Doctoral Theses

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Role of MGRN1 E3 Ubiquitin Ligase in Protein Quality Control Mechanism and Polyglutamine Diseases
(Indian Institute of Technology Jodhpur, 2014-11) Mishra, Amit Kumar
Proteins are major catalytic biomolecules of the cells that are maintained in their dynamic steady state levels by regular renewal. Cells achieve this through synthesizing new proteins and degrading damaged or misfolded proteins. Improper or poor folding of nascent polypeptide generates a continuous cytotoxic threat. Misfolded proteins, if accumulated, may cause malfunctionality, and subsequently cell death. Neurons are post-mitotic cells, hence are more vulnerable towards such cellular insult. The basic mechanism of protein quality control system, comprising of folding and degradation machinery, is however known, yet the details of all its components and comprehensive mechanism as well as the interplay remain obscure. Current study reveals that Mahogunin Ring Finger 1 (MGRN1), an E3 Ubiquitin ligase, earlier found to be involved in mouse coat color, is sensitive to cytotoxic stresses and gets elevated in these conditions. The current investigation explores the role of MGRN1 as a novel protein quality control E3 Ubiquitin ligase and shows that it suppresses the misfolded protein aggregation and cytotoxicity. MGRN1 interacts with Hsp70 protein in cells. All such characteristics have generated scope to investigate the role of MGRN1 in neurodegenerative diseases and interestingly, it was observed through the studies on polyglutamine proteins that MGRN1 suppresses the expanded polyglutamine protein aggregation. MGRN1 was also found to be associated with the polyglutamine aggregates in Huntington disease model mice brain. Investigating such novel quality control E3 Ubiquitin ligases may add to our knowledge about protein quality control system and neurodegeneration, which may in turn help in developing therapeutics to such devastating pathological conditions.
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.
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.
Mitigation of Negative Impedance Instabilities in DC/DC Converters and DC Microgrids using Nonlinear Control
(Indian Institute of Technology Jodhpur, 2015-07) Fulwani, Deepak M.
There has been increasing interest in dc microgrids since beginning of the first decade of 21st century. This is also witnessed by the quantum of work contributed by the community, many pilot projects around the globe, and many special issues of learned journals dedicated to the topic. Multi-converter dc distribution systems or dc microgrids are treated as one of the key enabling technologies, among many, towards the development of modern smart grids. DC distribution systems offer inherent benefits of higher power transfer capacity of lines, no reactive power and frequency control requirements, and avoidance of multiple power conversions when the source is dc, resulting in simple control structures, higher efficiency, and cost effectiveness. However, tightly regulated Point-of-load Converters (POLCs) in a multiconverter dc distribution system having cascaded structure, behave as Constant Power Loads (CPLs) when control bandwidth of load converter is sufficiently higher than that of feeder converter, and introduces a destabilizing effect into the system. This destabilizing effect of CPLs due to their negative impedance characteristics, may lead to reduced system damping, significant oscillations in the dc bus voltage, and sometimes voltage collapse. The linear control techniques, providing operating point dependent performance, are insufficient to stabilize a system with high penetration of CPLs, and fails to ensure required performance and large signal stability, in the presence of CPLs and uncertainty. Therefore, the application of robust nonlinear control techniques to stabilize the power electronic converters in multi-converter cascaded dc distributed system or dc microgrids under high penetration of CPLs, is one of the ways to address the issue. This thesis addresses the mitigation of the destabilizing effects introduced by CPLs in different non-isolated dc/dc converters and Photo-voltaic (PV) based islanded dc microgrid using robust non-linear Sliding Mode Control (SMC) approach. Novel sliding mode controllers are proposed to mitigate negative impedance instabilities in dc/dc boost, buck, buck-boost, bidirectional buck-boost converters and islanded dc microgrid. In each case, the condition for large-signal stability of the converter feeding a CPL is established. SMC based nonlinear control scheme for an islanded dc microgrid feeding CPL dominated load is proposed to mitigate the destabilizing effect of CPL and to ensure system stability in various operating conditions. A limit on CPL power is also established to ensure the system stability. For all proposed solutions, simulation studies and experimental results are provided to validate the effectiveness of the proposed sliding mode controllers.
