Theses

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Advanced Functional Nanomaterials for Energy and Environmental Applications.
(Indian Institute of Technology Jodhpur, 2021-02) Sharma, Rakesh Kumar
Innovative research ideas in the field of science and technology have the ability to garner solutions to current world problems – harnessing and storing clean and sustainable sources of energy without leaving any carbon foot print, other global problems such as reducing environmental pollution – clean water and air. For example, semiconductor catalysts have the potential to utilize solar energy to address the aforementioned issues when incorporated in devices. However, these semiconductor materials need to be tuned and engineered to suitable requirement to give optimum performance. In this study, we have reported various functional materials in the nano regime, synthesized using facile and replicable processes. These nanomaterials are further employed to explore possible applications.Titanium dioxide is a cost-effective, environmentally benign and abundant material having a wide bandgap of 3.14 eV. This material is designed to a spherically structured morphology comprising of smaller TiO2 nanoparticles with the bandgap reduced to 2.4 eV. This result was afforded by a two-step sol-gel and hydrothermal approach. The resulting nanomaterial was implemented for photocatalytic degradation of five different industrial dyes. Major findings related to dye degradation, including comparison at different pH medium and repeatability of the catalyst are outlined as a part of the thesis.Additionally, stable and effective nanomaterials HfO2 were devised for catalytic soot oxidation whereby soot from diesel and industrial engines can be oxidized before releasing into the atmosphere. Two chapters in the thesis explored HfO2 hydrogenated at different time intervals and Ni and Co incorporated clay as sustainable catalysts for oxidation of soot. The synthesized catalysts were able to lower the light-off temperature of the catalyst, Tm. The chapters discuss the mechanism of soot oxidation and the role of oxygen vacant sites for the effective working of the catalysts.Additionally, nitrogen-doped carbon material for multiple applications are further explored. Two types of nitrogen-doped carbons - hollow and solid are synthesized via a modified Stöber’s process. The developed carbon materials are utilized as electrode materials in DSSC device as photoanode and counter electrode and also a potential material for CO2 capture. Additionally, the materials were tested for possible electrode material in supercapacitor application.Another material which with interesting prospect in the optoelectronic industry is the all-inorganic perovskite CsPbX3 nanocrystals. A study is carried out based on these special perovskites involving the preparation and investigation for other significant physiochemical properties. These reportedly unstable luminescent nanocrystals are stabilized using a protecting encapsulation of metal oxides of Ti, Mo, Ta and Sn. Furthermore, composites of these halide perovskites with monolayer graphitic carbon nitride nanosheets were synthesized for photoelectrochemical application.
Analysing Multiqubit Entanglement, Nonlocality and Quantum Information Processing Protocols
(Indian Institute of Technology Jodhpur, 2018-10) Kumar, Atul
Quantum entanglement and nonlocal correlations are essential feature of quantum information and computation with no classical analogues. Apart from being central to the fundamentals of quantum mechanics and quantum information, entanglement is also used as an efficient resource for quantum information processing protocols such as dense coding, teleportation, secret sharing, entanglement swapping, and cryptography. The use of entangled resources to achieve efficient and optimal success in quantum information, in comparison to classical resources, is based on nonlocal correlations existing between the particles. The existence of such long-range correlations in quantum systems thus distinguishes the quantum world from its classical counterpart. Although entanglement and nonlocality are well studied in pure two-qubit systems in terms of entanglement of formation (or some physically equivalent quantity) and Bell Inequality, the description and characterization of multiqubit entanglement and nonlocality is much more complex. In fact the entanglement properties of bipartite mixed entangled states itself require a much better physical interpretation. What makes the problem extremely challenging is probably the characteristic trait of complexity. For example, the Bell-type inequalities for three-qubit pure entangled systems itself either fail to distinguish between bipartite and tripartite inequality or fail to identify the presence of nonlocal correlations in a large set of states. The intricacy of the problem increases further considering the real conditions, i.e., by considering interaction between the principal system and environment, leading to decoherence, which adversely impacts the efficiency of quantum systems; in general. Initially, the description of quantum correlations was mainly associated with entanglement and nonlocality- separable states were thought to be classical systems not useful for quantum information and computation. This perception has been questioned recently with the identification of few separable systems exhibiting quantum correlations and showing potential to be used as resources for quantum information processing. Quantum discord, for example, is a measure of genuine nonlocal correlations and captures the nonlocality in entangled as well as separable bipartite systems. Although quantum discord describes all types of nonlocal correlations in the system, it is difficult to obtain analytical expressions to evaluate discord due to the optimization procedure involved. A simple description that can be obtained analytically to distinguish the quantum and classical boundary would therefore be of great value. The Thesis readdresses the question of analysing the entanglement and nonlocality in bipartite and multiqubit entangled systems under real scenarios. For this, we establish analytical relations between nonlocality, state parameters, noise parameters and entanglement measures of several entangled classes in two, three and four-qubit systems under real noisy conditions. We further extend our analysis to study the applications of weak measurement and its reversal operations on the nature of correlations existing between the qubits in noisy environment. Interestingly, we find that more nonlocal correlations in the initially prepared state not always guarantee higher efficiency in quantum communication protocols. The analytical results obtained in the Thesis are in complete agreement with the numerical optimization. Moreover, we also propose a class of two-qubit mixed states which is demonstrated to be much more efficient in quantum information processing, than several other two-qubit pure and mixed states. We further emphasize on the usefulness of mixed entangled resources for quantum information and computation in terms of fully entangled fraction, nonlinear entanglement witness and Horodecki’s measure. In multiqubit systems, we consider to characterize nonlocal properties of three- and four-qubit Greenberger-Horne-Zeilinger states, three-qubit Slice states, three-qubitW andWn-type states under real conditions. We believe that our results will be of significant importance as all the multiqubit states considered for analysing entanglement and nonlocal correlations are experimentally viable. In addition, we also study the usefulness of quantum correlations in an arbitrary two-qubit state in a biased scenario, i.e., a situation where Alice and Bob perform measurements on their respective qubits with a certain bias. Our results show that quantum theory offers advantages over classical theory for the whole range of biasing parameters. The analysis is further extended using fine-grained uncertainty relations to distinguish between classical and quantum correlations. For a generic description to characterize nonlocal correlations between qubits, we propose to use statistical correlation coefficients and modify the two-qubit Bell-CHSH and the three-qubit Svetlichny inequality to analyse nonlocality in two and three-qubit entangled systems, respectively. For two-qubit systems, we demonstrate a necessary and sufficient condition for the violation of modified inequality. Further, we describe a simple way to evaluate geometric discord in terms of correlation coefficients and establish a relation between geometric discord and modified Bell-CHSH inequality to understand and interpret nonlocality in terms of correlation coefficients. For three qubit pure Greenberger-Horne-Zeilinger states, unlike the original inequality which fails to detect nonlocality in a large set of states, our modified inequality identifies the presence of nonlocal correlations in all the Greenberger-Horne-Zeilinger states. In addition, we also study the properties of a special class of non-maximally entangled four-qubit W-type states. Our results show that the class of states are highly useful in quantum information and computation. We generalize our analysis for deterministic transfer of information using N-qubit W-type states as resources. The importance of the proposed class, however, is limited by the realization of experimental set-ups to perform and distinguish multiqubit joint measurements. We, therefore, propose another efficient protocol to use non-maximally entangled W-type states for sharing an optimal bipartite entanglement. Interestingly, our analysis also suggests that four-qubit W-type states can be preferred as resources in comparison to three-qubit W-type states for certain ranges of state parameters. For practical implementation, we further propose a method to experimentally prepare W-type states using standard single and two-qubit measurements.
