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Development of Efficient MPPT Techniques for a Small-Scale Standalone PMSG based Wind Energy Conversion System with Energy Storage Integration
No full textIn recent years, the research and industrial communities mainly focused on renewable energy systems to combat environmental problems and also to meet the growing demand for electrical energy. Among various kinds of renewable energy sources, wind energy is gaining more support owing to its low area requirements, policy fostering, maturity of wind turbine system techniques, and zero carbon emissions during operation. Small-scale variable-speed wind energy conversion systems (VSWECS) are increasingly recognized as viable alternatives for remote areas and residential applications where large wind turbines are impractical. This system employs a permanent magnet synchronous generator (PMSG) as a variable-speed wind generator due to its advantages such as high torque density, gear-less operation, and lack of external excitation requirement. However, the small-scale PMSG-based VSWECS face challenges in extracting maximum power during varying wind speed and load conditions. Simultaneously achieving a constant output voltage along with improved reliability is also another key aspect to address. This research work aims to develop a 2 kW standalone small-scale PMSG-based VSWECS with battery backup to meet the power demand. The system comprises of four main components: a wind turbine emulator (WTE), a PMSG as a wind generator, power electronic converters, and battery storage. For a VSWECS, the wind turbine characteristic is emulated using a separately excited DC motor coupled to the wind generator. The output is interfaced to a two-stage power electronic converter, consisting of an AC-DC (3-phase uncontrolled rectifier) and a DC-DC (boost type) employed to harness maximum power extraction. Due to the stochastic and unpredictable nature of wind speed, extraction of maximum power from the VSWECS becomes an attractive control objective. This dissertation proposes novel adaptive step size (ASS) and drift-free ASS (DF–ASS) maximum power point tracking (MPPT) methods for the system. The control schemes achieve maximum power point (MPP) without using mechanical sensors like speed encoder and anemometer. The ASS and DF-ASS methods capture more power, reduce the steady-state power oscillation around MPP, and improve the tracking speed. Also, the proposed DF–ASS control scheme avoids the drift phenomenon during wind speed increase condition. The comparative experimental results of the proposed ASS and DF-ASS methods with respect to the fixed step size MPPT schemes show better dynamic and steady-state performance. However, the implementation of these speed sensorless MPPT algorithms (ASS and DF–ASS) needs two sensors (voltage and current) to determine the power that enhances the cost, and complexity with more power loss in the sensor circuit. Therefore to resolve the aforementioned limitations, the idea of a single sensor-based MPPT method is also analysed and proposed in this dissertation. This single load current sensor-based adaptive step size (LCAS) MPPT method utilizes only the load current information to track the maximum power. Extensive experimental work is carried out for the LCAS MPPT method that confirms better tracking efficiency, and faster tracking speed, along with the improved steady-state as well as transient performance. As VSWECS is operated at MPP for different wind speeds, the DC-link voltage varies accordingly. However, at the load end, it is necessary to maintain a constant voltage irrespective of environmental change. Therefore in this dissertation, a battery backup system is employed to manage load requirements by absorbing surplus wind power and supplying power during wind power shortages. The charging and discharging of the battery are regulated by a bidirectional DC-DC converter, which utilizes a dual-loop PI (proportional and integral) controller featuring both voltage mode control (VMC) and average current mode control (ACMC) loops. All the developed schemes are experimentally verified using an OPAL-RT real-time digital controller. The obtained results justify that the proposed scheme is capable of meeting the load requirements continuously despite the variations in wind speed and load, making the power generation unit self-sustainable and robust
Development of Novel Carbon Dot Hybrid Sensors for the Detection of Environmental Pollutants and Biomarkers
No full textNanocarbon materials can be potentially used in the growth of next-generation optical biosensors. Driven by its low-cost, simplicity, utility, high sensitivity and carbon-based optical biosensors have been widely researched as an alternative tool to aid scientists in identifying environmental pollutants and important biomolecules. In this context, the thesis entitled, “Development of novel carbon dot hybrid sensors for the detection of environmental pollutants and biomarkers” is an embodiment of investigations aimed at the design and development of metal doped carbon quantum dots sensors, sensing protocols, and exploring the practical applications of these sensors in the detection of the analytes in model plant or living organism for specific applications. The thesis has been divided into eight chapters. Chapter 1 presents a brief literature review on proper selection of molecular precursors, surface passivating agents, heteroatoms and metal precursors can produce carbon nanomaterials with biocompatibility, high QY and long-term stability which may offer a wide variety of applications. The underlying photophysical process responsible for the alteration of fluorescence response of the carbon dot in presence of the analyte has been discussed. The recent development of literature on the application of carbon dot in both environmental and biomarker sensing has been included. The goal of the thesis is defined at the end of the chapter 1. In chapter 2, Manganese dioxide-carbon dot (MnO2CD) composite nanoparticles of size 45 nm have