N +2)-qubit partially entangled states to be independent of the measurements performed by (N−1) controllers. The efficiencies of these states are consistent with the analysis of nonlocal correlations using our modified operators and quantum discord.states. In fact, our study further demonstrates the presence of nonlocality in mixed and separable states where even the Bell or Bell-type inequalities fail to capture nonlocal correlations. The results successfully address issues of bipartite vs tripartite vs multiqubit nonlocality and further identify all pure multiqubit entangled states for the complete range of state parameters. The discussion is extended to quantify nonlocality in different classes of four and five qubit entangled pure states. Furthermore, the analytical results obtained in this Thesis are in complete agreement with numerical results. Based on our studies for bipartite and multiqubit systems, we readdress the usefulness of partially entangled multiqubit states for quantum information and computation. For this, we revisit the question of analyzing efficiencies of four different sets of partially entangled states in three qubit classes under real conditions. In the presence of noise, we show that maximum entanglement and nonlocality in the input state do not always guarantee maximum efficiency in a protocol. For example, our analysis suggests that efficiencies of a set of partially entangled states are much more robust to noise than those of maximally entangled states in Greenberger–Horne–Zeilinger (GHZ) class of states. For a set of partially entangled states in presence of noise and weak measurements, efficiencies of communication protocols achieve the optimal value independent of the state and decoherence parameters. We further generalize our study to address efficiencies of (N + 2)-qubit partially entangled states for the presence of N controllers in a noisy environment from the perspective of controllers’ authority and average fidelity. These values are obtained by designing a generalized circuit using single and two-qubit gates and studying different cases of two sets of partially entangled multiqubit states. Our analysis identifies a set of partially entangled states for which the average fidelity is independent of the state parameter and measurements performed by (N − 1) controllers thereby facilitating the experimental set-ups to worry about a smaller number of parameters in the protocol when dealing with a multiqubit network. Interestingly, even in the presence of noise and weak measurement operations, we find the efficiency of a set of (N +2)-qubit partially entangled states to be independent of the measurements performed by (N−1) controllers. The efficiencies of these states are consistent with the analysis of nonlocal correlations using our modified operators and quantum discord.states. In fact, our study further demonstrates the presence of nonlocality in mixed and separable states where even the Bell or Bell-type inequalities fail to capture nonlocal correlations. The results successfully address issues of bipartite vs tripartite vs multiqubit nonlocality and further identify all pure multiqubit entangled states for the complete range of state parameters. The discussion is extended to quantify nonlocality in different classes of four and five qubit entangled pure states. Furthermore, the analytical results obtained in this Thesis are in complete agreement with numerical results. Based on our studies for bipartite and multiqubit systems, we readdress the usefulness of partially entangled multiqubit states for quantum information and computation. For this, we revisit the question of analyzing efficiencies of four different sets of partially entangled states in three qubit classes under real conditions. In the presence of noise, we show that maximum entanglement and nonlocality in the input state do not always guarantee maximum efficiency in a protocol. For example, our analysis suggests that efficiencies of a set of partially entangled states are much more robust to noise than those of maximally entangled states in Greenberger–Horne–Zeilinger (GHZ) class of states. For a set of partially entangled states in presence of noise and weak measurements, efficiencies of communication protocols achieve the optimal value independent of the state and decoherence parameters. We further generalize our study to address efficiencies of (N + 2)-qubit partially entangled states for the presence of N controllers in a noisy environment from the perspective of controllers’ authority and average fidelity. These values are obtained by designing a generalized circuit using single and two-qubit gates and studying different cases of two sets of partially entangled multiqubit states. Our analysis identifies a set of partially entangled states for which the average fidelity is independent of the state parameter and measurements performed by (N − 1) controllers thereby facilitating the experimental set-ups to worry about a smaller number of parameters in the protocol when dealing with a multiqubit network. Interestingly, even in the presence of noise and weak measurement operations, we find the efficiency of a set of (N +2)-qubit partially entangled states to be independent of the measurements performed by (N−1) controllers. The efficiencies of these states are consistent with the analysis of nonlocal correlations using our modified operators and quantum discord.states. In fact, our study further demonstrates the presence of nonlocality in mixed and separable states where even the Bell or Bell-type inequalities