7940 research outputs found
Sort by
Effect of Silicon and Y2O3 on Densification, Mechanical Properties and Isothermal Oxidation Behaviour of W-10Ni-3Co alloys Fabricated by Powder Metallurgy
No full textTungsten heavy alloys are highly sought after for industrial and military applications due to their exceptional density, strength, and stiffness. They find utility as kinetic energy penetrators, counterweights, and radiation shields. To enhance densification through liquid phase sintering and reduce the sintering temperature, nickel (Ni) and cobalt (Co) are commonly incorporated into tungsten-heavy alloys. Additionally, mechanical alloying can introduce nano Y2O3 particles into the alloy matrix. This results in a uniformly dispersed fine oxide strengthening (ODS) and an extremely refined grain structure, ultimately leading to increased strength at high temperatures and inhibiting recrystallization. The main objective behind the development of ODS tungsten alloys is to raise the maximum operating temperature. Nonetheless, the susceptibility of tungsten to oxidation at elevated temperatures poses a significant challenge. One potential solution to this critical safety concern involves incorporating oxide-forming alloying elements such as silicon (Si), chromium (Cr), and aluminum (Al), which promote the growth of a stable and protective oxide scale. This oxide scale effectively hinders oxidation at high temperatures. In the present study, we have introduced 1, 5, 10, 15, and 20 wt.% of Si into W, WNi, and WNiCo alloys through planetary milling and conventional sintering in hydrogen gas atmosphere at 1500 ⁰C for 2 hours. The alloy phase evolution and microstructure development have been characterized using XRD, SEM, and TEM, and the hardness and compression strength of the alloys are examined using UTM. The addition of Si into tungsten results in the formation of WSi2 and W5Si3 compounds after sintering. The percentage of these silicides increases with more Si addition. Due to the presence of these brittle compounds, the hardness of the material increases, and the compression strength decreases at higher Si percentages. The addition of Ni/Co, along with Si lowers the formation of intermetallics, and the compression strength of the tungsten has been retained in alloys up to 5 wt.% of Si. However, in the case of high wt.% of Si alloys, even in the presence of Ni/Co due to the more pronounced effect of intermetallics, the alloys become more brittle and subjected to early failure under compression test. Hence, alloys up to 5 wt.% of silicon has been selected as the optimum value. Further, 0.3 wt.% of Y2O3 particles are dispersed into WS1, WNS1, and WNCS1 alloys, and the alloys showed higher strength and hardness due to the combined effect of Ni, Co, Si, and Y2O3. The isothermal oxidation tests were performed on the sintered alloys at 800 ⁰C, 1000 ⁰C, and 1200 ⁰C for 10 hours. The activation energy of oxidation is increased with the silicon percentage in the tungsten due to the formation of SiO2 layer on the top of the tungsten. The presence of Ni/Co in the alloys provide more resistance to oxidation by forming NiWO4 and CoWO4 oxide layers in addition to SiO2. The addition of up to 1 wt. % Si along with Ni, Co, and Y2O3, showed the optimum mechanical properties and better oxidation resistance. Selective alloys are synthesized using SPS at 1300 C for 10 min at 50 MPa pressure to observe the effect of consolidation technique on densification, hardness and oxidation properties of alloys
Nano–Reinforced Al2O3–MgO–C Refractories
No full textRefractories in Al2O3–MgO–C system are an important class of oxide–carbon refractories. The structural property benefits of these refractories recommend their extensive usage in a range of steel making vessels (BOF’s, EAF’s, refining ladles), continuous casting components (ladle shroud, monotube, SEN), and many other flow–control devices (slide– gate plates, monoblock stopper). In steel making environments, these carbon based refractories work from ambient to 1600°C in oxidizing as well as non–oxidizing atmospheres. The structural properties of these high–temperature treated refractories in both oxidizing and non–oxidizing atmospheres are known to be essential for their increased service–life performance in steel making. Therefore, to gain the increased service–life performance, modern refractory processing strategies use nanoscale reinforcements as additional recipe parts for fabricating the fracture–resistant refractories with enhanced structural properties relative to the conventional or standard refractories (those systems that are fabricated without reinforcements). But to our knowledge such studies are very limited in the case of nano–reinforced Al2O3–MgO–C refractory. In the current work, nanoscale reinforcements, namely, YAG (Y3Al5O12; Yttrium Aluminium Garnet) nanopowder and EG\YAG (expandable graphite (EG)) hybridized powder were prepared in-house and studied their structural characteristics. Further, the nano–reinforced Al2O3–MgO–C refractories were fabricated by using these in-house prepared reinforcements (YAG; EG\YAG) with a reinforcement content of 0-2 wt.