been synthesized and utilized for the detection of arsenic, organoarsenic and organothioarsenic compounds such as dimethylarsenate (DMA), dimethyldithioarsinate (DMDTA), and dimethylmonothioarsinate (DMMTA). Chapter 3 and 4 describes the development of a betaine-modified carbon dot (BT@CD) and Ag- doped CD sensor for monitoring Cr(VI) and perchlorate respectively in water as well as real samples. Due to its easy translocation in the vascular bundles, these fluorescence nanosensors can be applied to detect Cr(VI) in rice plants (Oryza Sativa) through fluorescence confocal imaging. The treatment of rice plants with BT@JCDs in the concentration range of 0.2 to 1g/mL triggered photophysical parameters promoting plant growth. In chapter 5 and 6, we have constructed different surface passivated metal carbon dot integrated probes Ca@Cu-CD and AuNP@GCD for the detection of glycine and dopamine respectively. The exceptional combination of fluorescence and conducting properties establishes our probes as a dual sensor for the nonenzymatic detection of two neurotransmitter glycine and dopamine in real serum samples. Our effort to explore the use of carbon dot in developing wearable sensors has been presented in chapter 7. We have fabricated a mechanically stable, stretchable hydrogel patch by integrating Cu-CD in a PVA-Agar hydrogel. The hydrogel patch sensor can monitor Ca2+ level in sweat in both fluorescence and electrical mode. At the same time because of excellent skin adhesiveness and flexibility MCD@PAGH sensor can be attached to any joint to monitor strain induced by body motion in both electrical and fluorescence mode
Thermally Stable Cation-Pools in C-X (X = Halogen) and C-C Bond Formation
No full textThe cationic intermediates are valuable electrophiles with broad applications in organic synthesis. Various strategies have been established for cationic intermediate generation. However, the transient and unstable nature of cations in conventional reaction media necessitates their formation in the presence of nucleophiles. Further, the nucleophiles that are unstable or inert to the reaction media cannot be used for trapping the cationic species. Yoshida and co-workers established the "Cation Pool" method to address the limitations of the conventional methods. The "Cation pool" strategy facilitates the generation and accumulation of carbocations and onium ions in an appropriate solvent through an electrochemical redox process at lower temperatures. However, the accumulation of halogen and chalcogen cations in the solution as "cation pools" found to be challenging due to their instability. Besides, the electrochemical oxidation method employed for the generation of cation intermediates and their accumulation as cation pools at very low temperature is a sophisticated process and is expensive for large scale production. So development of new methods for the preparation and stabilization of cationic species is demanding. The current thesis entitled “Thermally Stable Cation-Pools in C-X (X = Halogen) and C-C Bond Formation” mainly describes the development of a new protocol for the generation and accumulation of halonium ions and methyl(methylene)sulfonium ion cation pools, and their further application in organic synthesis, particularly, in carbon-halogen and carbon-carbon bond formation reactions. The current thesis contains 7 chapters which are summarised as follows: Chapter 1: A brief review on generation of cation pools and their synthetic applications This chapter briefly describes different methods for the generation and accumulation of cationic intermediates involving carbocations and heteroatom cations as a cation pool in the appropriate solvent. Additionally, various applications of the cation pool method are also described in this chapter. In addition, a critical overview and objective of the present work are also presented. Chapter 2: Generation of dimethyl sulfoxide coordinated thermally stable halogen cation pools for C-H halogenation In this chapter, we discussed our effort in generating halogen cation pools from the reaction of 1,2-dihaloethanes (hal= Br, I) and dimethyl sulfoxide (DMSO) to facilitate C-H halogenation of both arenes and heteroarenes. The initial reaction between DMSO and 1,2- dihaloethane produces the sulfur ylide, which undergoes pyrolytic elimination of ethylene, resulting in halonium ions. These ions are accumulated and stabilized by DMSO through coordination, leading to halogen cation pools for subsequent halogenation reactions. This protocol demonstrates selective electrophilic monohalogenation of arenes at room temperature. However, when the reaction temperature was increased, polyhalogenated products are formed. The late-stage halogenation of heteroarenes and certain commonly marketed drugs further signifies the synthetic utility of this protocol in pharmaceutical chemistry. Chapter 3. Synthesis of oxazoles from enamides using thermally generated bromonium cation-pool This chapter describes the utilization of thermally generated bromine cation pool from the reaction of 1,2-dibromoethane and DMSO in the synthesis of substituted oxazoles from enamides. The reaction proceeds through initial bromination of enamides followed by tandem annulation to afford substituted oxazoles. Chapter 4. Benzannulation and N-annulation of β-ketoenamines for synthesizing aniline and pyridine derivatives using DMSO as a methine source This chapter describes the benzannulation and N-annulation of β-ketoenamines by the in-situ generated methyl(methylene)sulfonium ion from the reaction of dimethyl sulfoxide (DMSO) and 1,2-dibromoethane (DBE). The β ketoenamines underwent N-annulation to pyridine derivatives, while the N-alkylated enamines were benzannulated to afford substituted anilines. Based on the control experiments a reasonable mechanism was depicted for the said transformations. Chapter 5. Synthesis of bis-1,3-dicarbonyl compounds using DMSO as methylene source This chapter deals with the application of the in situ generated methyl(methylene)- sulfonium cation pool from the reaction of DMSO