Improving Security in Wireless Sensor Networks through Bio-Inspired Approaches
(Indian Institute of Technology Jodhpur, 2015-10) Badarla, Venkata Ramana
A Wireless Sensor Network (WSN) is a network made up of a set of sensor nodes and gateway nodes where sensor nodes monitor physical parameters such as temperature, moisture etc. and send it to gateway nodes. Security in WSN plays an important aspect since it provides sustainability to the network. Security threats can be introduced in WSN through various means, where the ongoing data transmissions can be tampered with or the nodes can be altered to behave in an unpredictable manner. The proposed research work uses biological inspirations and takes aspects from machine learning and social psychology for improving security in WSNs. The proposed work is a two-step model, where the detection of fraudulent nodes is the first step and reducing the effect of these nodes using bio-inspirations is the second step. For detection of fraudulent nodes, two approaches based on machine learning and social psychology has been proposed. The machine learning model is based on techniques like k-means and Support Vector Machine. Sociopsychological model is another model which is less complex to deal with fraudulent node detection. It enhances the performance by taking concepts from social psychology. After the detection of the fraudulent nodes, an immune model is instantiated. Biological immune systems have intelligent capabilities of detecting foreign bodies which attack our body. Moreover they have inherent insightful capabilities to remember the same foreign body when it hits the body again. In this work, a similar healing procedure is instigated in WSN to quickly recover from the attack. The proposed work has been implemented in LabVIEW platform and extensive simulations were carried out to study its performance for the metrics such as detection and recovery time, reliability, robustness, scalability, complexity etc. Further, it is experimentally evaluated on hardware test bed of size 16 nodes to obtain results that demonstrate the accuracy and robustness of the proposed model.
Reconfigurable Architecture for Cross Layer Design Optimization and its Applications
(Indian Institute of Technology Jodhpur, 2016-02) Yadav, Sandeep; Badarla, Venkata Ramana
Sharing of physical (PHY) and medium access control (MAC) layer knowledge with the higher layers in wireless networks provides efficient methods of allocating network resources and applications over the Internet. Cross Layer Design (CLD) refers to protocol design done by actively exploiting the dependence between protocol layers to obtain performance gains. This thesis presents a new cross layer protocol which uses the knowledge of radio's front end impairments to build reconfigurable MAC and PHY layers and demonstrates its performance via implementation on an experimentation system. One needs to be aware that any proposed cross layer design optimizations must be carefully evaluated on experimentation systems, which are optimized to meet the requirements of the particular layer being modified. A novel contribution of the thesis is the presentation of a framework for objectively evaluating various experimentation systems. The proposed framework, which contains metrics such as cost, latency and throughput, will help designers make informed trade-off decisions between various requirements and develop systems most optimized for CLD. The thesis evaluates various platforms using the proposed framework and shows that, while these platforms have significantly accelerated the pace of PHY layer research, they are not perfectly suited for MAC layer research. To overcome this gap, the thesis presents a new hardware architecture which is specifically optimized for MAC layer requirements, such as latency, processing speed, and cost. The thesis demonstrates how availability of commercial technology and careful trade-off is making it feasible to design such a system.
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.