fail to capture nonlocal correlations. The results successfully address issues of bipartite vs tripartite vs multiqubit nonlocality and further identify all pure multiqubit entangled states for the complete range of state parameters. The discussion is extended to quantify nonlocality in different classes of four and five qubit entangled pure states. Furthermore, the analytical results obtained in this Thesis are in complete agreement with numerical results. Based on our studies for bipartite and multiqubit systems, we readdress the usefulness of partially entangled multiqubit states for quantum information and computation. For this, we revisit the question of analyzing efficiencies of four different sets of partially entangled states in three qubit classes under real conditions. In the presence of noise, we show that maximum entanglement and nonlocality in the input state do not always guarantee maximum efficiency in a protocol. For example, our analysis suggests that efficiencies of a set of partially entangled states are much more robust to noise than those of maximally entangled states in Greenberger–Horne–Zeilinger (GHZ) class of states. For a set of partially entangled states in presence of noise and weak measurements, efficiencies of communication protocols achieve the optimal value independent of the state and decoherence parameters. We further generalize our study to address efficiencies of (N + 2)-qubit partially entangled states for the presence of N controllers in a noisy environment from the perspective of controllers’ authority and average fidelity. These values are obtained by designing a generalized circuit using single and two-qubit gates and studying different cases of two sets of partially entangled multiqubit states. Our analysis identifies a set of partially entangled states for which the average fidelity is independent of the state parameter and measurements performed by (N − 1) controllers thereby facilitating the experimental set-ups to worry about a smaller number of parameters in the protocol when dealing with a multiqubit network. Interestingly, even in the presence of noise and weak measurement operations, we find the efficiency of a set of (N +2)-qubit partially entangled states to be independent of the measurements performed by (N−1) controllers. The efficiencies of these states are consistent with the analysis of nonlocal correlations using our modified operators and quantum discord ±1.5 V. Furthermore, this MoS2 QDs-PVP based device shows stable resistive switching when heated even at 130°C. The excellent temperature stability of the fabricated MoS2 QDs-PVP RRAM device reveals that it can be effectively used in extremely hot weather conditions without degradation. These studies reveal that CdSe and MoS2 QDs embedded in PVP matrix can have great potential to be used as active materials for stable, high performance and low power RRAM dev
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    High Power Optical Pulses through Linear, Nonlinear, and Time-Varying Media and their Applications
    (Indian Institute of Technology Jodhpur, 2023-04) Ghosh, Somnath
    Optical pulses are electromagnetic waves that exist for a particular duration of time. Such short-lived light pulses are generated from lasers and are very useful for data transmission, imaging, medical surgeries, various time-resolved measurements, optical signal processing, and many more. However, the transmission of such optical pulses through the state-of-the-art photonic devices eventually encounters certain challenges due to the unavoidable light-matter interaction processes that, in a large amount, controls the targeted outcome. Essentially, shorter optical pulses, with duration ranging from a few picoseconds to several hundreds of femtoseconds, severely suffer higher order dispersive and nonlinear effects. However, a judicious management of such linear and nonlinear processes may result in certain exclusive pulse dynamics. This thesis entirely focuses on the investigation of such exclusive and robust characteristics of ultrashort optical pulses during their propagation through specially designed photonic structures exhibiting linear dispersive, nonlinear, and time-varying optical effects for specialty applications. Two device platforms, that have immense potential to change the course of scientific and technological flow, have been chosen to study the ultrashort pulse dynamics. First, optical fibers have been chosen as the waveguide structure supporting confinement of light through spatially varying refractive index profile, and then a linear dispersive bulk medium with a temporally varying refractive index profile. The specific purpose of high power short pulse delivery demands robust pulse characteristics to withstand higher order dispersive and nonlinear effects. Further investigations in this direction has demonstrated Solitons and Similaritons (widely known as Parabolic pulses) to be such special type of pulses which are robust against any detrimental optical effect once formed. Formation of these pulses requires pulse reshaping techniques that can be efficiently realized in optical fibers owing to their design-flexible structural and physical properties to guide and manipulate light. Especially, the photonic bandgap fibers (PBF) where the special arrangement of high and low index material in the cladding surrounding the low index core provides ample possibilities of fiber parameter customization necessary for pulse reshaping. Based on such PBF geometry, a group of all-solid specialty optical fibers, have