and DBE for the synthesis of methylenexv bridged bis-1,3-dicarbonyl compounds from the 1,3-dicarbonyl compounds. A plausible mechanism for the above transformation was also presented. Chapter 6: DMSO-DCE triggered chemodivergent C-methylenation of electron rich arenes: An easy access to diarylmethanes In this chapter, we exploited the chemodivergent property of dimethyl sulfoxide (DMSO) in combination with 1,2-dichloroethane (DCE) to incorporate a methylene group. The methyl(methylene)sulfonium ion pool is generated by heating commonly used solvents like DMSO and DCE. Subsequently, this cation pool is trapped by electron-rich arenes and heteroarenes through a dearomatization/rearomatization process, resulting in the formation of both symmetrical and unsymmetrical diarylmethanes. This protocol is further extended to produce N-methylenamides by reacting 2-naphthol with amides or nitriles in the presence of DMSO and DCE. Chapter 7: Conclusion and future scope In the last chapter, the overall summary and future scopes of the present work have been described
Robust and Efficient Strategies for Invader Drone Surveillance System Based on UAV Borne Radar Antenna Array
No full textThe Invader Drone Surveillance System (IDSS) is a modern framework that enhances security and monitoring capabilities. It uses radar-equipped Unmanned Aerial Vehicles (UAVs)/drones to offer situational awareness in real-time for intelligence gathering. UAVs swift and agile nature allows for comprehensive coverage of expansive areas and remote locations. Real-time data processing and analysis enable quick decision-making and a proactive approach to security issues. The system uses various algorithms for effective categorization, localization, and tracking of prospective invaders or threats. The IDSS is a flexible and efficient system for protecting vital infrastructure, boosting border security, and assisting military and law enforcement activities. The dynamic nature of the IDSS makes it difficult to adjust with changing environments and scenarios, such as unpredictable weather patterns, varying terrains, and evolving threat landscapes. The research proposes the following techniques for a better solution by looking at these issues. •Due to the adaptability and agility, UAVs are increasingly used for surveillance. The success of surveillance activities, however, depends on the UAV’s ability to coordinate effectively with one another. In this regard, a bio-inspired technique is proposed to maintain the connectivity and coordination among a swarm of UAVs in the surveillance system. To improve the effectiveness and robustness of the UAV surveillance system, the proposed methodologies use the concepts of swarm intelligence, self-organization, and adaptive behaviours. •In order to determine the presence of an invader drone, it is essential to recognize and keep an eye on a variety of flying objects, such as drones, birds, and helicopters. In this regard, the Convolutional Neural Network-Memetic Algorithm (CNN-MA) technique is proposed. The proposed algorithm categorizes and analyses the flying object based on the Micro-Doppler Signature (MDS) data obtained by UAV-mounted radar at different angles. Experiment results show how well the CNN-MA based classification strategy performs in reliably identifying and classifying various flying objects, offering useful information for improving UAV surveillance systems.• After identifying UAVs from other flying objects, the distinction between the surveillance and invader UAVs is crucial. In this work, the bandstop filter filters out the surveillance UAV data from the invader. Further localization of invader UAVs is done in a surveillance system utilizing an adaptable (reconfigurable) radar antenna array (ARAA). Effective surveillance, monitoring, and situational awareness depend on accurate and trustworthy UAV localization. The proposed method uses reconfigurable radar technology to improve the invader UAV localization, ranging, and detecting accuracy—even in challenging circumstances. The reconfigurable radar-based localization method achieves excellent precision and robustness, paving the way for improved UAV surveillance system performance in various real-world circumstances. •Towards the continuous monitoring of the invader UAV, tracking is very important. For this, the Hybrid Unscented Kalman-Continuous Ant Colony Filter (HUK-CACF) is used to investigate the tracking of invader UAVs. The proposed method applies the HUK-CACF algorithm to estimate the UAV’s position, velocity, and other state variables. The HUK-CACF is highly suited for UAV tracking because of its capability to handle nonlinear dynamics. •Finally, the last work focuses on implementing cryptographic methods to secure data transfer in a UAV surveillance system. Sensitive data transfer in UAV surveillance activities, such as patrolling UAV locations, sensor readings, control orders, etc., requires strong security against unauthorized access and alteration. The efficiency and performance of the cryptographic techniques are assessed through simulations, revealing their capacity to protect data integrity, secrecy, and authenticity in UAV surveillance systems. The results of this research will aid in creating reliable and secure data transfer methods that improve the security and privacy of UAV surveillance operations
Stochastic Geometry Analysis of Energy Harvesting, Edge Computing, and Device-to-Device Communication in Heterogeneous Wireless Networks