Analysis and Design of Wideband Fractal Antennas for Portable UWB Applications
(Indian Institute of Technology Jodhpur, 2015-04) Yadav, Sandeep ; Mohan, Akhilesh
The increase in demand for frequency bands to facilitate voice, data and video services have created the spectrum scarcity and forces the regulatory authorities to allow the unlicensed use of the spectrum. In 2002, FCC regularized the uses of 3.1-10.6 GHz spectrum with indoor and outdoor power spectral level mask. Nowadays, wireless communication systems require compact as well as wideband antennas. The compactness in design will assist in the integration of the proposed structures with portable systems. Design of a wideband antenna is very challenging as compared to narrow band antennas. The application of fractal geometry in antenna design resolve the above mentioned problems. The goal of the thesis is to analysis and design of wideband fractal antennas for portable UWB applications. The use of fractals in antenna design improves several characteristics. The miniaturization and wideband characteristics are obtained due to fractals properties like self-similarity and space-filling, respectively. Furthermore, antennas achieve wideband phenomena due to multiple resonances offered by the fractals. In the UWB antenna design, different fractal geometries such as Minkowski like, Minkowski, Sierpinski and Koch are used. Fractal application helps to achieve the desired miniaturization, wide impedance bandwidth and stable radiation pattern. With the application of different fractals, different antennas are proposed for concepts or techniques such as wideband with band-notch characteristics, reconfigurable band notch characteristics, reconfigurable narrowband characteristics, MIMO techniques and WBAN. The performance and characteristics of these antennas in frequency domain as well as in time domain are investigated to understand their behavior. It is demonstrated that the introduction of fractals at the edges of monopoles or at the ground plane improves the impedance bandwidth of an antenna. To the best knowledge of our, application of fractal UWB antenna either to provide reconfigurability in design or for WBAN is not provided previously. All the presented antenna structures are fabricated on different substrates (FR4 and Duroid) for different dielectric constants as well as thicknesses. It is demonstrated numerically and experimentally that the proposed antenna structures are suitable candidates for UWB applications.
Analysis of Lattice Boltzmann Method for Turbulent Flow Simulation on Multi-core GPU Architecture
(Indian Institute of Technology Jodhpur, 2021-09) Ravindra, Brahmajosyula; Prakash, Akshay
The present thesis explores the applicability of the lattice Boltzmann Method (LBM) to validate the turbulent flow simulation in the various complex flow domains. LBM in recent years has emerged as an alternative Computational Fluid Dynamics (CFD) approach other than traditional Navier-Stokes (NS) solvers. The method is based on the discrete numerical approach and solves the kinetic equations to discretize the fluid domain. The fluid in LBM is defined as the particle distribution functions. The computational domain of the fluid flow represents the Eulerian grid nodes, each of which consists of a lattice structure. The lattice structure is comprised of the particle distribution functions, which are restricted to move in specific directions. The research work mainly focuses on modeling large turbulent structures on a grid-scale for high Reynolds number flows with the Large Eddy Simulation (LES) model in the frame of LBM. The turbulent motions smaller than grid size are resolved using the popular Smagorinsky subgrid-scale (SGS) model. The study also gives special attention to investigate the effect of the different discrete velocity models of LBM and boundary conditions on the turbulent flow behavior. The results are presented for various turbulent statistics, including phase-averaged velocities, root-mean-square (RMS) velocity, Reynolds stresses, and turbulent kinetic energy (TKE). Moreover, another important work reported in the thesis is the turbulent flow simulation in the stirred tank reactor equipped with dual-Rushton impellers. The study shows the LBM capability to simulate the turbulent flow in such complex geometry. The work also investigates the effect of baffles on the flow hydrodynamics at different impeller clearance. The study compares the results at different impeller clearance in the presence and absence of baffles. The obtained results are validated with the experimental data available in the literature. The thesis work also presents the efficiency of the LBM algorithm on multi-core computer hardware. A highly parallelized computer code was developed using Compute Unified Device Architecture (CUDA) programming language to execute on Graphics Processing Units (GPUs) parallel platform. The computational performance of the algorithm is measured from the Millions Lattice Updates Per Second (MLUPS) parameter. This is obtained from the simulation run-time of the code on the multi-cores of the GPU. The computational scaling of the code is addressed in the study by executing the code at varying numbers of cores. The three-dimensional (3-D) approach of the domain decomposition is employed to increase the scalability. In conclusion, the research studies performed in the present thesis show the LBM viability as a feasible tool for the turbulent flow simulation at high Reynolds numbers with good accuracy and high computational efficiency for various simple to complex flow domains.