Development of Spectrally Selective Absorber Materials and Coatings for Photothermal Applications
(Indian Institute of Technology Jodhpur, 2016-08) Dixit, Ambesh; Vijay, Vivek; Chhibber, Rahul
"Solar energy is one of the most abundant renewable energy sources, which can be converted (i) directly into electricity using solar photovoltaic, and/or (ii) into thermal energy, which later can be used for numerous applications including electricity generation. The latter one is called as solar thermal technology, where Sun energy is concentrated onto a receiver for its maximum absorption with minimum thermal emission in the desired spectral range simultaneously for efficient conversion into thermal energy. An ideal spectrally selective absorber surface exhibits absorptivity “? ~ 1” in the solar wavelength range and emissivity “? ~ 0” in the infrared wavelength range to convert the entire incident solar irradiation into thermal energy, without any thermal loss. Thus, the development of such spectrally selective coatings is essential to meet the requirement. In addition, these coatings should withstand high operating temperatures and large thermal cycling, without any significant degradation in their solar thermal performance. Black chrome (Cr-Cr2O3) is one of the most extensively studied and commercialized spectrally selective absorber coatings for photothermal applications. Nevertheless, corrosion and thermal stability of black chrome coating are still challenging. The work has focused on improving the corrosion and thermal stability by introducing the nanoparticle (NP) in the black chrome spectrally selective coating matrix. The graphite encapsulated FeCo NPs are used in the black chrome electrolytic bath to synthesis FeCo(C) NPs modified black chrome thin films. These modified black chrome thin film structures have showed enhanced thermal stability and corrosion resistance, as compared to pristine black chrome structures. In addition, the work has also focused on design and development of reflector-absorber tandem spectrally selective coating structures for high temperature applications. These are based on Zr refractory material as a reflector in conjunction with ZrC-ZrN absorbers. The developed ZrOx/ZrC-ZrN/Zr/substrates structures suggest that these coatings can be used upto 700ºC in vacuum on SS substrates and upto 200ºC in ambient conditions without any significant degradation in their solar thermal performance. The corrosion studies on these structures are carried out in 3.5 wt.% NaCl electrolyte solution and observed that these structures are highly corrosion resistance. The corrosion rate is ~ 0.000054 (mm/y), which is much lower, as compared to both stainless steel and copper substrates. These studies suggest that the developed ZrOx/ZrC-ZrN/Zr structures may be used for high temperature applications under the adverse conditions such as saline environments
RF Sputtered ZnO Nanorods based Hydrogen Sensor
(Indian Institute of Technology Jodhpur, 2016-11) Kumar, Mahesh
Hydrogen is an emerging energy source which is known as "The fuel of future". It is extensively used in thermal power plants, hydrogen engines, fuel cells etc. Storage of hydrogen is quite challenging due to its highly inflammable nature even at 4% hydrogen in air. Therefore, for optimum surveillance of hydrogen gas, an energy efficient gas sensors with low operating temperature, high sensor response and selectivity, compact size and radioactive environmental stability are desired. 1-dimensional nanostructures grab all attention as they work as building blocks for miniaturized gas sensors with low power consumption. Nanorods based gas sensors show relatively high response at low working temperature even with minimal gas concentration. Detection at ppm level is achieved due to the availability of large surface reaction area with high surface to volume ratio. ZnO is wide band gap and n-type semiconductor material which have high thermal stability and high conducting electron mobility. This thesis mainly comprises of deposition of well-aligned ZnO nanorods and nanocrystalline thin films using sputtering technique where deposited ZnO nanorods are highly crystalline and are grown along c-axis with high optical properties and less number of intrinsic defects. Electrical characterization of ZnO nanorods/Si heterojuncton is also studied which shows rectifying behaviour along with strong dependence of barrier height on operating temperature. Deviation in Richardson constant is observed due to presence of barrier inhomogeneities at junction, which was further modified using double Gaussian distribution of barrier height. Then hydrogen sensing mechanism for Ohmic ZnO nanorods/Si heterojunction was proposed that gave fast response time of ~27 seconds at low operating temperature. For further enhancement of sensor response, Schottky contacted Au/ZnO nanorods based sensors were fabricated that showed sensors.