No full textTHE future of wireless networks will evolve through inter-layer innovations to support new-age applications and use cases such as augmented reality, internet-of-everything (IoE), automated unmanned vehicular systems, remote surgery, and many more. Major requirements are enhanced data rate, higher system capacity, ultra-low end-to-end latency, and improved energy efficiency. The co-existence of large-scale machine-type devices with human-centric and content-centric communication will demand a more complex scalable heterogeneous wireless network environment. Wireless networks can be self-sustaining by harvesting energy from ambient radio-frequency (RF) signals. With ever-increasing data demand, caching popular content in the memory of user devices is seen as a promising alternative to offload demand from macro base stations (BS) and reduce backhaul loads. Considering these necessities, the integration of energy harvesting (EH), edge computing, and device-to-device (D2D) communication can be a promising technology for next-generation heterogeneous wireless networks. Further, stochastic geometry-based mathematical modeling has given a major paradigm shift in the design and performance analysis of such networks. In order to evaluate the performance of heterogeneous wireless networks analytically, stochastic geometry’s primary goal is to endow probability distributions on the positions of network nodes. This dissertation proposes stochastic geometry-based approaches and new frameworks for modeling, optimization, and performance analysis of energy harvesting and cache-enabled cognitive D2D communication. The first contribution of this dissertation is the development of a new stochastic geometry-based comprehensive framework for EH-enabled adaptive mode selection policy for cognitive D2D communication underlying cellular networks. In the proposed peer discovery policy, the status of the energy queue of all potential D2D users is proposed to be shared among themselves before communication starts. The spectrum optimization problem for efficient network functioning is formulated and a solution to choose the optimum spectrum access factor is provided as the second contribution of this dissertation. Also, a channel inversion power control policy and a distance-based correlation-aware mode selection policy are proposed for the optimum utilization of resources. The expressions for the temporal correlation of link outages are provided. Incorporating this in the medium access control (MAC) protocol will reduce the number of retransmissions and improves energy and spectrum efficiency. The impact of different traffic patterns on network throughput is also analyzed. The third direction of this dissertation is the integration of edge computing in terms of caching and energy harvesting capabilities into D2D communication to propose an effective and energy-efficient content distribution network (CDN). Here the Markov chain model is used to analyze the transmission probability of a typical D2D user operating in EH mode. The fourth and final direction of this dissertation is the incorporation of an independent marked Poisson point process (imPPP) to probabilistically model the aggregate interference and signal-to-interference-plus-noise ratio (SINR) distribution of the randomly distributed nodes in the spatial domain. The efficacy of the proposed unified analytical framework is evaluated in terms of the overall network coverage probability improvement due to the minimization of congestion in the base station-oriented core network. All the developed D2D framework, simulation results, and the outlined remarks are utilized to provide significant design insights and specifications for the deployment strategies of EH and cache-enabled cognitive D2D communication in heterogeneous wireless networks
Study on the Effects of Direct and Hybrid Laser Processing in Fabrication of Surface Features on Different Fe-Cr-Ni Enriched Alloys
No full textA Fe-Cr-Ni enriched alloy holds the beneficial properties that have high strength, excellent corrosion resistance, and good mechanical properties. The exact composition can vary widely, allowing these alloys to be tailored for specific applications. Just like that, the most pronounced Fe-Cr-Ni enriched alloys are A4SS and SDSS-2507. Both A4SS and SDSS-2507 are widely used in harsh environments for their unique individual characteristics. However, being a dual-phase material SDSS-2507 is a combination of desirable properties of individual phases. That makes it difficult to process by any means due to its lower machinability index. However, a new era Yb:YAG fiber laser technology has the remarkable ability to spur innovation and expand the limits of what can be achieved in processing these materials. That is why fiber laser has become widely recognized as an excellent option in advanced manufacturing due to its exceptional processing capabilities. Since direct laser processing (DLP) is a temperature-dependent process, it causes surface heating with melting, exhibiting a reciprocal relationship between productivity and processing quality. Nevertheless, it causes several surface imperfections and oxidation. If it falls short of finding a viable remedy, it inevitably leads to material property depreciation. Therefore, the applied thermal cycle needs to be controlled to minimize the oxidation behavior of the materials. In order to overcome such problems hybrid laser processing (HLP) holds its dominance considerably in the field of innovation which brings new standards to the products concomitantly with higher productivity. Apart from this, while processing with a laser by any means, scan mode is a crucial processing window through which the major laser energy controllers can be directed, especially for the fabrication of simple to intricate surface features on a wide range of materials. Based on such major points, the current research objectives are framed in three different stages. At the primary stage, an experimental investigation was carried out on the existing area fill scan mode (AFSM) and unique scan mode like orbit-in-orbit laser beam positioning strategy (O-OLPS) with the other laser processing variables during the fiber laser micromachining approach (FLMMA). In order to provide insight into contemporary scan modes, the current research also scrutinized the channel’s dimensional and surface traits alongside surface morphology, elemental composition, phase quantification, micro - hardness, crystallite size, and lattice strain. The current research outcomes revealed that the O-OLPS strengthens the grain boundary in the present micro-machining process by reducing