Assessment of Human Actions in Videos.
(Indian Institute of Technology Jodhpur, 2020-07) Harit, Gaurav
Humans have the desire to achieve better performance and outcome of their efforts. In performances such as sports, yoga or professions such as surgery, humans strive to attain perfection and efficiency. They mprove their performances by comparing themselves with others or seeking feedback from experts. In this regard the question arises here; can we make a human action assessment system which can support the users with a flexibility of using the system at preferred time and place, thereby avoiding the dependency on a trainer. The key challenge in action quality assessment is the lack of an appropriate metric as it is quite a subjective task with a significant influence of human (expert) bias. The labels like scores or skill levels provided by human judges lack interpretability. Thus, it will be interesting to develop an utomated action assessment system that can bring more interpretability and objectivity to this domain. Action assessment system can be made more objective by considering a set of reference high- cision/expert-level action videos. In this thesis, we propose techniques to assess human actions, where the problem of action assessment is transformed into the problem of comparing a given action video with a reference ideo. We consider two use-cases : Yoga and Sports, and assess actions like Sun Salutation, Diving and Gymnastic Vaults. We contribute a new Sun Salutation Assessment dataset that includes expert and non-expert performances and their respective ground truth judgments. Sun Salutation is a long term complex action with many possible errors and is a good test-bed for human action assessment techniques. Physical exercises like Sun Salutation and Aerobics are repetitive in nature. Such exercises require the performer to achieve consistent dynamic poses and smooth transitions. The quality check for such exercises involves the analysis of attributes such as pace, consistency, smoothness, etc. of the performers. We propose a framework to identify jerky and inconsistent movements in a performance that involves action segmentation using Hidden Markov Model, followed by an inter-pose timing analysis. Based on the performance skill, humans can be divided into experts, mid-level, and amateurs. Amateur performers are prone to miss or wrongly perform a part of some action. We propose a template matching-based approach where the pose sequence of the test performer is compared with an expert sequence and the action segments that were missed or anomalously performed are reported. Template-based matching is a fairly simple approach to identify differences and has difficulty in scaling when the number of templates tends to grow. In practice, actions can be performed correctly in multiples ways. Thus there is a need for comparison of the test sequence to all expert renderings possible for an action sequence. Towards this, we propose an unsupervised sequence-to-sequence autoencoder-based model that learns to reconstruct all expert videos. The skill level of a test performance is judged based on how well the learned model can reconstruct the test sequence. The closer the test performance is to an expert, the more accurately it gets reconstructed. Actions like diving or gymnastic vaults are constrained with limited availability of expert performances, which makes it difficult to train an autoencoder-based assessment model. To address this limitation, we propose a Deep Metric Learning based framework, where a Long Short Term Memory (LSTM)-based Siamese network learns to predict if two videos in a pair are similar or dissimilar based on the difference in their scores. The learned model is utilized for action scoring where the performances are compared with the reference expert performance to determine the score.
Assessment of nonlinear responses and bifurcation analysis of light- weight shaft disk system with differrent loading configuration.
(Indian Institute of Technology Jodhpur, 2020-01) Pratiher, Barun
The flexible rotating shaft with rigid-disk has widely been used in numerous industrial and nonindustrial applications starting from daily used home appliances, transportation, shipping, heavy industries, aerospace, mining, power generation and many more. Identifying characteristics behaviour of the systems and analysing its stability in working environment is very important subject impacting design, control, maintenance and safety. Linear analysis of such systems explores only fundamental characteristics behaviour of the systems, and it becomes difficult to predict the reasons behind a violent behaviour and the catastrophic failure of the system under critical working conditions while presence of the nonlinearities within the system causes undesirable behaviour of the system that may further lead to working instability. To address this need, nonlinear approach becomes more inevitable to indicate and detect the causes of nonlinearities. Thus, objective of this research is to perform nonlinear analysis of the rotating system mounted on flexible bearings with nonlinearity due to large deformation of the shaft and bearings to study the effect of mass unbalance, axial load, rotor-stator interaction and moving base on the system’s stability, bifurcation and prediction of chaotic behaviour. Dynamic model of a flexible rotating system consisting of a flexible shaft with geometric eccentricity, a rigid disk loaded with an unbalance mass and characterized with the nonlinear curvature, axial stretching effect and gyroscopic effect has been developed. A mathematical model of the rotor bearing system is developed using Galerkin’s principle and the extended Hamilton’s principle. Free vibration analysis of the nonlinear rotor bearing system is performed to analyse the effect of nonlinearity on the characteristics behaviour of the system with influence of the disk parameters. Further the study is extended to analyse the forced vibration with the effect of an unbalance mass, a pulsating axial loading and moving platform excitation. Effect of the nonlinearity is monitored considering the different resonance conditions of these different excitations and analyzed the stability for corresponding behavior of the system. A perturbation technique has been used to obtain a set of nonlinear algebraic equations that govern the overall dynamics of the system. The system stability has been studied by investigating the bifurcation and route to chaos upon changing the design parameters such as geometric eccentricity, mass unbalance and disk parameters under the resonance conditions. The present system exhibits a complex behaviour travelling with periodic, quasi-periodic, period-doubling and chaotic on a gradual change of design variables. These complex behaviours have been studied in detail with the illustration of time history, phase trajectories, bifurcation diagrams and Poincare’s map for the each category. Qualitative assessment of bifurcation diagrams has been studied to explore the boundaries of the stable and unstable behaviours and essential dynamics of the systems. Then, the perturbation results are compared with results obtained using direct integration of the equations of motion to verify its compliance. The results are then portrayed using different vibration analyzing tools for better understanding. Further, a non-dimensional equation of motion for the rotor-bearing model is formulated considering the inextensibility condition of the shaft axis. The model is analysed considering nonlinear effect due the inextensible condition under excitations due to an unbalance force, combined effect of an eccentricity and unbalance mass, contact phenomena between the disk and casing. A set of nonlinear algebraic equations have been derived from the nonlinear governing equation to obtain system responses and their stability upon changing the design variables i.e., unbalance and disk parameters under resonance condition due to imbalance and geometric eccentricity as well as rubbing model parameters. Large and violent vibrations are major problems in the light-weight and flexible rotor system. Thus, external damping always needed for effectively controlling and reducing the vibration. The viscoelastic material can provide means to reduce the vibrations and act as a mechanical damper. To analyses influence of viscoelastic properties on the nonlinear behavior of the system, a material for the shaft is considered as viscoelastic. Results are then portrayed using different vibration analyzing tools for better understanding.