%. Subsequently, these nano–reinforced refractories were separately fired in oxidizing atmosphere as well as non–oxidizing (reducing) atmosphere at a maximum temperature of 1600°C. Then the structural properties of these fired refractories were further evaluated to determine the efficient function of a nanoscale reinforcement (YAG; EG\YAG) in promoting the structural property benefits. The nano-reinforced Al2O3–MgO–C refractories fired in oxidizing atmosphere exhibited significant enhancement of structural properties as compared to the standard components (R). Herein, both nanoscale reinforcements (YAG; EG\YAG) showed comparable structural property improvements in terms of oxidation resistance (73%–67%), hot-strength (10–11 MPa), and thermal shock performance (60– 67%) in Y20 (2 wt.% of YAG) and H20 (2 wt.% of EG\YAG) refractories, respectively. But the experimental data based on damage parameter calculations (DE) and energy–to failure characteristics (), indicated that the nano–reinforced refractory components fortified with EG\YAG (H20: DE~27%; ~36 kJ m-3) are more fracture–resistant than the nano–YAG reinforced refractories (Y20: DE~32%; ~29 kJ m-3). These structural property benefits with EG\YAG reinforcement were ascribed to the in–situ grown, bimodal microstructure with EG\YAG sintered framework in the nano–reinforced Al2O3–MgO–C refractory (H20) interior. Similarly, the nano-reinforced Al2O3–MgO–C refractories fired in non-oxidizing atmosphere, also showed a notable improvement in structural properties over the standard components (R). In this case, the nano-reinforced refractories (H20) with EG\YAG exhibited moderately enhanced structural properties as compared to the nano-YAG reinforced refractories (Y20). Herein, the structural property improvements are verified in terms of higher bulk density (Y20: 3.16 g cm-3; H20: 3.21 g cm-3 ), lower apparent porosity (Y20: 10.1%; H20: 9.2%), reduced stiffness (Y20: 84 GPa; H20: 62 GPa), increased load– bearing capacity (Y20: 0.423; H20: 0.591), enhanced mechanical reliability (Y20: m~22; H20: m~28), and greater dimensional -6 °C-1-6 °C- 1), respectively. These reinforcement benefits with EG\YAG were attributed to the development of in-situ grown EG\YAG sintered framework as a core (YAG)–sheath (EG) microstructure in all parts of the nano–reinforced Al2O3–MgO–C refractory (H20). All these beneficial features confirm that the nanoscale EG\YAG powder as an efficient reinforcement than the YAG nanopowder. Additionally, this work proposes materials design strategies for the fabrication of fracture–resistant, nano–reinforced refractories in Al2O3–MgO–C system against oxidative damage and thermal shock failure with the application of our newly proposed scaling parameters. They are named as strength factor (fs) and reinforcement index (Ri), respectively. Furthermore, the guidelines for implications of these research findings to practical applications involved in various potential areas of steel making are discussed
Comprehensive Analysis on Designing Cobaltite Spinel based Nanocomposite Sensors for Detection of Toxic Chemicals and Gases
No full textSpinel structures play very important role in many areas of materials science due to the large diversity of oxide compounds for various applications. Specifically, cobaltite-based spinels containing two distinctcation shave been use das potential sensordueto the irunique semiconducting and redoxproperty with desirable results. These nsing activity of these materials can be furtherenhanced by modifying reduced grapheneoxide(GO) and graphitic carbon nitride(g-C3N4) asasupportonit. This inturn allows the preparation of novel materials with promising characteristics. Keeping this in mind, this PhD thesisis focused on designing cobaltitespinel-based nano composite for the sensing of toxic analytes both in gas and liquid for mthrough the variation of their shape, size, morphology, and substitution of cations followed by different syntheticroutes. Broadly,it is focussedon two major objectives. The first major objective eisto modify different spinel based sensors(MnCo2O4, ZnCo2O4, and NiCo2O4) with reduce dgr phene oxide and use themas potential sensor for the detectionoftoxic gases(H2, NO2, andCH4) while the second major objectiveis to design spinel (MnCo2O4 and CuCo2O4) with