crystallite size. The comparative study revealed that the O-OLPS offers around 28% reduced taperness with a controlled deeper and less widening channel profile, which might be a possible way to enhance micro-channel effectiveness for marine applications. In the second stage, an effective scan mode i.e., O-OLPS is adopted in this study for producing micro-channels on A4SS and SDSS-2507 for marine applications. As FLMMA is one of the most demanding manufacturing processes, this research aims to enhance the FLMMA by introducing O-OLPS in DLP and HLP as an existing industrial potential by altering the laser processing variables via tailoring the scan factors of the fiber laser. The core goal of this research is to scrutinize the materials’ responsiveness like dimensionality, material ablation, and surface traits. By tweaking the laser processing variables like energy and scan factors along with the environmental factors, the O-OLPS was examined under DLP and HLP. Apart from these, both the materials’ comparative performance was studied through phase quantifications, elemental analysis, surface morphology, corrosion study, and possible identification of corrosion products by utilizing Raman spectroscopy. It has been observed that the formation of defects and oxides is higher in A4SS compared to SDSS - 2507. Moreover, SDSS-2507 provides superior surface performance with higher corrosion resistance before and after laser processing compared to A4SS. However, from the material ablation perspective, A4SS holds a higher material removal ability compared to SDSS - 2507. From the Raman and corrosion studies, it can be concluded that A4SS is more susceptible to forming iron oxyhydroxides compared to SDSS-2507. The superior corrosion resistance of SDSS-2507, particularly in chloride environments, is less likely to undergo localized corrosion processes, which led to the formation of iron oxyhydroxides. Lastly, the SDSS-2507 surface outperformed the A4SS surfaces when processed under DLP and HLP and proved its efficacy in the application of a harsh environment. At last, the purpose of conducting the second stage fulfills its intention by selecting the most suitable material for marine applications. In the final stage, the versatility of O-OLPS was scrutinized under varied environments like DLP, active and inactive gas supported laser processing (A and IA-GSLP), and chemical- supported laser processing (CSLP) during the fabrication of a multi-pattern integrated surface (MPIS) feature, an intricate profile on SDSS-2507. This research also sheds light on the comparative mechanism that how the dynamic interaction occurs during the fabrication of MPIS under DLP, GSLP, and CSLP. Artificial chemical environments namely H3PO4, NaCl, and NaNO3, and their concentration, different gases like active and inactive, and their pressure levels along with controllable laser processing windows like energy and scan factors, were used to perform GSLP and CSLP to study SDSS-2507’s material ablation and surface characteristics. As SDSS-2507 holds a dual phase with varied thermal characteristics, this research further examined each phase’s sensitivity to laser-induced chemical reactions and attacks from aggressive and non-aggressive ions during CSLP. In order to acquire insight into the DLP, GSLP, and CSLP effects on SDSS-2507, phase analysis, surface morphology, surface chemistry, crystallite size, residual stress, mechanical property, and lattice strain were also studied. After DLP, GSLP, and CSLP, the SDSS - 2507’s resistance against aggressive Cl− ions was also scrutinized through electrochemical corrosion analysis and the oxide products were analyzed by Raman study. It has been found that by taking advantage of O-OLPS, surfaces processed under NaCl-CSLP and A-GSLP exhibited superior performance in terms of material ablation rate among the other environments, whereas the IA-GSLP solely performed well in terms of a clean surface with minimal leftover residue after H3PO4 compared to all. In comparison to NaNO3-CSLP and NaCl-CSLP, a decrease in crystallite size of up to 22.49%, and 19.12% was also seen respectively in H3PO4-CSLP. Similarly, compared to DLP and A-GSLP a decrease in crystallite size of up to 6.52%, and 5.08% was seen in IA-GSLP. Moreover, in comparison to before laser processing these values are 26.23% and 24.22% lower in H3PO4-CSLP and IA-GSLP respectively. Similarly, when compared to before laser processing, the corrosion rate was found to be 20.75%, 35.84%, 23.25%, and 28.30% lower in case of NaNO3-CSLP, H3PO4-CSLP, A-GSLP, and IA-GSLP respectively. While, there was a reduction in corrosion resistance observed in case of NaCl-CSLP and DLP. The above findings suggest that the MPIS fabricated under H3PO4-CSLP performed well in all aspects and can readily be applicable in harsh environment. Based on the facts presented above, it can be concluded that the MPIS that was fabricated using H3PO4-CSLP outperformed the others in every respect, and it can possibly maintain its integrity and functionality in any harsh environment especially marine without significant degradation
Synthesis of Graphene Derivatives and The Designing of Hybrid Filter For Water Purification
