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Abstract The traditional approach of open-sun drying is facing contemporary challenges arising from the widespread adoption of energy-intensive methods and the quality of drying. In response, solar dryers have emerged as a sustainable alternative, utilizing solar thermal energy to effectively dehydrate vegetables. This study investigates the performance of a single-basin, double-slope solar dryer utilizing natural convection for drying bottle gourds and tomatoes, presenting a sustainable alternative to traditional open-sun drying. The solar dryer exhibited superior moisture removal efficiency, achieving a 94.42% reduction in tomatoes and 83.87% in bottle gourds, compared to open-sun drying. Drying rates were significantly enhanced, with maximum air and plate temperatures reaching 54.42 °C and 63.38 °C, respectively, accelerating the dehydration process. Moisture diffusivity analysis revealed a marked improvement in drying behavior under solar drying, with values ranging from 3.12 × 10−11 to 4.31 × 10−11 m2/s for bottle gourds, and 4.65 × 10−11 to 2.31 × 10−11 m2/s for tomatoes. Energy efficiency assessments highlighted the solar dryer’s advantage, with exergy efficiency peaking at 61.78% for bottle gourds and 68.5% for tomatoes. Furthermore, the activation energy required for drying was significantly lower in the solar dryer (29.14–46.41 kJ/mol for bottle gourds and 27.16–55.42 kJ/mol for tomatoes) compared to open-sun drying, enhancing energy conservation. Visual inspections confirmed the superior quality of the solar-dried vegetables, free from dust and impurities. An economic analysis underscored the system’s viability, with payback periods of 2 years for bottle gourds and 1.6 years for tomatoes. Overall, this study demonstrates the efficacy of solar dryers in optimizing vegetable preservation while promoting energy efficiency, aligning with global sustainability goals by reducing post-harvest losses and supporting eco-friendly practices.

Abstract Solar collector systems efficiently transform sunlight into energy that may be used to meet various needs. This research aimed to use the Taguchi method to determine the ideal operating parameters for a solar thermal collector with a rectangular spiral absorber. Controllable parameters including mass flow rate, solar radiation, and absorber design were manipulated during the energy recovery process, and features like PV temperature and outlet water temperature were used to assess the system’s effectiveness. The findings indicate that certain criteria significantly affect response indicators. The observed percentage contribution of absorber design, solar radiation, and the mass flow rate was 69.19%, 27.99%, and 2.83% in PV surface temperature. In comparison, the individual percentage contributions were 73.63%, 13.51%, and 10.57% for absorber design, solar radiation and mass flow rate for water output temperatures. The present model’s R2 values for PV and outlet water temperatures are 97.24% and 99.67%, respectively. The Predictive regression model was found in fine harmony and the maximum percentage error is limited to 0.68%. The maximum analytical electrical efficiency was observed with a spiral rectangular absorber of 14.57% at the lowest mass flow rate of 0.04 kg/s at the lowest radiation level of 600 W/m2. In comparison, maximum analytical thermal efficiency was observed with a spiral rectangular thermal absorber of 63.56% at the highest flow rate of 0.06 kg/s and the highest solar radiation level of 1000 W/m2. The analytical and experiment findings were in better agreement in this study, with the highest relative error of 7.52%. According to the study’s findings, the rectangular absorber-based PVT system is at its best at a higher mass flow rate to lower PV temperature and boost thermal energy recovery via water. The present research work can be extended for exergy, environmental, and economic feasibility analysis.

Abstract Firecrackers are a vital element of cultural festivities that happen worldwide. However, the hazardous by-products they emit have a significant impact on environmental pollution, leading to the greenhouse effect and climate change. Aluminium powder serves as the fuel in the traditional flash powder mixture, nitrate of potassium serves as an oxidizing agent, and sulphur acts as the igniter at exact concentrations. The presence of sulfur in the flash powder mixture is critical as it acts as an igniter, contributing to the formation of sulfur dioxide, which can cause environmental harm. We carried out an experiment employing Sargassum wightii brown seaweed powder as a replacement for sulphur at specific amounts to lessen the effects of sulphur in flash powder. We discovered that Sargassum wightii brown seaweed powder may replace up to 50% of the sulphur significance in the flash powder mixture without impairing the flash powder's traditional performance. Our experiments included impact and friction sensitivity, SEM, and FTIR analyses to evaluate the improved flash powder composition. The results revealed that the modified flash powder mixture SP5 and SP10 emits less emission by 12% and 21%, and produces similar noise performance of 108 and 107 dB(A) to the normal flash powder composition (SP), affirming that the SP10 flash powder is a viable alternative. Moreover, in our relentless pursuit to mitigate the detrimental effects on our environment, we have ingeniously introduced a novel product—the Chinese cracker made from vegetable waste paper. Not only does this innovative solution address concerns regarding land pollution, but it also presents a sustainable approach to consumer goods.