both reduced graphene oxideandgraphitic carbon nitride for the detection fhazardous chemicals like pesticideandherbicides(chlorpyrifos and glyphosate). In the first project, I have demonstrated the morphological analysis of different structures (rod, sphere, flakes, and flower) based MnCo2O4 modified with rGO as potential sensor for detection of H2 gas (Chapter2, Sens. ActuatorsBChem., 2023, 380, 133348). After that, highlighting the effect off lowers haped spinel on sensing, the second project focusedona comparative study between normally synthesized ZnCo2O4 and MOF-derived ZnCo2O4 flower modifiedrGO for the detection of CH4 gas (Chapter3, Env. Sci. Nano, DOI:10.1039/D3EN00205E). In view of previous study, in the third objective, effort was given to de signacation substitited MOF-derived spinel based nano composite based potentialsensor for the sensing of NO2 gas (Chapter4, Sens. Actuators B Chem., 2024, 403,135182). In the electro chemical sensing part, this thesis documents our attempts to design spinel based nano composite supported by g-C3N4 as anefficientsensor for the detection of hazardous chemicals In this regard,in the fourth project,explorationon the design of MnCo2O4 particles decorate donbothrGOandg-C3N4 sheets to design highly selective and sensitive chlorpyrifossensor was done (Chapter5, J. Electroanal.Chem. 2022, 909,116115).Lateron, research was conducted to determine whether adequate growth of nano particlesong-C3N4 (H-C3N4) could be achieved by surface modification and improved electrocatalytic properties of the spinel nano particles.Towards this purpose, rGO ixand H-C3N4 modified MOF-derivedCuCo2O4 nanocomposite was designed a sanefficient sensor for the detection of glyphosate (Chapter6, Ind. Eng.Chem.Res., 2023,62, 3477). All the material spresentedin this thesis provedtobe highly sensitive, selective, stable, efficient, and recyclable system for the above applications which are of environmental significance
Robust Hand Gesture Recognition System for Real-time Multimedia Applications
No full textHand gesture recognition (HGR) is now a viable alternative for interaction between humans and machines. It has been applied to various fields, such as sign language interpretation, medical fields, virtual reality (VR) environments, and robotics. It plays a vital role in developing effective human-machine interfaces (HMIs) that enable direct communication between humans and machines. The research challenges such as poor lighting, occlusion, cluttered backgrounds, etc., make gesture identification difficult in real-time scenarios. The dissertation focuses on the development of a vision-based hand gesture recognition system using deep learning approaches, followed by the design of a low-cost human machine interface (HMI) to control multimedia applications using gesture commands in real-time scenarios. The first contribution includes a low-cost human-machine interface via a hand gesture recognition system based on the ensemble of Convolutional Neural Network (CNN) models. Though this technique exhibits good results in terms of detection accuracy, but, in the case of real-time inferencing tasks, the speed is reduced in terms of frames per second (fps) due to the accuracy-speed trade-off. This problem is addressed in the second contribution, where five pre-trained CNN models and a vision transformer (ViT) are used for gesture classification tasks. The best model among those used models is then utilized to operate multimedia applications like the VLC player and Spotify music player using gesture commands in real-time. However, this system fails to produce promising results under cluttered backgrounds, various lighting conditions, etc. To address those issues in the third contribution, we have divided our work into two parts by proposing two lightweight deep learning-based models. Here, we have chosen a small version of the ‘you only look once version 5’ (YOLOv5) model for its small size and fast inference speed. In the first part, we have frozen some convolutional layers in the baseline model. As a result, the number of trainable parameters, floating-point operations per second (FLOPS), and model size (in MB) have been reduced. Consequently, the inference speed is increased during real-time inference tasks without sacrificing significant detection accuracy. Next, the model was used to develop a robust hand gesture recognition system that enables physically challenged individuals to interact with systems. In the second section, we have proposed a lightweight YOLOv5s model by employing a channel pruning algorithm to reduce the model size, number of parameters, and FLOPs. Then, the channel-pruned YOLOv5s model is further utilized to build a gesture-controlled HMI to