No full textRecognizing the significance of graphene and its derivatives, the overarching goal is to develop advanced composites based on graphene derivatives that have improved properties for treating wastewater containing a variety of organic, inorganic, and /or pathogenic pollutants using various techniques. We have successfully synthesized graphene derivatives, including GO and rGO, from various organic sources like graphite, coal, and rice husk (G-GO, G-rGO, C-GO, C- rGO, RH-GO, RH-rGO). Our primary objective was to assess the effectiveness and quality of these synthesized materials for wastewater treatment. Subsequently, we employed the most efficient graphene derivatives (G-GO, G-rGO) in combination with a polyurethane (PU) polymer substrate to create a cost-effective material called GOPU. We further enhanced the performance of this graphene polyurethane composite by adjusting the size of the polyurethane substrate into micro-sized GOPU granules and by substituting GO or rGO with a highly efficient novel GO-Fe3O4-PEI composite for adsorptive removal of various organic, inorganic, and pathogenic pollutants. Additionally, wastewater treatment was performed using a ternary photocatalyst, TiO2@Gd2O3@g-C3N4, to promote photocatalytic destruction of a broad spectrum of organic, inorganic, and pathogenic pollutants. Further, to enhance the catalyst's efficiency and make it functional even without light, we introduced carbon nanotubes (CNT). We developed an innovative day-night photocatalyst through a hydrothermal method called g- C3N4@Gd2O3@CNT, which exhibited a post-illumination catalytic effect. Furthermore, we designed a unique photoreactor called a Flatplate photoreactor, featuring a flat glass reactor panel loaded with a polymeric day-night photocatalyst, g-C3N4@Gd2O3@CNT@PU. This photoreactor was employed for efficient wastewater treatment. This current study explores an innovative approach and route for wastewater treatment by leveraging newly developed composites based on graphene derivatives. It offers valuable insights into the effectiveness of multifunctional graphene derivative-based day-night catalysts in wastewater treatment and their versatile application in other fields
Algorithms for Droplet Routing in Digital Microfluidic biochip: Managing deadlock, Route Storage and Contamination
No full textDigital microfluidics Biochip (DMFB) is a miniature hand-held device capable of automating biochemical assays. It is used extensively in genetic research and medical diagnostics. Droplet routing in biochemical synthesis using DMFB is very challenging. It needs a physical movement of various droplets to implement a specified operation in the synthesis. Droplet routing aims to move droplets from a source cell to a destination cell and maintain fluidic constraints all the time. The tasks include handling issues like deadlock contamination and minimizing execution time and number of cells used. The total execution time (latest arrival time) is mainly impacted by deadlock. Detection of the deadlock early can enable preemptive action to be taken to minimize the LAT. To achieve this, the bound boxes of the droplets are checked for overlapping. Various deadlock scenarios are analyzed, and four deadlock conditions are defined. The simulation result also shows a reduction in LAT. A bidirectional route exploration mechanism is proposed to reduce the route exploration time. The proposed method treats the DMFB as a rectilinear grid. The route exploration is performed by using two waveforms- source and destination wave. The source wave originates from the source cell and moves towards the destination cell. The destination wave begins at the destination cell and moves towards the source cell. Every cell visited by any cell is marked with an alphanumeric value. Both the cells intersect at pivot cells markedby both waveforms. These pivot cells act as boundary cells and convert the DMFB to a bipartite graph. Each pivot cell is assigned a pivot value by summing the numeric values of the marking. The pivot cell with minimum value is given as the pivot value of the droplet. The droplets are then sorted in ascending order to generate the droplet order. The routes of each droplet are validated by selecting a pivot cell using four user-defined heuristics. Two ants are generated from each pivot cell and sent to the source and destination. When these ants reach their destination, the route they follow is extracted from their header. The routes of all the droplets are then compacted to get the final parallel moving sequence. The simulation result shows an improvement in the latest arrival time. A flooding-based droplet routing mechanism is proposed for biochemical synthesis. In the route exploration phase, flood the whole biochip with scout packets. A duplicate copy of the scout packet is forwarded to each of the neighbors of the current cell. The scout packets are discarded if it has the same origin cell, or the current cell is already in its header. When a scout packet reaches its destination cell, the route is extracted from its header and added to the route list. Each route is validated by a Hello packet. The hello packet is sent from the destination cell to the source cell along the route in the reverse direction. When the hello packet reaches the source cell, the route is added to the validated route list. The routes are then sorted in ascending order by route length. The droplet with the least route length is assigned the highest priority. The route compaction is performed based on the droplet order. An improvement of 12.25% and 20.5% in LAT is observed for free and virtual topology. A 3-tuple representation method for droplet routes to minimize memory/space requirement is proposed. The proposed method assumes the route of a droplet is a set of smaller sub-routes. In the route exploration phase, a rectangle is created by intercepting two L-lines drawn in opposite directions. A rectangle is drawn for every droplet. This converts the droplet routing into a rectangle overlapping problem. Two edges from every rectangle need to be removed, transforming into an edge optimization problem. The space/memory requirement is minimized by using a 3-tuple representation method: . S, M, and E are the addresses of the source, middle, and end cells. The performance of the proposed method is compared against three well-known droplet routing protocols. The latest arrival time shows an improvement of 13.83% and 21.31% in free and virtual topology, respectively. Similarly, a 32.47% reduction in memory requirement is also noted. A proactive wash droplet routing algorithm is proposed for contamination problems in biochemical synthesis using DMFB. Fluid droplets of heavier molecules, such as protein, leave some residue while traversing their route. This residue acts as a contamination source for any other fluid droplet visiting these cells in a later time cycle. It results to an unwanted