The increasing occurrence of severe vulnerabilities, such as natural catastrophes and man-made attacks, has resulted in a corresponding rise in power outages on a global scale. Given the growing recognition of such exceptional occurrences, there is a pressing need to examine the matters pertaining to resilience and the mitigation of risks. This study presents a comprehensive overview of the current state-of-the-art in power system resiliency, as well as an exploration of the measures required to ensure a sustainable environment.These instances of measures include resilience by enabling localized generation and distribution of electricity,diversification of energy resources, withstanding of severe weather conditions, cyberattacks and enabling communities to proactively address the consequences of power outages. There are multiple approaches to bolstering resiliency, which aim to facilitate recovery from unforeseen circumstances and promote stability in the face of uncertain events. These measures also serve to mitigate the impact of unexpected incidents such as power outages. Integrating unpredictable renewable energy sources like solar and wind power into energy networks is difficult, especially in terms of resilience. Renewable energy output fluctuates owing to weather and time of day, requiring sophisticated grid management, energy storage, and demand-response mechanisms to maintain system balance and resilience. This study elucidates the enhanced principles of power system dependability and resilience, in addition to several ways for establishing a sustainable power ecosystem. It examines the complex dynamics of risk assessment, including equipment failures, natural disasters, and human errors, to determine their likelihood and implications. Moreover, the study thoroughly examines the critical moments that occur after accidents, emphasizing the need of prompt reaction and recovery measures in reducing downtime and restoring regular operations to impacted power networks. This involves determining the fundamental reasons behind the incidents, such as whether they arise from equipment malfunctions, human mistakes, external influences like natural calamities, or cyber assaults. In addition, the report examines the efficacy of current response protocols and emergency procedures in reducing the impact of accidents and restoring regular operations to impacted electrical systems.

Lightweight materials with better resistance to sliding wear are prominent candidates for automobile brake drums, clutch pads and cylinder block applications to facilitate fuel economy. This attempt is reserved to cater to materials with higher tribological quality needs. Less dense foamy pumice stone particles were involved in three different percentages (5, 10, and 15 wt%) to reinforce lightweight AZ31 Mg alloy. A stir-assisted squeeze casting technique was pursued to process the composite and refine the grain structure. A phase detection, elemental mapping and microstructure study were done through X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), and scanning electron microscopy (SEM), respectively. An experimental dry sliding wear scrutiny was administered using a pin-on-disc apparatus by considering: (i) ambient and elevated temperature environments and (ii) three different levels of loads. The results reveal a significant drop in wear loss and a frictional coefficient for 15% pumice-loaded composite than the base alloy. Post-wear examination acknowledges the fact that the ambient temperature wear is governed by adhesive-abrasive wear and high temperature is by abrasive wear mechanisms. Worn-out scrutiny authenticates the presence of oxide layers and their role in lubrication. A comparative study with previous works upholds the novel magnesium composite is the right candidate for the mentioned automobile applications.

Abstract Perovskite solar cells (PSCs) hold potential for low-cost, high-efficiency solar energy, but their sensitivity to moisture limits practical application. Current fabrication requires controlled environments, limiting mass production. Researchers aim to develop stable PSCs with longer lifetimes under ambient conditions. In this research work, we investigated the stability of perovskite films and solar cells fabricated and annealed in natural air using four different anti-solvents: toluene, ethyl acetate, diethyl ether, and chlorobenzene. Films (about 300 nm thick) were deposited via single-step spin-coating and subjected to ambient air-atmosphere for up to 30 days. We monitored changes in crystallinity, electrical properties, and optics over time. Results showed a gradual degradation in the films’ crystallinity, morphology, and electro-optical properties. Notably, films made with ethyl acetate exhibited superior stability compared to other solvents. These findings contribute to advancing stable and high-performance PSCs manufactured under normal ambient conditions. In addition, we also discuss the possible machine learning (ML) approach to our future work direction to optimize the materials structures, and synthesis process parameters for future high-efficient perovskite solar cells fabrication.