control two multimedia applications (VLC player, Spotify music player) in the presence of the background environment, low light, and various light conditions. Due to the speed-accuracy trade-off, the detection accuracy is slightly diminished compared to the baseline YOLOv5-small model. However, the inference speed (in fps) has been increased in real-time. Simulations are conducted on two publicly accessible and two custom datasets. The experimental results show that the suggested schemes are superior to existing works under various constraints. These model prototypes can also be utilized for sign language recognition, robotics, etc., under complex backgrounds and different lighting conditions in real-time
Fostering Innovation through Supply Chain Finance in Indian MSMEs: A Fintech Embedded Solution
No full textBanks and financing institutions play crucial role in traditional supply chains by providing the necessary finance and related services. Because of the proliferation of technology and an increasing number of businesses operating across various sectors are mulling over the possibility of utilizing this opportunity to facilitate supply chain finance (SCF). There is a rise in the number of requests for risk-free financing solutions to assist the day-to-day operations of Micro, Small and Medium Enterprises (MSMEs), which results in the increased complexity brought about by globalization. However, there are many problems with implementing SCF solutions into place, which make it harder for MSMEs to get the money for their day-to-day operations. In pursuance of this, the present research aims to evaluate the possible challenges that hinder the implementation of SCF in Indian MSMEs. Study also targets to evaluate and analyze the factors influencing the application of blockchain technology in SCF solutions for Indian MSMEs. The study investigates the role of fintech-enabled SCF solutions for attaining sustainable financial performance by Indian MSMEs. This study also attempts to conceptualize and validate the impact of SCF by implementing fintech-embedded solutions on the Indian MSMEs’ financial performance. The decision-making variables are identified through literature review, along with the consultation with financial experts, MSME owners and academic scholars. The present study has used various multi-criteria decision-making (MCDM) tools like fuzzy theory, analytic hierarchy process (AHP), sensitivity analysis, total interpretive structural modelling (TISM) and MICMAC analysis to explore and analyze the factors affecting implementation of SCF solutions in Indian MSMEs. Further, the study proposes the hypothetical model for the sustainable financial performance of MSMEs and empirically validates it using structural equation modelling (SEM) to bring into light the possible areas of enhancing the MSME’s financial performance through implementing fintech solutions. The study’s findings suggest that mismanagement of cash flows and working capital management disruptions are acting as the most prioritized barriers to SCF. The external factor of cultural challenges has been prioritized as the minimum-influence factor that has the least negative influence on the operations of SCF in MSMEs. The ‘real-time exchange of information’ by which data can be accessed by any partner is a very easy and quick way and the ‘transparent platform’ by which the data and information remain secure, are the most influential factors affecting the application of blockchain embedded SCF in Indian MSMEs. The empirical study validated the proposed model and confirmed the effect of SCF as mediator between independent variables (information sharing, role of financial institution, market visibility, supply chain risk reduction) and the outcome variable (sustainable MSME’s financial performance). Additionally, the moderation effect through ‘fintech solution’ is tested positively between the independent variables (information sharing, role of financial institution, market visibility, supply chain risk reduction) and the outcome variable (sustainable MSME’s financial performance). Managers should focus more on management of inflow and outflow of finance in the business to reduce the chance of financial risks. The new blockchain-enabled SCF should be implemented to overcome challenges associated with traditional SCF. This study also would help small business managers and academia to implement the empirical model constructed to reduce the financial risk of MSMEs’ and achieve sustainable financial performance through fintech-enabled SCF solutions. The SCF is crucial for solving MSMEs' financial issues. However, SCF is still developing and has great research potential. This study was conducted in India therefore, generalizing it to the developed world is impractical. This type of analysis should be done in emerging and developed countries to determine small firms' financial feasibility. This study solely uses data from tier-one and tier-two cities from the four states of India, further study can be made by taking all states as a population to better understand the implementation of SCF in MSMEs