mixing, leading to a contamination problem. Wash droplets are introduced to clean this residue before the arrival of any other fluid droplets. The proposed method proactively cleans all the contamination cells/spots by appending a wash droplet behind every fluid droplet. The fluid and wash droplets are moved using a stop-and-wait manner. The wash capacity is taken into consideration. The capacity is reduced by 1 for every contamination cell it visits. A wash droplet becomes dirty as its capacity is reduced to 0. The droplets start moving along their route, and a wash droplet follows it by maintaining a gap of at least one cell. When the wash droplet becomes dirty, it is moved to the nearest waste reservoir, and a new wash droplet is replaced. The performance of the proposed method is mapped against three popular protocols. The simulation result shows total cleaning is achieved, and an improvement of 3.122% is recorded for the latest arrival time
Efficient Ground Area Coverage using UAV Network
No full textUnmanned aerial vehicles (UAVs) have gained popularity recently. The flight control unit (FCU), onboard CPU, camera, and other sensors automate UAVs. They collectively form an ad hoc network called flying ad hoc networks (FANETs). Compared to other terrestrial ad hoc networks, FANET has some unique features that attract users more these days. Regarding applications, other forms of ad hoc networks have specific restrictions. They can only be used on the surface of the ground or water. The best part is that FANET can be used in a regular environment in hazardous locations. FANET is now integrated with terrestrial networks for reliable wireless communication. UAV’s agility, processing power, data collecting, and transmission improve network infrastructure. It’s useful for environmental and traffic monitoring, rescue operations, smart farming, and more. All the uses mentioned above go under the coverage applications, in which UAVs need to cover or scan a target ground region to complete a mission successfully. Finding a suitable collection of waypoints for the movement, a collision-free path to cover all the waypoints, establishing a stable route for data transmission, and an automated fault diagnosis approach to isolate faulty UAVs and erroneous data for a successful coverage operation are the objectives of the thesis. Simulation is performed to evaluate the proposed work using Network Simulator-3 (NS-3) and Python environment. An optimized aerial decomposition approach is proposed for determining a suitable set of waypoints for the movement of UAVs. The decomposition process is carried out by integrating the footprints created by a UAV. This work considers two distinct forms of UAV footprints: the camera footprint, which pertains to visual coverage, and the antenna footprint, which pertains to sensing coverage. The midpoint of each footprint is regarded as a waypoint for the trajectory of a UAV. An objective function is introduced to optimize the decomposition process by maximizing and minimizing the inside and outside ground area coverage, respectively. The proposed work is evaluated regarding the percentage of inside and outside area coverage using the generated set of waypoints. It improves the inside area coverage to 6.8% and reduces the outside area coverage to 67.59% approximately. A path planning approach is proposed to find a collision-free path. It aims to cover all the waypoints generated before. The proposed approach involves representing the collection of waypoints as a graph, whereby a UAV determines its subsequent intermediate waypoint by considering the environmental conditions at its present waypoint. Geometrical methods, such as the collision cone approach and triangle laws are used to determine the occurrence of collision with static and dynamic obstacles. The path planning algorithm’s performance in a collision-free environment is evaluated using the traveling salesperson algorithm (TSP) Next, the process of path planning involving collision detection and avoidance is conducted and compared to the FGM-I approach. Path length, execution time, and the total number of collisions required to be avoided are the parameters of the evaluation process. The proposed algorithm reduces the path length to 8.17% and the total number of collision avoidance to 40.3% approximately. Routing mechanisms of non-cluster-based and cluster-based approaches are proposed to find a stable and energy-enabled route to the ground control station (GCS). The non-cluster-based routing incorporates three key parameters in the route discovery process: the velocity threshold, energy threshold, and expected link stability time between two UAVs. However, in the case of the proposed cluster-based routing, the cluster head election process considers five parameters, including connectivity degree, link stability time, surplus energy, connectivity with backbone UAV, and speed differential. The clustering process is managed using an approach of reinforcement learning (RL) mechanism called State-Action-Reward-State-Action (SARSA). The routing mechanism is implemented through the inter and intra-cluster forwarding method. The performance evaluation of both methods encompassed the assessment of various parameters such as packet delivery ratio (PDR), delay, routing overhead, network lifetime, number of redundant clusters, and topology construction time. The non-cluster-based and clustering-based routing schemes reduce their routing overhead to approximately 11.6% and 13.7%. An automated fault diagnosis method is proposed to identify the different kinds of faults. In this work, UAVs cover a ground region filled with sensor devices and collect sensor data during the coverage mission. This work identifies two types of data faults: sensor faults and UAV data faults, and the classification of the faulty data is performed at the GCS. The fault detection process is performed in three stages: the sensor fault detection and elimination using a modified Z-score statistical test, the UAV data fault identification using a multivariate analysis of variance (MANOVA) test, and the classification of erroneous data using a centroid-based probabilistic neural network (PNN) at the GCS. The evaluation is performed using fault detection accuracy (FDA), false alarm rate (FAR), false positive rate (FPR), and false classification rate (FCR). The proposed PNN detects an accuracy of 95.3%, 92%, and 91% for permanent, intermittent, and transient UAV data faults, respectively