In this experimental study, efforts were undertaken to augment the overall efficiency of a dual-fuel engine. This present study was conducted in three steps. In the initial phase, Aluminium oxyhydroxide (AlO(OH)) was synthesized and analyzed using UV–visible spectroscopy, XRD (X-ray diffraction), Thermogravimetric (TG) analysis, and Differential Scanning Calorimeter (DSC). In the second part of the study, the impact of AlO(OH) NP dosage on the performance of a producer gas-powered diesel engine was investigated. To optimize adequate AlO(OH) NPs addition, three working fluids are prepared by dissolving NPs in dairy scum oil methyl ester (DiSOME) biodiesel ranging from 20 to 60 ppm and varied in steps of 20. In the next phase, the present study examined the effect of 60 ppm of various NPs, including multi-walled carbon nanotubes (MWCNT), Aluminum oxide (Al2O3), and AlO(OH) on the combustion and emission characteristics of a 1-cylinder 4-stroke direct injection diesel engine operating in dual fuel mode using a combination of DiSOME and producer gas. The study concluded that DiSOME-PG operation with 60 ppm AlO(OH) and without nano-addition resulted in decreased BTE by 2.9 % and 14.6 % respectively compared to diesel-supported dual fuel operation. To the extent that exhaust levels are concerned, AlO(OH) addition to the DiSOME-PG combination lowers hydrocarbon (HC) and carbon monoxide (CO) emissions than identical fuel amalgamation without AlO(OH) NP. It is noticed that the retarded combustion related to the DiSOME-producer gas mixture can be improved with NP addition. The DiSOME-producer gas functioning with NPs addition is the individuality of this current effort.

A healthy environment improves the quality of life on Earth, while natural disasters affect the quality of the environment. An area’s Landslide Hazard Zonation (LHZ) provides key information about the susceptibility to natural or manmade disasters. Using the Weighted Overlay Technique, this research aims to develop the landslide susceptibility and zonation mapping of Koh-e-Suleman Range (a hill station around the heritage site). Six causative factors are evaluated: geology, elevation, slope inclination, distance from streams, type of soil, and annual rainfall intensity, considering equal risk influence for all the factors. All causative factor maps were generated to yield equal classes and provide uniformity to the results except for soil types found in the study area. The findings indicate that the study area may comprise four landslide hazard zones with high, medium, low, and very low-intensity susceptibility of landslides. The accuracy of the final LHZ map is verified by comparing the hazard zonation area percentages with the global landslide inventory map from a macro-study of NASA. It was found that the study areas largely fall within low- and very low-hazard zones.

The present investigation focuses on the microstructural behavior and mechanical properties of Aluminium alloy 2024 reinforced with SiC nanoparticles by applying the Friction Stir Processing (FSP) technique. Taguchi L9 orthogonal array was used to find the optimal process parameters. The experiment used the expected best process parameters, which confirmed the predicted highest value for the mechanical characteristic. Traverse speed, axial load, and rotating speed are the main factors affecting aluminum metal matrix composite. Hence, this experiment examined the effects of five different tool spinning speeds, specifically 800, 900, 1000, 1100, and 1200 rpm. Weld samples are fabricated wherein the stir zone contains SiC nanoparticles. The results of the study indicate that the optimal welding rotational speed of 1000 rpm has a significant impact on the microstructure, wear rate, and microhardness. Specifically, it was observed that the stirred zone exhibited enhanced wear resistance compared to other zones. The study's findings revealed that after implementing friction stir processing (FSP), a well-defined shear zone was observed on the advancing side of the stir zone. Additionally, it is found that the uniform dispersion and strong bonding of SiC particles with an aluminium matrix further enhance wear resistance.

This study primarily investigates the antibacterial properties, tensile strength, flexural strength, impact strength, hardness, and microstructural characteristics of a composite, utilizing Scanning Electron Microscopy (SEM) for detailed analysis. The composite, crafted through a hand layup technique, optimally blends ramie and hemp fibers within an epoxy matrix. Its antibacterial efficacy was rigorously tested against common bacterial strains, demonstrating significant potential for medical and hygienic applications. The evaluation of tensile strength revealed the composite’s enhanced capability to withstand longitudinal stresses, with a peak strength of 37.81 MPa, achieved by increasing ramie fiber content. In addition, a flexural strength of 39.72 MPa underscored the material’s robust resistance to bending forces, crucial for structural uses. The composite’s impact strength, accessed via the Izod impact test, registered at 0.021 J/m2, indicating its ability to absorb and dissipate energy upon sudden impacts, making it ideal for automotive and protective gear applications. The Rockwell hardness test further quantified the composite’s resistance to surface indentation, vital for wear-resistant surfaces. SEM analysis offered a comprehensive view of the microstructural dynamics between the fibers and the matrix, especially under tensile stress, highlighting the intricacies of fiber–matrix adhesion, crack propagation, and overall composite integrity. Notably, the antibacterial properties were confirmed by an 18 mm inhibition zone, which showcases the composite’s ability to inhibit bacterial growth effectively.