Automatic Modulation Classification Using Deep Learning Techniques
(Indian Institute of Technology Jodhpur, 2021-07) Yadav, Sandeep Kumar
Automatic Modulation Classification (AMC) is used to identify the modulation format of the received RF signal without any prior knowledge of the transmitted signal. It is an intermediate step of signal interception and demodulation. AMC has become a prominent area of research in the current scenario due to its use in many military and civilian applications. In the military, modulation identification is used in signal information extraction, jamming signal generation, and radio surveillance. In the civil domain, one of the important applications is adaptive modulation, which enables us to get optimum data rate and reliable communication by deciding the transmitting modulation according to the channel condition provided by the receiver for reliable communication. AMC is also being used for spectrum sensing. The exclusive frequency spectrum allocation to any user for the prevention of frequency intervention causes scarcity of frequency spectrum. This problem is being resolved by detecting frequency utilization in a particular band of spectrum and providing a balance between deficit and under-utilization. It is a basic building block for designing cognitive radios (CR) and software-defined radios (SDR). CR is employed for the identification of an unused frequency spectrum and provides it to other users for different time intervals. In this research work, a method for modulation classification based on the constellation graphical representation is developed. Carrier frequency, symbol rate, and phase offset are the essential parameters that are estimated to extract the constellation points. An efficient way of classification between ASK, PSK, and QAM is proposed. ASK is differentiated from PSK and QAM using linear egression, and further classification between PSK and QAM is done using circle fitting. In further research section, some other methods for modulation classification using deep learning (DL) are developed. DL is a newly addressed area of research in the field of modulation classification. One of the methods for modulation classification based on the Symmetric Dot Pattern (SDP) representation of RF signal is developed. Snowflake images generated by the SDP technique are used to train the Deep Convolution Neural Network (DCNN). Two DCNN models viz. ResNet-50 and Inception ResNet V2, both concatenated by 8 fully connected layers are used for modulation classification. The density of points in the SDP pattern is used to create a grayscale image and RGB components are generated using Adaptive Local Power Law Transform (ALPLT), for color image formation. A hierarchical model of eight stages with each stage doing a binary classification using DCNN is formed. Thesis also includes constellation density matrix (CDM) based modulation classification algorithm to identify different orders of ASK, PSK, and QAM. CDM is formed through the local density distribution of the signal constellation for a wide range of SNR. Two DL models, ResNet-50 and Inception ResNet V2 are trained through color images formed by filtering the CDM. In other work, the two-dimensional Fast Fourier Transform (2D-FFT) of constellation structure is used as a classification feature. CDM is formed using the density spread of constellation points and a 2D-FFT matrix is generated through the two-dimensional Fast Fourier Transform of CDM. A light and efficient DCNN model is designed to classify the modulation schemes of different orders of PSK and QAM. The thesis work also includes a software-defined radio (SDR) based automatic modulation classification. A LabVIEW-based Field Programmable Gate Array (FPGA) implementation of a modulation classification algorithm is proposed. Any modulation scheme among BPSK, QPSK, 8PSK, 8QAM, 16QAM, and 4ASK is classified by alteration of oversampling factor and further error minimization between the extracted constellation and ideal constellation of considered modulation schemes. The developed algorithm is implemented on NI-FlexRIO-7975 FPGA module with NI-5791 adapter and signals for testing are generated using NI-PXIe-5673.
Bandwidth Enhancement of Microwave Absorbers Using Engineered Planar Structures
(Indian Institute of Technology Jodhpur, 2020-02) Dixit, Vivek; Hiremath, Kirankumar R.
Microwaves play a vital role in communications systems viz. Mobile Phones, Bluetooth, Wi-Fi, and so on. Additionally, the microwaves find a wide range of applications in the radar systems for target detection and navigation, microwave ovens for cooking, environmental remote sensing for change and feature extraction, medical systems for the diagnosis of disease and medical treatment. In spite of the wide range of applications, there are certain limitations associated with microwaves viz. Electromagnetic Interference (EMI), dielectric heating effect, and so on. The microwave absorbers are invariably required for overcoming the limitations of microwaves viz. minimizing the EMI between the circuit components for the smooth functioning of the devices, minimizing the health risk by absorbing the unwanted radiations. Additionally, the microwave absorbers are required for lowering the Radar Cross Section (RCS) of the target for defence applications.The thesis presents the design philosophy along with the limitations of different classes of microwave absorbers viz: Salisbury Screen Microwave Absorber, Jaumann Absorbers, Material Based Absorbers and Metamaterial Absorbers. Additional resonance modes can be induced using engineered planar structures to achieve bandwidth enhancement.The thesis describes the application of engineered wire-based absorbers (WBA) for bandwidth improvement. The resonant frequency of WBA varies inversely with the length of the wire element. The cross-polarization of the WBA is almost nil owing to dipole behaviour. Additionally, WBA can be fabricated using a low-cost screen printing process. Multiband viz. single/dual/triple band and bandwidth-enhanced absorbers are designed and realized using engineered wire structure. The bandwidth of the WBA is further improved using capped dielectric absorber. Two resonating modes (WBA and dielectric absorber) are tailored by tuning the thickness of the dielectric layer and wire element length. The designed absorber offers the bandwidth of more than 6 GHz for 10dB return loss.The thesis presents a design approach to improve the bandwidth of Dielectric Material Based Microwave Absorbers (DMBMA). The design comprises of planar square patches of DMBMA placed periodically on the metal-backed FR4 sheet. The bandwidth of 8 GHz (10-18 GHz) is achieved for –10 dB reflections in the proposed absorber. The enhanced bandwidth is attributed to the overlapping of /4 resonance and square patch induced coupling mode.The bandwidth of the conventional Salisbury Screen Microwave Absorber (SSMA) is improved using the square patch and WBA. The bandwidth for square patch-based SSMA is 59.7%. The bandwidth of SSMA is 42.1% for the same thickness. The overlapping of the /4 mode and the additional coupling mode due to square patch, result in bandwidth improvement.Using WBA in combination with the SSMA can improve the bandwidth to 53.5% (8.9- 15.4 GHz) for -10 dB reflection. The FR4 substrate with the SSMA works as Jaumann configuration and introduces an additional resonance mode. The selective overlapping of resonant mode excited by wire element and the additional resonance mode enhances the bandwidth of the absorber.The thesis describes the bandwidth enhancement of multilayer absorbers using engineered planar structures viz. metallic square patch. The fractional bandwidth for -10 dB reflection of the TLMA with the thickness of 6.13mm is 9.7 GHz. In comparison, the fractional bandwidth for -10 dB reflections for square patch-based TLMA is 11.2 GHz.