Study of Localization Transition in Non-Hermitian Quasi Periodic System
No full textDisorder-driven delocalization-localization (DL) transition and its impact on the energy spectrum have been extensively studied in diverse physical systems. In Hermitian systems with random disorder, this transition is famously known as the Anderson localization (AL) transition. It is well established that only with the random disorder the AL transition takes place in a three-dimensional (3D) lattice system. However, with quasiperiodic (QP) potential, DL transition can take place even in one-dimensional (1D) lattice systems. Interestingly, in recent years it emerged that such DL transitions can also take place in the non-Hermitian systems, with a much more fascinating set of associated phenomena, compared to their Hermitian counterpart. The non-Hermitian systems can broadly be classified into two classes; one class without PT symmetry and the other class with PT symmetry. The absence or presence of such symmetry drastically alters the nature of the eigenspectrum across the DL transition. In this thesis, we investigate the DL transition and its associated changes in the energy spectrum in the context of non-Hermitian lattice systems with QP potential. In the first part of our study, we have proposed a generalized non-PT symmetric 1D non-Hermitian QP lattice. Well-studied non-Hermitian models, namely the Aubry-André-Harper (AAH) model and the Hatano-Nelson (HN) model with QP potential can be obtained from our proposed Hamiltonian as limiting cases. In our generalized Hamiltonian, the non-Hermitian behavior arises due to asymmetry in the hoppings and the complex nature of the QP potentials. We demonstrate that the interplay between these two leads to more diverse and intricate phases. For identical modulation of the real and the complex parts of the QP potential, we obtain the analytical expression of the critical point that precisely captures the DL transition for systems with periodic boundary conditions (PBC). Our numerical investigations reveal that the critical point remains unchanged even with open boundary conditions (OBC). One particularly fascinating aspect of our findings is the emergence of a mixed phase between the delocalized and localized regions in systems with non-identical modulation of the real and complex parts of the QP potential. This mixed phase presents a remarkable coexistence of skin modes and localized states for systems with OBC, while systems with PBC exhibit a coexistence of delocalized and localized states within the mixed phase. To provide further insights into the underlying physics, we construct comprehensive phase diagrams, shedding light on the crucial role of various parameters in a broad range of non-Hermitian QP lattices. In the second part of our investigation, we turn our attention to the PT symmetry class of non-Hermitian systems. In particular, we have focussed on one such system, namely the well-known non-Hermitian AAH model, that can be obtained from our preceding generalized Hamiltonian as a limiting case. The nature of the DL transition is extensively studied in this system. Recently, in the contemporary realm of spintronic device development, spin-orbit interaction has garnered considerable attention from researchers due to its potential impact on electronic systems. This has led to the exploration of the influence of Rashba spin-orbit (RSO) on DL transition in the Hermitian AAH model. However, a similar investigation in the context of non-Hermitian lattice systems has not been taken up so far. Motivated by this, we investigate the impact of RSO coupling on the DL transition and the energy spectrum in the non-Hermitian AAH model. Incorporation of RSO coupling into the PT symmetric AAH model does not alter its symmetry. Employing computational techniques and analytical methods, we scrutinize the alterations induced by RSO coupling on the DL transition. We observed consistent quantitative changes in the DL transition point for both PBC and OBC cases. However, in PBC, the breaking of PT symmetry aligns with the DL transition point, while in the OBC case, the symmetry remains broken regardless. There is a crucial difference between the DL transition in the Anderson model and the systems addressed in the previous sections. The DL transition in the Anderson model is associated with the existence of a mobility edge, while is absent in both the systems addressed in the previous chapters. However, some studies have revealed that the introduction of short-range hopping gives rise to a mobility edge in the 1D non Hermitian PT symmetric AAH Hamiltonian. In the third and final phase of our investigation, we address the fate of the mobility edge and PT symmetry in such systems with RSO coupling. Interestingly, our results show that the presence of RSO can significantly modify the mobility edge identically in both PBC and OBC systems; in certain cases to the extent of almost completely suppressing it. However, in systems with PBC, the breaking of PT symmetry matches the point where the mobility edge occurs. On the other hand, in systems with OBC, the symmetry remains broken regardless, which is similar to what we observed in the non-Hermitian AAH model we examined earlier with RSO coupling. In summary, this thesis provides a comprehensive exploration of the DL transition and its implications for the energy spectrum in non-Hermitian 1D QP systems with and without PT symmetry. Our findings offer valuable insights into the fundamental aspects of DL transitions which could potentially benefit various fields, ranging from condensed matter physics to quantum information science