Development of Graphene-Based Multi-Modal Piezoresistive Sensors for Human Health and Fruit Growth Monitoring
No full textThe modern world requires a modern health monitoring approach, which necessitates the requirement of smart wearable devices. Among wearable devices, flexible piezoresistive sensors have gained immense attention due to their broad applicability as wearable sensors for monitoring physical activities and physiology. The applicability of flexible piezoresistive sensors extends beyond wearables, encompassing a diverse array of applications, including smart farming, robotics, structural health monitoring, man-machine interface, etc. However, monitoring physical activities and physiology requires highly sensitive, long-run electromechanical stability, high flexibility or stretchability, and body-conformal piezoresistive sensors. To achieve the desired characteristics requires highly conductive and mechanically robust nanomaterials. Graphene has remarkable electrical, mechanical, and thermal properties, making it an ideal candidate for developing high-performance flexible piezoresistive sensors. In view of the importance of flexible piezoresistive sensors, the primary objective of this thesis is to develop highly sensitive, durable, stretchable, non-invasive, body conformal, eco-friendly, wearable piezoresistive sensors for monitoring human physical activities, physiology, and fruit growth. For the development of wearable strain sensors, graphene has been synthesized with the aim of reducing or eliminating the use of hazardous chemicals or strong acids in synthesizing graphene. In this study, graphene flakes have been synthesized through an electrochemical exfoliation process utilizing various electrolytes, including H2SO4, Pirahna, and CuSO4.5H2O, as intercalating agents. Initially, reduced graphene oxide (rGO) was synthesized by exfoliating pencil lead in H2SO4 electrolyte. The synthesized rGO was characterized using various analytical instruments, including XRD, TEM, FESEM, Raman spectroscopy, EDX, and SAED. Utilizing the prepared rGO, highly sensitive, durable, stretchable piezoresistive sensors have been developed by depositing rGO over silicone sealant using drop casting methodology. The fabricated rGO-sealant sensors have shown a gauge factor greater than 4000, durability longer than 1600 cycles at 100% strain and detection capability over a wide range of strains (0 - 120%). The developed rGO-sealant sensors demonstrated their ability to monitor physical activities and detect physical touch. Further, microsized multilayer graphene flakes (μG) were synthesized on a large scale by exfoliating graphite rods in piranha solution. The synthesized multi-layer graphene flakes were characterized using various methodologies which exhibit high-quality graphene flakes. Using the synthesized μG and silicone elastomer (SiE), a screen printable composite (SiE-μG) was prepared to fabricate supersensitive antibacterial piezoresistive sensors. The sensors were fabricated by depositing the SiE-μG composite on an orthopaedic bandage. The fabricated sensors have shown supersensitivity of 18300 at 35% strain, durability of 50000 cycles, and minimum detection limit of 0.4% strain. The developed strain sensors show antibacterial properties against Escherichia coli (E. coli). Moreover, the sensors have shown all the other significant characteristics required by a reliable wearable health monitoring device, such as ultra-conformality, skin-friendly, eco-friendly, fabrication simplicity, and cost-effectiveness. Owing to the above merits, the SiE-μG@Bandage sensors have demonstrated multifunctional applications in real-time monitoring of physical activities, physiological signals, joint movements, yoga postures, and meditation. Moving further, a lightweight, hydrophobic, and highly stretchable strain sensor using a synthesized graphene silicone-based screen printable conductive paste (GSiCP) for remote monitoring of fruit growth in real-time was fabricated. For the fabrication of GSiCP sensors, Few-layer graphene (FLG) was obtained by electrochemical exfoliation of graphite rod using a suspension of CuSO4.5H2O as electrolytes to eliminate the use of strong acids. The GSiCP printed hydrophobic strain sensor (GSiCP) shows high sensitivity, stretchability, and cyclic durability of 2050, 125%, and 5000 