Nanoparticle Based Inhibitors to Target Protein Aggregation
(Indian Institute of Technology Jodhpur, 2016-11) Kar, Karunakar
Self-assembly process of proteins into defined higher order structures is a fundamental process which influences both structural and functional properties of many tissues in human body. Formation of amyloid fibrils due to protein aggregation is known to cause several medical complications such as the onset of various neurodegenerative diseases, complications during DNA-recombinant synthesis and formation of aggregates during storage of protein therapeutic agents. Because the process of protein aggregation has lethal impacts, it is necessary to find effective strategies to target such aggregation process. One of the straightforward strategies for targeting protein-aggregation linked diseases is to find potential inhibitors against such aggregation process. This work has focused on making of stable and effective nanoparticles coated with inhibitor molecules to target the amyloid aggregation of selected globular proteins, considering them as convenient model amyloidogenic proteins. This work has also explored the effect of selected surface-functionalized nanoparticles on collagen fibril formation. First section of this thesis covers a fundamental investigation of amyloid aggregation of a single metabolite phenylalanine and its effect on amyloid formation of globular proteins, exploring the critical role of hydrophobic and aromatic side-chains during protein aggregation. Next sections of this work have explored the inhibition effect of piperine-coated gold nanoparticles and capsaicin-coated silver nanoparticles against aggregation of insulin and serum albumin respectively. Finally, the inhibition effect of nanoparticles coated with aromatic residues has also been tested on collagen fibril formation under in vitro conditions. The results signify a unique approach to target protein aggregation through nanoparticle based inhibitors.
Effects of High Energy Radiation on Perovskite Oxides for Voltage Tunable Applications
(Indian Institute of Technology Jodhpur, 2016-11) Kumar, Mahesh
In current scenario, the communication system demands compact size of components with multiple functionality. To meet these requirements, there has been rapid growth in tunable RF and microwave components of communication systems for voltage tunable applications. Voltage-dependent permittivity and lower dielectric loss are the desirable characteristics for the current and next generation tunable microwave applications. Perovskite oxides such as (Ba,Sr)TiO3 (BST) and Pb(Zr,Ti)O3 (PZT) have considered a promising material for applications in tunable microwave devices with their voltage-dependent dielectric permittivity and high dielectric constant. Communication satellite and nuclear industry applications include communication frequency filter where the devices are exposed to high energy radiations. The goal of the undertaking this work was to fabricate tunable components and study the changes in the electrial and material properties of BST and PZT, exposed to high energy radiation. In the present study, radiation dependence of dielectric capacitance and tunability in the perovskite oxides thin films have been explored. BST thin films were deposited on sapphire substrate by RF magnetron sputtering technique and interdigitated capacitor (IDC) structures were fabricated using photolithography. Gamma and neutron irradiation induced changes of the BST based tunable capacitor have been investigated and it was found that capacitance of the IDC devices decreased with increasing radiation doses up to a certain level and subsequently with higher radiation level capacitance gradually increases. The observed tunability (~25%) of the un-irradiated BST device was observed nearly constant with irradiation doses and found higher radiation tolerance for its use in space and nuclear application. The surface morphologies and leakage current of these films were also investigated as a function of radiation doses. X-ray photoelectron spectroscopy was used to investigate the surface chemical states of gamma-irradiated BST thin films and core level shift was observed towards higher binding energy with increasing gamma doses. Further, Epitaxial heterostructure of ferroelectric PbZrTiO3/SrRuO3 (SRO) were grown on single crystal SrTiO3 (001) substrates by pulsed laser deposition technique and platinum electrodes were deposited on top of PZT film. The tunability of the PZT varactor devices strongly dependent on bias voltage and exhibited dielectric tunability of 55% at 100 kHz and 10 V. The dielectric capacitance was found to decrease with enhancing gamma irradiation doses, accompanying chnages in the loss tangent values. The tunability of the epitaxial PZT thin film capacitors observed to decrease linearly up to 25% with increasing gamma dose at 400 kGy dose. Moreover, surface chemical states of epitaxial PZT films were investigated by X-ray photoelectron spectroscopy as a function of gamma doses. An anomalous behavior was observed in Pb4f states and core level of Pb4f state shifted towards lower binding energy due to reduction of PbO to metallic Pb with increasing gamma doses. Higher current and disappearance of Negative differential resistance characteristics were found in higher gamma dose which confirms the presence of metallic Pb. The results achieved from this study would be highly valuable in order to predict operational performance of such devices in radiation environment.
Ferroics and their Rubber Composites for Wide-band Microwave Absorption
(Indian Institute of Technology Jodhpur, 2017-01) Dixit, Ambesh; Vadera, Sampat Raj
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.