Solar energy systems operate directly connected to the sun. Solar chimney power plants are privileged systems that can provide power output even in cloudy weather and during hours when there is no sun. The design and sizing of this system, which researchers focused on after its first application in the 1980s, is very effective on its performance. In this study, the collector slope and chimney slope that give maximum power output for the Manzanares pilot plant are investigated with a 3D CFD model. Simulations made using the RNG k-e turbulence model and the DO (discrete ordinates) solar ray tracing algorithm provide results that are in high compatibility with experimental data and literature. It is understood that the system provides maximum power at 0.6° collector slope and 1.5° chimney divergence angle. It is seen that the system, which gives a power output of approximately 46 kW in the reference case, exceeds the power output by 4.5 times and reaches 216.853 kW in the design that includes the collector and chimney slope. The effects of the main elements of the system on the performance are also included by changing the collector radius and chimney height while preserving these inclination angles. More than the power output in the reference case, 49.233 kW, can be achieved with the inclined design, with a collector radius of 73.2 m and a chimney height of 155.68 m. Although the effect of increasing the chimney height on power output continues after 1.2 floors, its effect decreases. In the study, it is seen that increasing the chimney height and changing the collector radius provide a greater increase in power output. Furthermore, the scope extends to the incorporation of an Artificial Neural Network (ANN) model, presenting a novel approach to predicting SCPP system performance. The findings ascertain the utilisation of 9 neurons in the hidden layer of the ANN, demonstrating a precise alignment with the study data.

The magnesium alloy composite is a vital material for automotive applications due to its features like high stiffness, superior damping resistance, high strength, and lightweight. Here, the motto of research is to establish the AZ91 alloy nanocomposite with the exposures of 0, 1, 3, and 5 volume percentages (vol%) of nano zirconium dioxide (ZrO2) particles (50nm) through fluid stir metallurgy route associated with 1x105 Pa vacuum die cast process. Exposures on structural morphology, hardness, and impact toughness of composite are analyzed and identified as the nano AZ91 alloy composite enclosed with 5vol% is homogenous particle dispersion, enhanced hardness (97.6HV), and optimum toughness of 21.2J/mm2. However, composite faces machining difficulties due to the hard abrasive particles with higher hardness, resulting in tool wear. This experiment predicts the optimum mill parameters during the end mill operation of magnesium alloy nanocomposite (AZ91/5vol%) by using a tungsten carbide coated end mill cutter to attain the maximum metal removal rate with low surface roughness and tool wear analyzed via the general linear model (GLM) ANOVA approach. The input conditions for end milling operation vary, like feed rate (0.1 -0.4mm/rev), depth of cut (0.05 -0.2mm), and spindle speed (250-1000rpm). During the ANOVA GLM approach, the L16 design experiment is fixed for further interaction analysis. The results predicted by the depth to cut and feed rate were dominant and played a major role in deciding the tool wear, surface roughness, and MRR.

In this work, we conduct acidified aqueous glycerol pre-treatment (AAG) on rice husks (RH) and utilize the response surface methodology (RSM) to assess the impact of pre-treatment parameters. The primary objective of this research is to optimize the parameters to maximize the cellulose content within RH. The parameters under consideration encompassed temperature (ranging from 80 to 110 °C), retention time (spanning 15 to 45 min), and biomass loading (varying from 5 to 10 wt. %). To achieve this optimization, we perform the Box-Behnken Design (BBD) within the framework of RSM. Additionally, we scrutinize the interactive effects of these parameters on cellulose content. Our findings unveiled a remarkable increase in cellulose content, escalating from 40 % in untreated RH to an impressive 75 % in pre-treated RH under the optimized conditions of 110 °C for 45 min with a 5.0 wt. % biomass loading. To further evaluate the effectiveness of the pre-treatment process, we conduct scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses, shedding light on alterations in surface morphology and crystallinity of RH. This investigation yields valuable insights, presenting novel opportunities for the efficient conversion of readily available rice husks into high-value products, such as biofuels and composites.