cycles, respectively. The continuous real-time on-field fruit (brinjal) growth was monitored remotely using a GSiCP sensor with the Internet of Things (IoTs). Further, these sensors have shown their capability to monitor various physiological signals, physical activities and orthopaedic joint movements. The objective of the thesis was extended towards the development of degradable strain sensors. The degradable strain sensors were developed by depositing A prepared composite of multilayer graphene flakes, Arabic gum, and cellulose acetate on a printing paper sheet. The developed sensors are water degradable. The developed sensors were used to monitor joint movements. The present research work addresses the new perspective for the development of wearable strain sensors for real-time human health monitoring using economically synthesized graphene flakes
Functionalization of Ferrocenyl Molecules for Bridged Architectures: Synthesis, Structure, Sensing and Amyloid Inhibition
No full textFerrocene-based organometallic derivatives stand out as exceptionally versatile molecular entities in the field of organometallic chemistry owing to its unique structural architecture properties, redox behavior and diversity in functionalization. In the last two-three decades, ferrocenyl chemistry has undergone remarkable advancement, positioning itself as a highly versatile building block with applications spanning medicinal chemistry, material science, catalysis, sensing and electronic communication. Recent studies indicate that the meticulous design and functionalization of ferrocenyl analogues across various structural levels can significantly tune their electronic, structural and biological properties. Among the widely known ferrocenyl derivatives, mono-functionalized ferrocenyl derivatives are extensively investigated, whereas research on bi-functionalized ferrocenyl frameworks remains limited. Moreover, the synthesis of symmetrical and unsymmetrical 1, 1’-bifunctionalized bridged ferrocenyl architectures with rotational flexibility led to molecular systems endowed with exceptional biological, sensor-based and catalytic properties, with a range of different conformational orientations. The immense potentials of functionalized bridged ferrocene-based organometallic derivatives and the scarcity of suitable reaction conditions prompted us to adopt a solid-supported reaction methodology to synthesize a diverse range of flexible and rigid heterocycle and carbocycle linked bridged ferrocenyl derivatives, along with di and tri ferrocenyl molecular architectures. The thesis, with six chapters, bridges these gaps by pioneering a solid-supported reaction methodology to synthesize a diverse array of multifunctional ferrocene-based organometallic systems encompassing, heterocycle and carbocycle tethered ferrocenyl molecules, heterocycle functionalized diastereomeric carba[3]ferrocenophanes, azine bridged di- and tri ferrocenyl molecular frameworks and enone bridged tri ferrocenyl system along with their characterization and structural evaluation. The synthesized heterocycle tethered ferrocenyl conjugates demonstrate significant advancements in amyloid inhibition study, effectively inhibiting bovine serum albumin (BSA) and hen egg white lysozyme (HEWL) amyloid fibrillation, along with the disaggregation of matured fibrils. Furthermore, the bridged di and tri ferrocenyl architectures exhibit high selectivity in sensing chemical warfare agents (CWAs) like picric acid (PA) and phosgene gas. In addition, an Arduino-based electrochemical device has also been fabricated with the azine bridged diferrocenyl receptor for detecting toxic phosgene gas
Feasibility Studies on Integrated Treatment of Chromium Contaminated Water using Microbial Consortium and Hairy Roots of Nicotiana Tabacum
No full textHexavalent chromium (Cr(VI)) contamination represents a critical environmental challenge in Odisha, given its status as a region abundant in chromite mines. The discharge of water from these mines into surface water bodies often contains Cr(VI) concentrations exceeding permissible limits. In response to this pressing issue, bioremediation emerges as a promising eco-friendly solution. By harnessing the natural processes of microorganisms to degrade or transform contaminants, bioremediation offers a potential means to mitigate Cr(VI) pollution effectively and sustainably. Chromium reducing bacterial cultures were isolated from the chromite mine soil. Five highly potent bacterial isolates were screened after acclimatization and identified using 16S rRNA sequencing. Three bacterial consortia namely CRC589, CRC580 and CRC489 were developed from the different combinations of screened bacterial isolates. The optimization