Bias-Stress Stability and Charge-Carrier Trapping in High Performance Organic Thin-Film Transistors
(Indian Institute of Technology Jodhpur, 2014-12) Tiwari, Shree Prakash
Organic transistors have shown immense potential to be used in flexible, large-area, and low-cost electronic systems, such as pixel drivers in active-matrix organic light-emitting diode displays. However, there are many performance and stability issues to be addressed before these transistors can be employed in the circuitry of commercial systems. The main performance issues are low field-effect mobility and high operating voltage, whereas the stability issues are the degradation of the device characteristics upon exposure to ambient air or to electrical stressing. In this work, low-voltage flexible p-channel and n-channel organic transistors are demonstrated using six promising organic semiconductors. These high-performance organic transistors were subjected to various bias-stress conditions to analyze and compare the electrical stability. A comprehensive study of the environmental and electrical stability was conducted. The benchmarking of these organic TFTs is done with various technologies with respect to the channel sheet resistance and the 10%-current decay lifetime of TFTs. Some of the flexible organic transistors, processed at lower temperature show higher lifetimes as compared to those of a-Si:H TFTs, during bias-stress stability study. The primary reason for the bias-stress effect in organic transistors is the trapping of chargecarriers. One of the techniques to quantify the trapping of charge-carriers is the displacement current measurement. Long channel-capacitors were fabricated using four different organic semiconductors and four different contact metals in order to measure the number of chargecarriers injected into and extracted from the organic semiconductor, along with the density of trapped charges in the device, in order to better understand the trapping dynamics in organic transistors.
Biophysical Approach to Develop Inhibitors against Protein Aggregation
(Indian Institute of Technology Jodhpur, 2016-08) Kar, Karunakar; Sahu, Satyjit
Self-association of proteins into higher order structures such as amyloids and collagen assemblies is a fundamental process in biology. In nature, the self-assembly process of triple helical collagen molecules is known to generate higher order structures which are vital to both structural and functional properties of extra cellular matrix. However, the process of amyloid formation of proteins is mostly linked to many health complications including a series of neurodegenerative diseases. Until now, ~40 different proteins including huntingtin, #-synuclein and lysozyme are known to form disease-linked amyloids. To understand the mechanism of diseases linked to amyloid formation and excess collagen accumulation, it is critical to unravel the underlying principles of such process of self-assembly of soluble proteins/peptides into insoluble higher-order structures. This work has explored the effect of selected proteins, natural compounds and surface-functionalized nanoparticles on the aggregation of both collagen and amyloidogenic proteins. Different biophysical techniques were used to understand the effect of these compounds on the conformation, activity and aggregation properties of selected proteins. Further, in silico studies were performed to identify crucial biomolecular interactions. Important findings are: (a) type I collagen prevents amyloid formation of lysozyme; (b) evidence of rapid coaggregation among proteins during amyloid formation; (c) capsaicin inhibits collagen fibril formation and increases the stability of collagen fibers; (d) eugenol prevents amyloid formation of globular proteins; (e) strategically designed surface-functionalized nanoparticles show anti-amyloid activity. These findings improve our mechanistic understanding of protein aggregation process which may possibly facilitate the development of therapeutics against pathologies related to protein aggregation.
Bioremediation of Low Level Uranium (VI) Waste Including Denitrification Using Microbial Fuel Cell
(Indian Institute of Technology Jodhpur, 2019-01) Chhabra, Meenu
Nuclear wastes emerging from nuclear fuel cycle plants are generally rich in nitrates and heavy metals like Uranium. Nitrate and uranium have been identified as the major groundwater contaminants. Microbial fuel cells (MFCs) have the potential for denitrification and power production. However, the reported rates of denitrification in MFCs are low and there are no reports of U (VI) removal and/or simultaneous nitrate and U (VI) removal in a MFC. In this work, denitrification rate in a MFC is improved first by identifying an effective microbial consortium. High-rate denitrifying MFCs were developed using cow manure and soil. Further, the consortium was acclimatized under autotrophic (AD) and heterotrophic (HD) conditions to compare the power output and nitrate removal rate. The microbial communities were identified and found to exhibit resilience and high diversity. AD supported high power and HD supported high nitrate removal rate. Also, the abundance of denitrifying genes was assessed and they were present in both the conditions. The U (VI) was removed as a phosphate precipitate. Microbes at cathode produced phosphatase which liberated phosphate from an organic compound. Nitrate acted as an electron acceptor thereby allowing simultaneous nitrate and U (VI) removal. The work is extended to real low level effluents from nuclear fuel recycle division at BARC (Bhabha Atomic Research Centre), Mumbai. The MFC removed nitrate from these wastes while supporting power generation. In summary, this thesis work demonstrates the application of MFC for the removal of nitrate and U (VI) from contaminated water.
Blind Signal Modulation Recognition through Clustering Analysis of Constellation Signature.