Supported Chiral Platinum Nanoparticles for Asymmetric Catalysis
(Indian Institute of Technology Jodhpur, 2017-02) Sharma, Rakesh Kumar
This study draws attention towards supporting materials, such as carbon materials and polymers, and their unique properties that lead to a rational design of heterogeneous nanocatalysts, especially for chemical reactions that are of high value in pharmaceuticals, pesticides, biological and fine chemicals industry. With the increasing demand of chiral products, a number of efficient asymmetric heterogeneous catalysts based on transition metal loaded support with chiral modifiers have been developed for a wide range of organic transformations. The major part of asymmetric catalysis is homogeneous catalysis because it facilitates molecular reactions in an efficient manner with high chirality transfer. Despite these merits, separation and purification of products, as well as recycling of the catalysts, make it less environmentally benign and more costly. The immobilization of asymmetric homogeneous catalysts on the support is a viable option to overcome such issues and to make them recyclable and economical. Out of various studies on symmetric heterogeneous catalysis, asymmetric hydrogenation of ?-ketoester is one of the key reactions with wide application in pharmaceutical industries. Metal nanoparticles loaded carbon composite systems are of great interest as they blend the exclusive properties of carbon materials with metal nanoparticles. In the current research work, carbon materials, loaded with highly platinum dispersed nanoparticles, were synthesized for hydrogenation of methyl pyruvate using a natural chiral modifier. Out of various carbon supported metals, the Pt/MWCNTs was found to be most efficient system and provides high enantioselectivity (ee > 99%) due to the high absorption of cinchona and substrate on atomically dispersed Pt nanoparticles that maximize metal utilization. One to one Substrate-modifier interaction was examined by NMR. During this study, the excellent activity of Pt (111) plane was observed due to higher packing density, stability and cohesive energy than other crystal planes, leading to significant chemisorptions of a variety of chemical entities. For that, a strategy was developed that involves preparation of Pt (111) from phase transfer reagent Tw20, followed by mixing of functionalized carbon materials to obtain heterogeneous Pt (111) hexagonal nanocrystal loaded carbon catalyst, by simple thermolytic reduction in air, which were tested for asymmetric hydrogenation of ?-ketoester at ambient reaction conditions, using cinchonine as modifier. Chiral polymers were also prepared and used as supports, because they are tuneable based on the monomer used and synthetically viable. In this study, it was found that the chirality could be transferred from the support to substrate with an ease in case of hydrogenation of carbonyl groups. In a distinct study, the F-CD-BF4/Pt/MWCNTs were screened for stereoselective allylation of imine and aldehydes.
Small Molecule Based Solution Processed Organic Field-Effect Transistors and Applications
(Indian Institute of Technology Jodhpur, 2017-02) Tiwari, Shree Prakash
Organic field-effect transistors (OFETs) have gained tremendous attention from researchers due to its suitability for applications in large area flexible electronics. Solution processing of organic semiconductors, which act as active layer in these devices, is preferred for its attractive advantages of low cost and simplicity. The quality of active layer and dielectric-semiconductor interface are some of the crucial factors which regulate the performance of OFETs. However, improvement in these aspects is quite challenging due to numerous intricate issues related with material properties and processing conditions. In this work, the organic semiconductor TIPS-pentacene is explored for demonstration of high performance OFETs in bottom gated top contact (BGTC) architecture, which has become the conspicuous choice for OFETs due to its inherent high mobility and air stability. Successively, two types of flexible OFETs have been fabricated which are used to demonstrate high electromechanical stability and sensing phenomenon depending on their suitability. Firstly, the effect of structural dissimilarity of the additive solvent from the main solvent on the properties of the resulting crystals of TIPS-pentacene and corresponding device performance on rigid Si/SiO2 substrates is comprehensively studied. With toluene as the main solvent, benzene, cyclohexane, and hexane were used as additives for making