of process parameters for achieving maximum Cr(VI) reduction involved two main methodologies. Initially, a conventional single-variable approach was employed to individually optimize factors such as carbon source, nitrogen source, pH, incubation temperature, inoculum size and inoculum age. Subsequently, to further investigate the interactive effects of key variables on Cr(VI) reduction, Box Behnken design within the framework of Response Surface Methodology was implemented. Optimization results revealed that the optimum temperature for all the three consortia was 35°C and optimum pH for consortia CRC589, CRC489 was 7 whereas pH 8.5 was known to optimal for CRC580. Batch and continuous studies for Cr(VI) reduction were conducted with consortiumCRC489. Cr(VI) reduction in the CSTR revealed that at the dilution rate of 0.01 h-1, the maximum reduction of 91 % and 80% was achieved at the initial Cr(VI) concentration of 10 mg/L and 25 mg/L respectively. Hairy roots were induced from Nicotiana tabacum through the infection of Agrobacterium rhizogenes MTCC 2364. Effect of various influencing factors on the hairy root induction such as co-cultivation period, infection time, Acetosyringone concentration and ultrasonication treatment was evaluated. Maximum of 36.35 % of transformation efficiency was achieved at 72 hours of co-cultivation period with 30 minutes of infection time. The supplement of 100 μM acetosyringone increased the transformation efficiency to 55.35 % with reduced number of days for root induction. Hairy roots were used to treat Cr(VI) solutions to understand the mechanism of action and to evaluate their efficiency for the chromium removal from varying chromium concentration. The effluent of CSTR study was treated with hairy roots and resulted in a Cr(VI) level below the permissible limit in the water with 99.28 % reduction. In addition to that the production of secondary metabolite from the hairy root under the influence of various Cr(VI) concentration was evaluated by HPLC. The production of nicotine, a secondary metabolite from N. tabacum was elicited significantly at the lower concentrations (2 mg/L and 5 mg/L) of Chromium
Mechanical and Tribo Performance of Agave Lechuguilla-A Sustainable Natural Fiber and Its Composite
No full textEnvironmental awareness has become a significant driving force for researchers worldwide, leading them to focus on studying natural fiber reinforced polymer composites as a cost-effective alternative to synthetic fiber reinforced composites. The abundant availability of natural fibers and the simplicity of the manufacturing process have attracted researchers to explore various low-cost fibers available globally and assess their suitability for reinforcement purposes, as well as their ability to meet the necessary specifications for high-quality polymer composites in diverse applications. Considering its affordability and remarkable specific mechanical properties, natural fiber emerges as an excellent renewable and biodegradable substitute for widely used synthetic reinforcements such as glass, aramid, carbon, and others. Despite the growing research and environmental sustainability of natural fibers, their application is constrained to low-end uses owing to their relatively lower strength when compared to synthetic fibers. Moreover, these fibers face challenges related to poor adhesion, higher hydrophilicity, and reduced compatibility with polymer matrices. To address these challenges, researchers are pursuing diverse chemical treatment methods for natural fibers. Natural fibers like jute, bamboo, luffa, abaca, ramie, kenaf, coir, pine apple, date palm, sisal, hemp, etc., have already proved their potential as a reinforcement material after chemical modification for the fabrication of polymer composites. Like all experimented natural fibers, the potential of short Agave Lechuguilla (AL) fiber as a reinforcement material in polymer-based composites has yet to be investigated. The Agave Lechuguilla plants are mainly found in the South American continent, particularly in Mexico and nearby regions. The fiber quality of this plant could be recognized by its existing applications in the fields of mats, carpets, ropes, cords, brushes, insulating materials for roofs, household construction, and paper industries. These versatile applications have proved their worth as a structural material with reasonably good mechanical properties. The Agave Lechuguilla fiber consists of 79 percent cellulose, 3-6 percent hemicellulose, and 15 percent lignin, as well as other components like ash, moisture, etc. By looking at the structure of the fiber, it can be said here that due to its cellulosic content, this fiber can be considered a sustainable and suitable