(Indian Institute of Technology Jodhpur, 2020-09) Yadav, Sandeep Kumar
Blind Signal Modulation Recognition (BSMR) detects the type of modulation in the intercepted signal. BSMR is an intermediate step between signal detection and its demodulation. It is becoming an active research area due to its application in many military scenarios like surveillance and electronic warfare, which requires a type of modulation in intercepted signals to prepare jamming signals. BSMR gained more attention in cognitive radio (CR) as it is widely used for civilian applications like spectrum management, link adaptation to overcome from the problem of spectrum under-utilization. Most of the approaches for modulation classification are based on the modulated signal’s component, but the modulation type can be best identified with the use of the constellation diagram. Modulations with well-defined constellation structure viz. ASK, PSK, and QAM are considered for classification.BSMR involves two steps: first is preprocessing of the received signal in which different parameters are estimated like carrier frequency, symbol rate, channel state information, timing, and waveform recovery, etc., and the second step is the algorithm to classify the modulation format. In this research, the constellation signature from the blind signal is extracted in different channel scenarios. As the constellation points form clusters in the I-Q plane, different clustering algorithms have been adopted for modulation classification between ASK, PSK, and QAM modulation schemes. Noisy data points corresponding to the same symbols are considered as a single cluster. The order of modulation can be obtained by estimating the correct number of clusters. This is done using the Density-based Ordering Points To Investigate the Clustering Structure (OPTICS) clustering algorithm. For modulation domain estimation, i.e., ASK, PSK, or QAM, k-means clustering and linear regression techniques are employed. In other work, different numbers of cluster centers are estimated using k-medoids clustering. A similarity function for calculating resemblance with ideal constellation structure is defined. It gives a decision in favor of the highest similarity score. The work is further extended to classify the FSK modulation scheme. A hierarchical and local density (HLD) approach is proposed to classify modulation schemes in a two-stage process. Local densities are calculated around the ideal points and compared for final modulation classification. Further, slow and flat fading channels and non-Gaussian noises are considered. A new method to estimate symbol rate and phase offset of the unknown blind baseband signal is developed. The symbol rate is estimated using the spectrum of the instantaneous phase of the complex baseband signal. The phase offset is determined based on the symmetrical structure of the constellation. A software-defined radio (SDR) based implementation of blind signal modulation recognizer (BSMR) on field-programmable gate array (FPGA) is developed. The system works without any prior knowledge of the received signal. The algorithm is deployed on NI-FlexRIO-7975 FPGA with the NI-5791 adapter using LabVIEW. The algorithm is optimized to use minimum hardware resources and facilitate future up-gradation. Signals for testing are generated using NI-PXIe-5673 (RF transmitter), and the system detects the modulation type in 81.451 msec under the AWGN channel.
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
Characterization of Clay Ceramics Based on Reuse of Organic Residue and Industrial Wastes for Point of Use Water Filtration Application
(Indian Institute of Technology Jodhpur, 2018-06) Plappally, Anand K.
Frustum shaped ceramic water filter manufacturing technology has been introduced in different parts of India, scilicet Jodhpur district in Western Rajasthan, Tindivanum and Thiruvallur in Tamil Nadu and Samastipur in Bihar. The dissemination of the manufacturing technology was carried out among traditional potter families residing in these rural locations. The purifying receptacle of this water filter (named G Filter locally) in Western Rajasthan is made of low-cost raw materials - clay and sawdust taken in equal volume fractions. United Nations and NGOs such as Potters for Peace, (Nicaragua) Pure Home Water Filters (Ghana), RDIC Cambodia, Potters Without Borders etc. promote such low cost point of use gravity-based ceramic water purifiers across the globe to societies affected by water contamination or water scarcity due to natural calamities, economic scenarios etc. More than a score of dissertations and graduate thesis from around the globe during the last two decades exemplify the importance of ceramic water filtration through similar frustum shaped low-cost water filters. Gravity-based filtration theory, microbial contamination removal, organic and inorganic contaminant removal, porous media flow theory, strength of brittle clay ceramics, public health behavior, clay-based manufacturing, wear, surface physics, transport phenomena, clay science, wood technology, material characterization, production, environmental science, marketing, rural development, customer satisfaction, household water treatment systems and socio-economic related to these filters are the research areas which can be cited while performing this work. Firstly, the thesis is encouraged views of traditional potters of India. G Filter was introduced using a traditional blended manufacturing approach with mechanized forming at the different location. Traditionally, potters decode the efficacy of the clay artifacts by visual appearance and touch. This would mean that surfaces may hold answers to the strength and functionality of the ceramics manufactured. Indirectly ceramic surface characterization in terms of its roughness, pore, pore density, porosity will affect the strength. Compressive strength decreases polynomially with increasing surface roughness of clay-organic fraction ceramics (porous clay ceramics). The degree of the surface roughness increased proportionally with pore density. Fracture toughness of these materials decreased in a linear order with the increase in surface roughness. Furthermore, the fracture toughness also followed linear transformation with the sawdust used as a raw material while manufacturing the clay ceramics. Composition characterization of fired clay ceramics showed the presence of fluxing compounds which contributed to their densification. The clay ceramics with equal volume fraction of clay and organic filler (50O) were characterized by the highest frequency of pores oriented orthogonal to the surface. This result affirms the feasibility of use of such clay ceramics for separation processes. The ceramic showcased more than 2 log reduction value while filtering E. Coli contaminated water. Secondly, traditional potters from Bihar questioned the ability of the water filters to separate arsenic from their household groundwater supplies. This diverted attention to the search for local low-cost methods to separate arsenic in drinking water using distinct material modifications to the fired clay ceramics (50O). There are numerous decades of research on Fe and its reaction with arsenic in water to form large complexes which can be separated using adsorption and filtration methods. Bihar is home for India’s iron production and use. Hence locally available Fe fines could solve the local arsenic contamination of groundwater in the region. The clay ceramic (50O) was modified by limited volume addition of Fe fines to the clay and organic material mixtures to form new Fe additive based ceramics (FCC). FCC ceramics when tested for arsenic adsorption, displayed high arsenic removal efficiency of 99% for a contact period of 90 mins. The Freundlich and Langmuir isotherm models well with the equilibrium adsorption data. The addition of ferrous waste enhanced arsenic removal efficiency of clay ceramics between 3 pH to 7 pH. The 99% E.coli removal was found in FCC based ceramics. The mechanical strength of the clay ceramics was found to be nearly doubled with the incorporation of ferrous material. Finally, the thesis is set in rural parts of Western Rajasthan dotted with abundant clayey soil and limestone mining locations. There are several studies where calcium based salt solutions treat arsenic-contaminated waters. The clay ceramics (CC or 50 O) was now modified by adding limited volumetric quantities of marble to the clay and organic material mixture to form new marble based ceramics (MCC). The addition of marble enhanced the arsenic removal efficiency of porous clay ceramics (CC). The MCC followed Freundlich adsorption model. The antibacterial property of marble removed microbes from the effluent. This proposed a low-cost alternative for enhancing microbial removal efficacy of ceramic filters. Marble addition greatly enhanced compressive strength and fracture toughness of the clay ceramics. The implication of the study is on the design and development of low-cost ceramics for use in household water treatment. Moreover, the study indicates possible scale-up of G filter for treating specific contaminants. The new material developed presents a low cost option, easy manufacture and can be implemented within a constructed wetland system where targeted removal of specific contaminants is required from large volumes of surface or groundwater.