solutions of TIPS-pentacene. It was found that a higher structural dissimilarity of the additive in the binary solvent mixture promotes a better molecular aggregation and higher crystallinity in the active layer and improved electrical characteristics in the corresponding OFETs. OFETs fabricated from toluene/hexane solvent resulted in improved field-effect mobility higher than 0.1 cm2 V-1 s-1 compared to 0.05 cm2 V-1 s-1 for toluene solvent. Subsequently, blending of insulating polymer binder polystyrene (PS) with TIPS-pentacene was studied for phase separation and resulting high performance and electrically stability in OFETs. Drop casting of blend solution and solvent evaporation on Si/SiO2 rigid substrates resulted in a vertically phase separated, tri-layer semiconductor-polymer-semiconductor structure. Though the dielectric capacitance density decreased from 10.6 nF cm-2 (300 nm SiO2) to 3.1 nF cm-2 due to phase separated additional PS dielectric layer, the average process transconductance parameter (product of mobility and capacitance density) improved by a factor of ~4, with maximum mobility as high as 2.6 cm2 V-1 s-1 in saturation region for -30 V operation. These devices exhibited average mobility of 1.5 cm2 V-1 s-1, threshold voltage of 1.4 V, and high current on-off ratio of ~8×106 with better stability under bias stress compared to neat devices. For future flexible electronics, low voltage operated and high performance OFETs on flexible substrate are required, for which two device strategies were employed on PET substrates. First type of devices were fabricated with an active layer of neat TIPS-pentacene on HfO2-PVP hybrid gate dielectric, whereas the other type of devices were fabricated with TIPS-pentacene:PS blend films on HfO2. At an operating voltage of -10 V, neat TIPS-pentacene devices exhibited average and maximum mobility of 0.11 and 0.23 cm2 V-1 s-1, average threshold voltage of 0.1 V and current on-off ratio of ~105, whereas TIPS-pentacene:PS blend devices showed average and maximum mobility of 0.44 and 0.93 cm2 V-1 s-1, average threshold voltage of -0.3 V and on-off ratio of ~105. Blend devices outperformed neat devices due to a better quality of dielectric-semiconductor interface, which was developed because of vertical phase separation. Due to their better electrical performance, TIPS-pentacene:PS blend OFETs were further explored for demonstration of low voltage operation and high electro-mechanical stability. At further reduced operating voltage of -5 V, an average and maximum mobility of 0.5 and 1.1 cm2 V-1 s-1, average threshold voltage of -0.5 V, current on-off ratio of ~105, and low sub-threshold swing of 0.3 V/dec. were achieved. In addition, low drain current decay of 10% and a very small threshold voltage shift of 0.3 V were observed for 1 hr bias stress at VDS = VGS = -5 V, indicating to very high bias stress stability in these devices. For a bending radius of 5 mm, high stability in electrical characteristics was found with increasing duration of mechanical strain, where average mobility changed from 0.43 to 0.30 cm2 V-1 s-1 for a very long strain duration of 2 days. Upon application of 100 cycles of tensile and compressive strain, mobility of representative device changed from 0.32 to 0.29 cm2 V-1 s-1, indicating very high electromechanical stability in these devices. Further, flexible OFETs with active layer of neat TIPS-pentacene on HfO2-PVP hybrid gate dielectric were used to examine the photo-sensitivity of TIPS-pentacene to visible and UV lights because of relatively simplified device structure and purity of semiconductor layer. Photo-sensitive OFETs exhibited maximum response to blue light illumination with intensity of 1.7 mW/cm2, showing a current modulation as high as ~105 at low operating voltage of -5 V. Enhancement in the photo-response was observed with increasing time of visible illumination and gate bias during illumination. However, increasing UV irradiation time resulted in an enhanced positive threshold voltage shift and reduced mobility. The saturation drain current at biasing conditions of VGS = -10 V and VDS = -5 V was found to rise slightly for smaller values of irradiation time, however decreased for higher values of illumination time. A similar trend of positive shifting of VTH and mobility roll-off was observed when gate bias during UV irradiation was increased.
Processing of Heart Sound Signal to Monitor Cardiovascular Functions in Real-life Scenario
(Indian Institute of Technology Jodhpur, 2017-04) Tiwari, Anil Kumar
Solar Power Generation Forecasting using Neural Network Based Aproach.