been presented, to accomplish reshaping of high power ultrashort pulses through longitudinal fiber tapering into either similaritons or solitons such that they can propagate over long distances without any temporal as well as spectral distortions. Firstly, an approach based on input pulse customization technique has been implemented to realize a stable self-similar delivery of parabolic pulses through a designed longitudinally tapered fiber with standard Bragg fiber crosssection in the near-infrared wavelength range. Formation of parabolic pulses from a backgroundguided combined input pulse, and its stable propagation with self-similar evolution through the tapered fiber has been presented over kilometer long distances providing a comparatively better outcome. Further, to achieve stable delivery of self-similar parabolic pulses in mid-infrared, a novel fiber customization approach exhibiting a rapidly varying longitudinal dispersion profile with near-zero average normal dispersion has been adapted to design and optimize the specialty fiber. A detailed study on the roles of higher order dispersion and nonlinear effects in such dispersion oscillating fiber has been presented, along with the proposal of a two-fold fiber engineering scheme to eliminate such higher order detrimental effects. Furthermore, based on the fundamental light guiding principle of PBFs, a multicore specialty bandgap fiber supporting an ultra-wide low-loss fiber bandwidth owing to the concentrically arranged effectively formed cores have been proposed to deliver stable femtosecond solitons and/or similaritons over kilometer long distances, eliminating the challenge of bandwidth limitation in fibers. Finally, to meet the requirement of robust transport of high power short optical pulses, a very special type of multilayered fiber, known as topological fiber, has been demonstrated where light guidance occurs at the interface of two topologically distinct periodic structures. Such guided interface states of light are inextricably tied to the topology of the entire system through an invariant quantity which inherently provides the immunity to backreflections, defects or dislocations. A detailed pulse propagation study through such topological interface states has also been presented which is envisaged to pave the way towards futuristic fiber optic technology. On the other hand, the behavior of ultrashort optical pulses in a time-dynamic medium has been investigated which has tremendous potential towards new generation all-optical integrated photonic devices. Light dynamics in such a linear dispersive medium with refractive index as a function of time has led to certain exquisite optical phenomena such as asymmetric pulse transmission and wavelength conversion. The effect of presence of deliberate gain and loss in the medium has been analyzed thoroughly. Furthermore, the dispersive nature of the medium has been investigated separately to study its effect on the asymmetric propagation of pulses. Moreover, the shifting of pulse central wavelength with respect to the input in such a linear time-dynamic medium has been found to assent the phenomenon of spectral nonreciprocity, which was primarily observed in presence of nonlinearity or magnetic effects in cavities or waveguides. Finally, a nonreciprocal behavior of optical pulses through such linear time-varying medium has been demonstrated with appropriate theoretical explanation, which will surely open up a new avenue for next-generation integrated photonic devices.
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    Dynamical Heterogeneity of Interface Water upon Membrane Phase Transitions
    (Indian Institute of Technology Jodhpur, 2023-01) Debnath, Ananya
    Lipid bilayers are essential components of cell membranes because they serve as semi-permeable barriers between the extracellular and intracellular environments. Fluid (Lα ), ripple (Pβ ), and gel (Lβ ) are the three primary phases of lipid membranes. The functionality of the cell membrane is active at its fluid phase and at a full hydration level. A co-existence in the gel and the fluid phases in membranes results in the creation of grain boundary defects and helps in a drug release. Water molecules near membranes regulate various properties of the cell such as transport, raft formation, molecular recognition, signal transduction and so on. Such water have different characteristics than bulk water (BW). Thus understanding the role of water on the membrane phase transitions is crucial to control the function of membrane under physiological and low temperature conditions. Although water dynamics and thermodynamics around membranes have been found to be correlated with the phase transition, the underlying mechanism of the correlation is not explored and not characterized. The current thesis provides evidences of emergence of dynamical heterogeneity in interface water (IW) near membranes at three phases using all-atom molecular dynamics simulations. The correlation between the structure and dynamics of the IW and membranes are quantified across fluid to ripple to gel phase transitions. To understand whether the regional coupling of lipid and water dynamics is significant enough to capture any perturbation in fluid membrane, we identify IW near a fluid membrane composed of 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC) lipids. IW residing within a distance of ±0.35 nm of the locations of the most probable density of CO/PO/Glyc. heads of DMPC molecules are referred to as IW-COd/POd/Glycd . All IW molecules manifest signatures