Chemical Vapor Deposition Grown MoS2 for Sensing Applications.
(Indian Institute of Technology Jodhpur, 2020-10) Kumar, Mahesh
Since the isolation of graphene in 2004 by Geim and Novoselov, two-dimensional (2D) materials have been opened new avenues for developing next-generation electronics devices. 2D semiconducting MoS2 with a tunable bandgap, being the frontrunner of layered transition metal dichalcogenides (TMDCs) family has grabbed the renewed interest of the research community by providing unprecedented device performance at the atomic scale. This thesis work is focused on most vibrant gas and light sensing applications of chemical vapor deposition (CVD) grown 2D MoS2.Different nanostructures including horizontal flakes, vertical flakes and nanowires network of the MoS2 were synthesized by using the CVD process and examined their gas sensing characteristics to explore the role of different adsorption sites of MoS2. It was observed that edge sites of MoS2 exhibit higher gas adsorption compared to that of terrace sites on the basal plane of MoS2 because edge sites have a large number of dangling bonds as well as high d-orbital electron density. In this context, the MoS2 nanowires sensor with high edge sites-to-volume ratio exhibited better sensitivity with detection limit to 4.2 ppb NO2 as compared to that of horizontal and vertical aligned MoS2. Further, defect and interface engineering were simultaneously utilized for improving the gas sensing performance of the MoS2 sensor. Optimal sulfur vacancies as defects were deliberately created in vertically aligned MoS2 via thermal annealing and then, rGO nanoparticles were loaded on the sulfur vacancy containing MoS2 (Sv-MoS2) for forming rGO/Sv-MoS2 heterojunctions. P-type rGO changed the intrinsic n-type semiconducting behaviour of MoS2 into p-type via enhancing charge transfer through chemical bonding in between rGO and Sv-MoS2. As a result, p-type rGO/Sv-MoS2 sensor exhibited excellent sensitivity to NO2 with complete recovery at low temperature (50 °C) by exploiting electronic and chemical sensitization.Despite the high sensitivity to NO2 gas at room temperature, slow response and incomplete recovery restrict MoS2 usage on a commercial gas sensing platform. To address slow response/recovery kinetics, MoS2 gas sensor was tested under thermal and optical energy sources. The temperature was capable to achieve full recovery with the expense of sensitivity, however, the sensor showed enhanced sensitivity with complete recovery at room temperature under UV light irradiation. In addition, nucleation controlled one-step CVD process to synthesize MoS2–MoO3 hybrid micro flowers using vapor transport process was developed. The MoS2–MoO3 hybrid sensor showed good response to NO2 gas with complete recovery at room temperature without using any extra energy source (temperature or UV light). This research work helps to remove the microheater from commercial metal-oxide gas sensor technology due to gas detection at room temperature.In the last part of the thesis, 2D MoS2 is also explored in optoelectronics application via fabricating a photodetector using a van der Waals heterostructure of the MoS2 and rGO. This vertical out-of-plane rGO/MoS2 heterojunctions exhibited high responsitivity and detectivity in visible range wavelengths with excellent stability in air ambient as a result of the synergistic effect of enhanced photoexcited carrier density and photogating effect. The potential challenges and future perspectives in the emerging MoS2 research for sensing applications are also discussed.
Close Shell Metal Oxides for Solar Cell and Water Treatment Application
(Indian Institute of Technology Jodhpur, 2017-01) Sharma, Rakesh Kumar
Current study reveals simple and unique additive free synthetic method to prepare both nanocrystals and nanorods structures at sub-zero temperature using easily accessible chemicals. The role of sub-zero reaction temperature from 40 to 10 °C on the structure of TiO2 and phase transformation between anatase to rutile have been investigated. The current work also throws light on the role of temperature in dimension control of titania nanostructures. The current investigation explores the agile architecture of nanostructures and smart combination of semiconducting close shell metal oxide materials where, novel mesoporous solid nanospheres of ZnO-TiO2 with type-II heterojunction reduces the recombination, and synergistically enhances the electron mobility and charge collection capability. Also, substantial efforts have been focussed on the phase tunable synthesis of TiO2 for improving the charge recombination in TiO2. The band gap engineering of TiO2 is highly important for its effective utilization. Hydrogenated TiO2 nanospheres at a low doping concentration of HfO2 nanodots exhibited pronounced optical absorption and light scattering effects. The hydrogenation of TiO2 shifted the band gap to IR while HfO2 doping reverted the optical bandgap to the visible region. All prepared TiO2 have been explored as photoanode material in DSSC. Collaborative role of the mixed phase and different morphology remarkably shows enhancement in both photocurrent density and photoconversion efficiency. With high specific surface area, pronounced optical absorption and light scattering effects of close shell metal oxides nanosphere exhibited a significant increase in the performance of DSSC. Interestingly, the smaller active area of photoanode emerged as a key elevating factor. Also, graphene associated with various substrate was also found to be promising candidate to replace Pt counter electrode. To remove hazardous contaminants like Cr(VI) and organic industrial waste dyes, simple, high removal efficiency, low-cost, ease of operation and cost effective photo assisted filter membrane method was introduced. The hole-scavenger have been also used in photoreduction of harmful contaminants in air atmosphere. All synthesized materials have demonstrated superior activity to the Cr(VI) photoreduction. The catalyst has also demonstrated good recoverability as well as recyclability.