(Indian Institute of Technology Jodhpur, 2017-05) Ravindra, Brahmajosyula; Vijay, Vivek
Forecasting of solar power generation is important in successful evacuation of the solar power into the existing electricity grid. The importance of solar photovoltaic (SPV) plant yield forecasting is crucial in the power scheduling, balancing, and grid control operations. These operations of electricity grid depend on the approaches used and followed to minimize the effect of solar power variability. This variability arises due to the atmospheric processes as well as system conditions.This thesis concentrates on the solar power generation forecasting of rooftop (small scale) and ground based (large-scale) solar photovoltaic plants. Various case studies in which 15 minute averaged data, daily averaged data and monthly averaged data from two plants in India are considered. Seasonal (summer, winter and rainy) categorization of the data is also studied. The generation of solar power plant depends on the variation in ambient conditions. Several empirical correlations and simple lumped dynamic models help in validation of the experimental data. This work proposes the use of an intelligent approach to forecast the power generation of solar photovoltaic plant. The main objective of this work is to explore the ability of neural network models to forecast the solar power generation. We propose models using Artificial Neural Network and Generalized Neural Network for solar power generation forecasting. Here, historical data of solar irradiation (Global Horizontal Irradiation, GHI), global tilted irradiation (Global radiation on an inclined plane, GTI), ambient temperature, module temperature, wind velocity, sun availability are the input parameters to the neural network in the modeling for forecasting. The neural network has adaptability and has been trained with values of input parameters and power generation of a PV plant.Forecasting models were developed for particular time horizon for various seasons. These models are tested and validated for various forecasting time intervals. It is observed from the obtained results that, compared to the artificial neural network, generalized neural network-based forecasting model is able to capture the nonlinearity effects of solar power generation. In addition, comparative study of forecasting results have shown that proposed generalized neural network-based forecasting model outperforms the artificial neural network model.
Technical Analysis for Short-Term Forecasting of Financial Data and Turn of the Year Effect
(Indian Institute of Technology Jodhpur, 2017-05) Vijay, Vivek
Stock market always attact investors to invest money according to their choice form which large profits can be earned. The fundamental drive behind maximizing this profit is strategy of buying and selling of stocks. Prediction of buying and selling patterns of stocks, or the whole market has always been a challenging task. It is due to the complexity,high volatility and non-inearity in the data. The rate of variation of financial time seres depends on several factors, such as fluctuations, interest rates and volume of transactions. Several statistical and machine learning techniques have been developed to forecast the movement of financial time series. Here we first discuss the trading band approach tob predict buy or sell patterns of a particular stock. These bands suggest buy or sell signals based on historical movements. Originally developed by J.H Hurst, these bands became more popular when a trading band was defined by using Moving Average (MA). The most popular trading band is the Bollinger Band, develoed by John Bollinger in 1980. These are volatility bands placed below and above the moving average of given financial time series. Al-though, the dynamic nature of these band makes them useful for different secrities with standard settings but due to the low decision time they arev unable to capture sudden peaks. We develop a new trading band ( Optimal Band ) which is based on absolute extrema (maxima and minima) and local extrema. We also develop an approach of predicting the buy / sell pattern using Hidden Markov Models. On the other hand, if trading bands and technical indicators exhibit similar partterns for two or more stocks, the decision is made on the basis of return and association with parttern. We first classify the historic data as per their pattern by using the Optimal Band. For each of the categories of pattern, we further divide the whole data into different categories of returns. If the interest lies in the interested in forecasting the returns then the historic value of pattern are used to predict the same but if one is interested in forecasting the returns then the historic value of pattern becomes more useful. Therefore, it becomes important to analyze the strength of dependence between the two variable, returns and patterns. We use historic data to see buying and selling pattern by using the Optimal Band. The pattern data is tham divided into there categories, namely, sell, neutral and buy. This is further used to estimate the future category of returns, high, moderate and low. The whole data is then presented in the form of a 2-dimensional contingency table by using the variables, returns and pattern. In techincal analysis, one of the fundamental drivers is volmue of transactios. We include volume as the third variable with its two categories, namely up and down. This division of volume is parimarily based on the range of historic returns. This creates a 3-dimensional contingency table. there are two possible sets of partial tables corresponding to the variable volume. We test different hypotheses for these tables. turn of the year effect, also known January effect, refers to a phenomenon of changing behaviour of stocks during some trading days of the January month. The presence of this effect is well investigated on high returns of the January month for small capital companies. We provide an evidence of the effect by using buying selling ratio and logistic regression. We predict the probability of next pattern from the given state of pattern ( buy, sell, neutral). The reslts are demonstrated for the data od Cipla Pharmaceutical Pvt. Ltd., Tata Motors and Maruti Suzuki.