of dynamical heterogeneity at room temperature due to regional confinement and exhibit multiple structural relaxation time-scales. Both fast and slow relaxation time scales of the IWd are correlated to the respective time scales of the closest lipid moieties. These analyses imply that the spatially resolved interface water dynamics can act as a sensitive reflector of regional membrane dynamics occurring at sub ps to hundreds of ps time scales and thus will be able to capture any alterations in membrane structure and function in future. Since membranes are active at a fully hydrated state and the cells die upon dehydration, understanding biological cell membranes under anhydrous conditions is of tremendous importance. We find that the bilayer undergoes from a disordered state to a ordered state upon dehydration with a drastic slow-down in the relaxation times of the IW originated from dynamical heterogeneity. The diffusion constants and the structural relaxation times of the IW obey the Stokes-Einstein (SE) relation for the bilayer fluid phase which changes to a fractional SE-like relation at the onset of bilayer ordering. Thus, our analysis provides the mechanistic insights of dehydration induced bilayer ordering. To understand the structural changes of the IW due to bilayer phase transitions, we perform a ∼ 11.55μs long all-atom molecular dynamics simulation at the gel, ripple and the fluid phases of the bilayers. The first and second peak heights of the radial distribution functions (RDF) of the BW increase monotonically with a decrease in temperature, signifying the presence of enhanced tetrahedrality at the lowest temperature which is below the homogeneous ice nucleation temperature accessing the ”no man’s land”. Similar behaviour is observed for the IW near fluid and gel phases but not for the ripple phase, probably due to the curvature induced in the ripple phase. Changes in locations of the first and the second hydration shells show two crossovers near fluid to ripple and ripple to gel phase transitions. The angular distribution functions of the IW near the fluid bilayers exhibit peaks corresponding to a distorted tetrahedral arrangement similar to the high-density liquid (HDL) phase due to the presence of interstitials. This changes to tetrahedral arrangement for the IW near the gel bilayer, indicating the presence of low-density liquid (LDL) like phases. As temperature reduces, membrane phase transitions are associated with a drastic slow down in structural relaxation times of the interface water (IW) and the lipids originated from dynamical heterogeneity. Diffusion constants of the IW undergo dynamic crossovers at both fluid-to-ripple-to-gel phase transitions with the highest activation energy near the gel phase leading to a stronger correlation of the IW dynamics with the gel membrane due to larger number of hydrogen bonds. Similar to the BW, Stoke Einstein (SE) relations are conserved for the IW near all three phases of membranes for the time scales derived from the diffusion exponents and the non-Gaussian parameters, indicating that these time scales are coupled with the diffusion even at lower temperatures. However, the SE relationship breaks for the time scales calculated from the self intermediate scattering functions. The behavioural differences in these different time scales upon supercooling are found to be universal irrespective of the nature of the water and other glass forming liquids. The spatial correlation length scale of the heterogeneous local dynamics of the IW are captured from the data collapse of block size dependent Binder cumulant which is a scaling function of only the underlying correlation length. The dynamical length of the IW is found to have inverse power law dependence on temperature for the fluid phase. The dependence becomes very weak for the gel phase unlike glass forming liquids. Interestingly, the dynamical length scale of the IW near the ripple phase is temperature independent and thus, can capture to the domain size of the ripple signifying a possibility of probing the heterogeneity length scale of a bio-membrane from its curvature induced domain size. The length scale is monotonically dependent on the first peak of the radial distribution function of the IW near all phases this suggests that the heterogeneity length scale is structure dominated. Our analyses, for the first time, estimate the coupling between the spatio-temporal scales of the IW and membranes across phase transitions. The structural relaxations of the IW follow an activated dynamical scaling with the heterogeneity length scale only for the gel phase which is similar to that predicted from the random first order transition theory. However, the drastic growths in the heterogeneity length scale across phase transitions are not accompanied by similar growth in the heterogeneity time scales. This is because, the growing structural relaxation time scales of the IW are dominated by the supercooling whereas the growing length scales are dictated by the membrane phase transitions. In summary, the thesis sheds light on how the structure and dynamics of lipids and IW are correlated across a wide range of temperature and hydration numbers relevant for physiological and extreme conditions. Our findings suggest that hydration water dynamics can sensitively reflect localized membrane movements and thus can be an alternate tool to probe any perturbations in membranes. These can help to understand drug delivery mechanisms and mimic cryo preservation procedures for use in biomedical applications in the future.