fiber to be used as a reinforcing material in polymers for structural and other applications. Against this background, in this dissertation, an attempt has been made to study the mechanical and tribological performance of Agave Lechuguilla fiber reinforced epoxy composite. The manufacturing of the composite is carried out using the conventional hand-lay-up method by reinforcing varying weight percentages of fibers. Enhancement of compatibility between the fiber and matrix is achieved through the chemical modification of fibers using alkali, potassium permanganate, and hydrogen peroxide treatment. It is found that hydrogen peroxide- treated fiber composite exhibits favorable strength and stiffness in comparison to other treatments. An assessment of moisture absorption behaviour is performed on both treated and untreated fiber composites. The kinetics of moisture absorption for the composite is also explored. The findings of the study validate the applicability of the Fickian diffusion model for describing moisture absorption within the composite material. To assess the tribo-potential of AL fibers, experiments involving solid particle erosion tests and abrasive wear tests have been carried out. All tests are executed following the ASTM standard guidelines. The outcomes of the solid particle erosion test clearly indicate the semi-ductile nature of the composite behavior. From the abrasive wear study, it is found that reinforcement of AL fiber significantly enhances the wear resistance properties when compared to the neat epoxy resin. This improvement, however, is restricted to a reinforcement of AL fiber up to thirty-weight percent. Further, morphological analyses are performed on SEM to observe the cause of failure due to fracture during mechanical tests and worn-out surfaces during tribological investigations. The findings presented in this study can provide a foundational starting point for both industrial designers and researchers interested in designing and developing polymer matrix composite components utilizing Agave Lechuguilla fiber as reinforcement. The whole dissertation has been divided into seven chapters to make the analysis independent of each other as far as possible. Major works on mechanical characterization, moisture absorption characteristics, erosive and abrasive wear characteristics of AL-epoxy composite are given in chapters 3, 4, 5, and 6, respectively
Source Camera Identification for Compressed JPEGs through PRNU and Machine Learning
Full text linkOnline Social networks (OSN) such as Facebook, Twitter, and WhatsApp, etc. are excessively used to socialize or gain insights into people’s behavior and their activities. Everyday millions of images and videos are captured and uploaded, which is then misused by a felon to fulfill their evil-deeds. Today’s digital cameras store image metadata along with the image itself on the media card, DVDs, and RD-ROMs. The image metadata includes the data about the image such as the date and time the image was captured, the focal length, shutter stops, make, and model of the camera. If a forensics examination is conducted only on the computer then metadata can be easily used to identify the images and to link back to a specific camera. However, the metadata can be easily editable through different software or can be lost if the image file format changes, for example, software processing is applied, downloaded, or transfer through online social networks. It is difficult to standardize digital images for the courtroom due to rapid changes in the growth of computer-related technologies. The Digital Forensic Research community keeps suggesting innovative approaches to study digital videos and images and also to identify the probable source. This can be done by analyzing the camera sensor-specific artifacts left behind in an image. However, the high degree of compression destroys the camera sensor-specific artifacts by uploading the image to online networking sites. JPEG compression is one of the standard processes in most consumer-level cameras. It is a standard compression algorithm, however, the size and the quality tradeoff are at the manufacturer’s and the users’ discretion. Our work is to attempt to investigate the source camera identification problem, we present a model on an unknown model detection problem to find the source of the image through source camera identification that works on compressed images too. We propose a PRNU and machine learning-based method to identify the source with an accuracy of 98%. We perform our experiments using images from the Dresden dataset. The proposed approach outperforms the current state-of-the-art in terms of accuracy in source camera identification on JPEG compressed images