Systems Modeling of Target and Chemical Profiles of Drugs to Predict Their Phenotypic Side Effects With Canonical Correlation Analysis
(Indian Institute of Technology Jodhpur, 2017-06) Bagler, Ganesh
Despite technological advances and improved understanding of biological systems, drug discovery remains an inefficient and arduous task, with the high attrition of candidate molecules. Side effects (adverse reactions) is one of the key factors contributing to the rejection of candidate molecules with therapeutic potential. Hence, accurate prediction of phenotypic side effects is an important problem in drug discovery. The action of drugs needs to be seen from the systems perspective knowing that cellular mechanisms form a web of interactions with intricate cross-talks among biomolecules. Availability of data capturing molecular interaction of drugs, and their phenotypic side effects have facilitated systems-level models aimed at prediction of potential side effects. Towards the goal of predicting side effects, objectives set in this thesis were driven by the idea of creating holistic models using empirical data, and devising mathematical as well as computational strategies. We integrated data from existing resources such as DrugBank and SIDER for systems-level investigations of side effects, and developed an integrative Generalized Canonical Correlation Analysis model which facilitates consolidation of various drugs features. We concluded that models implementing chemical profiles show more consistent accuracy than those based on target profiles. Further we constructed a graph theoretical model of biological space to account for associations among drug targets, and by comparing the performance of various network metrics inferred that simple network parameters are comparable to intricate parameters. Our studies performed for identification of minimal ‘known side effects’ set as a predictor for a class of adverse reactions suggest that, partial information of side effects profile could be used as a factor for arriving at the remaining side effects. Finally, towards the goal of obtaining drug features that contribute the most to side effects prediction, we developed a partial canonical correlation analysis model that facilitates enumeration of contribution from individual drug features. Our systems-level investigations offer insights into mechanisms of adverse drug reactions and provide data-driven methods for their prediction.
System Biological Investigation of Brain Networks
(Indian Institute of Technology Jodhpur, 2017-06) Bagler, Ganesh
Neuroscience has been driven by inquiry for principles of brain structure organization and its control mechanisms. Brain is a complex system comprising of large number of neurons that interact with each other giving rise to its functions. Hence, going beyond reductionist approaches, systems biological investigations using graph theoretical models of brain mechanisms is expected to provide better understanding of emergent properties of brain. With this view, in this thesis, we asked questions addressing brain structure organization, its control and network correlates of neuropathology. We modeled the neuronal connectivity of C. elegans as a network to characterise its graph theoretical properties. Using structural controllability analysis, we identified its ‘driver neurons’ and characterised them for their phenotypic and genotypic properties. The driver neurons were found to be primarily motor neurons located in the ventral nerve cord and contributing to biological reproduction of the animal. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a ‘distance constrained synaptic plasticity model’ that simultaneously explained small-world nature, saturation of feedforward neuronal motifs as well as number of driver neurons. Importantly, our model was able to accurately encode the identity of specific driver neurons matching with those observed empirically. By implementing a motif tuning algorithm, we observed that ‘number of driver neurons’ shows an asymmetric sigmoidal response, indicating robust control for saturation of feedforward motifs and a fragile behavior for their depletion. We further modeled the interplay of excitatory and inhibitory synapses for the study of structural balance in this neuronal system, to highlight the contribution of inhibitory synapses. Beyond investigating structural brain network in C. elegans, we constructed human functional brain network models to probe network correlates of schizophrenia. Thus, through systems biological investigations of brain networks, we have addressed questions related to brain structure organization, mechanisms of its control and network correlates of schizophrenia. Our studies highlight the importance of systems-level models of brain networks and provide insights into their structure, function and control.

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