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
Complex Network Generative Models Using Corona Product of Graphs
(Indian Institute of Technology Jodhpur, 2017-11) Adhikari, Bibhas
Complex networks are ubiquitous in natural, technological and social systems. In this thesis, we propose complex network generative models based on corona product of two graphs. A major feature of this framework is that it gives a visual understanding of the network generation process which helps in deriving many properties of the resulting networks analytically. We propose four network generative models among which two models are deterministic and we call them corona graphs and self-organized corona graphs (SoCG). Both of these models are defined by a network motif. Indeed, corona graphs are defined by taking the corona product of a network motif with itself iteratively. The network motif which defines a resulting corona graph, is called the seed graph for the corona graph. We investigate certain structural properties of corona graphs including degree distribution, diameter, and node betweenness distribution. We also derive computable expressions for eigenvalues, Laplacian eigenvalues and signless Laplacian eigenvalues of corona graphs defined by certain seed graphs. It is observed that the cumulative degree distribution of a corona graph decays exponentially when a large number of iterations is considered to generate the corona graph. This observation conveys a limitation of corona graphs in employing them as practical models for many real networks since a real network often exhibits power-law in the tail of its degree distribution. Thus we define a self-organization process for link generation in each step of the generation of a corona graph in addition to the links defined by the corona product itself. This provides a new network generative model which we call self-organized corona graphs (SoCG). We observe that SoCG inherit a hierarchical pattern in its structure and the degree distribution follows power-law in its tail when a large number of iterations is considered. In addition, we investigate the diameter and clustering coefficient of SoCG which establish that SoCG are small world and SoCG have high clustering coefficients for certain seed graphs. Obviously, large SoCG inherit a motif which is the seed graph itself. We compare the spectral radii and algebraic connectivities of SoCG with that of corona graphs using numerical simulation. We also analyse the count of different network motifs that are inherited by large SoCG defined by certain seed graphs. The next model which we propose in this thesis is called generalized corona graphs defined by Erd ¨ os-R ´ enyi graphs (GCG-ER). This model is inspired by exploring the idea of corona graphs defined by Erd ¨ os-R ´ enyi (ER) graphs. Here, we consider a simple connected graph on n 2 nodes initially and the definition of generalized corona product of graphs is employed to add ER graphs (having n nodes) with the existing nodes, picked randomly where all such ER graphs have a fixed edge probability. We continue the process iteratively and hence generate a large network. Thus, in GCG-ER, the deterministic links are generated due to the definition of generalized corona product of graphs, and links with a fixed link-probability are introduced due to the addition of ER graphs in each step of the generation of the resulting network. We investigate certain structural properties of these graphs that include degree distribution, average path length, node betweenness distribution, expected number of triangles and the average clustering coefficient. Finally, we propose a stochastic model for generation of complex networks inspired by the generalized corona product of graphs and we call the resulting graphs as stochastic corona graphs (SCG). First we define generalized stochastic corona product of graphs and use it to define SCG in which existence of all the possible edges are defined with a fixed probability. This model can also be explained as GCG-ER in which the deterministic links and the initial deterministic connected graph in GCG-ER are converted as links with a fixed probability, say p; and an ER graph with edge-probability p respectively. We also demonstrate a social perspective for formation of these graphs. We investigate the degree distribution, expected number of triangles and the average clustering coefficient of these graphs.
Computational Gastronomy: Analysis of the basis of flavor in Indian cuisine and health impact of spices
(Indian Institute of Technology Jodhpur, 2020-01) Bagler, Ganesh
Cultures across the world have evolved diverse culinary repertoires that form an integral part of their identity. Traditional recipes have been shaped to incorporate ingredients driven by their taste and health considerations. The study of culinary practices has hitherto been mainly under the purview of humanities and social sciences. In this thesis, we take a computational gastronomy approach to conduct a data-driven investigation of traditional Indian recipes to study the basis for their flavor composition and health impact of culinary herbs and spices. The first part of the thesis explores the basis of flavor in Indian Cuisine through the principle of food pairing applied to its traditional recipes to show what ingredient combinations are generally followed in a typical Indian recipe and its regional cuisines. The study provides a basis for designing novel signature recipes, healthy recipe alterations and recipe recommender systems. Further, the thesis presents a repository of flavor compounds, FlavorDB, a comprehensive database for the exploration of flavor compounds in food ingredients. The latter and final sections of the thesis unearth the health significance of key dietary ingredients, spices and herbs from data available via published biomedical literature. By carrying out a data analytical approach, the thesis provides valuable insights into their therapeutic utility. Further, by integrating spice-phytochemical-disease associations, we identify bioactive spice phytochemicals potentially involved in their therapeutic effects. The results and data from this investigation are compiled and presented in the database SpiceRx.In summary, we take a data-driven approach to investigate the data of traditional Indian recipes to identify culinary fingerprints of its regional cuisines. Our computational gastronomical analysis led to the identification of spices as the molecular fulcrum of Indian recipes. We further investigated the therapeutic effects of culinary herbs and spices to highlight their broad-spectrum benevolence. We also created a data repository of flavor compounds (FlavorDB) and an integrated resource for empirical evidence of the health impacts of culinary herbs and spices (SpiceRx). We believe that these studies will provide an impetus for data-centric investigations of food, flavor, health and their related applications.
Conflicts in Geometry
(Indian Institute of Technology Jodhpur, 2017-11) Banik, Aritra; Banerjee, Subhashish
The thesis is motivated by what are called choice problems in computer science literature. Here, we define conflicts on the objects in some underlying classical problem such that it precludes some objects from being part of the solutionon if some others are in the solution.

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