Abstract A numerical analysis of a CdTe/Si dual-junction solar cell in terms of defect density introduced at various defect energy levels in the absorber layer is provided. The impact of defect concentration is analyzed against the thickness of the CdTe layer, and variation of the top and bottom cell bandgaps is studied. The results show that CdTe thin film with defects density between 1014 and 1015 cm−3 is acceptable for the top cell of the designed dual-junction solar cell. The variations of the defect concentrations against the thickness of the CdTe layer indicate that the open circuit voltage, short circuit current density, and efficiency (ƞ) are more affected by the defect density at higher CdTe thickness. In contrast, the Fill factor is mainly affected by the defect density, regardless of the thin film’s thickness. An acceptable defect density of up to 1015 cm−3 at a CdTe thickness of 300 nm was obtained from this work. The bandgap variation shows optimal results for a CdTe with bandgaps ranging from 1.45 to 1.7 eV in tandem with a Si bandgap of about 1.1 eV. This study highlights the significance of tailoring defect density at different energy levels to realize viable CdTe/Si dual junction tandem solar cells. It also demonstrates how the impact of defect concentration changes with the thickness of the solar cell absorber layer.

This multilevel inverter produces a multi-stepped output voltage based on series connection of power cells making the use of standard low voltage components. The proposed topology uses only one voltage source and with combination of capacitors and is able to produce maximum boost with reduced number of components and voltage stress. One module can generate 7 voltage levels by using one DC power supply and two capacitors. This paper also proposes suitable ways of extension to achieve higher voltage levels thereby making the harmonic distortion very low. The proposed topology specifically addresses a very potential problem associated with capacitor type inverter that is unsteadiness or disproportionate discharge of capacitor voltage. Another potential problem is high inrush current during charging and this is also addressed in a unique. A comprehensive comparison between the proposal and other capacitor based multilevel inverter topologies is carried out based on number of components, voltage stress, cost function and other performance parameters. The main novelty lies in the reduction in number of components, multiple extension variants basic topology, addressing capacitor voltage imbalance and high inrush current during charging. Finally, the working, efficiency and accuracy of the proposed inverter are validated by laboratory prototype models.

This research aims to provide an efficient and cost-effective renewable energy supply. It assesses the potential for photovoltaic (PV) and hydro energy in Pirthala, Haryana, India, using HOMER Pro® v3.14.2. A Hybrid renewable energy system (HRES) can continuously power 855 homes. The optimal HRES configuration comprises well-optimized PV modules, hydro turbines, converters, and batteries. The top four configurations were selected based on criteria such as net present cost (NPC) and cost of energy production (COE). The most effective HRES configuration involves a 3461-kW solar array, a 98.1 kW hydro turbine, 304 lithium-ion batteries of 100 kWh, and a 2785-kW converter, achieving a 100 % integration of renewable energy. This ideal HRES was thoroughly assessed regarding economic, technical, and renewable energy considerations. The results and the optimized HRES configuration can serve as a valuable reference for similar initiatives in rural areas, contributing to adopting renewable energy sources and enhancing energy access and reliability.

This research aims to provide the groundwork for smartly categorizing hand movements for use with prosthetic hands. The hand motions are classified using surface electromyography (sEMG) data. In reaction to a predetermined sequence of fibre activation, every single one of our muscles contracts. They could be useful in developing control protocols for bio-control systems, such human-computer interaction and upper limb prostheses. When focusing on hand gestures, data gloves and vision-based approaches are often used. The data glove technique requires tedious and unnatural user engagement, whereas the vision-based solution requires significantly more expensive sensors. This research offered a Deep Neural Network (DNN) automated hand gesticulation recognition system based on electromyography to circumvent these restrictions. This work primarily aims to augment the concert of the hand gesture recognition system via the use of an artificial classifier. To advance the recognition system's classification accuracy, this study explains how to build models of neural networks and how to use signal processing methods. By locating the Hilbert Huang Transform (HHT), one may get the essential properties of the signal. When training a DNN classifier, these characteristics are sent into it. The investigational results reveal that the suggested technique accomplishes a better categorization rate (98.5 % vs. the alternatives).

Cardiovascular diseases, particularly coronary artery disease, pose big challenges to human life. Deployment of the stent is a preferable treatment for the above-mentioned disease. However, stents are usually made up of shape memory alloy called Nitinol. The poorer surface finish on the machined nitinol stents accelerates the migration of Nickel ions from the implanted nitinol stent, which is considered toxic and can lead to stenosis. The current study deals with controlling surface quality by minimising surface roughness and improving corrosion resistance. Femtosecond laser (fs-laser 10−15 s) micromachining was employed to machine the Nitinol surface to achieve sub-micron surface roughness. The Grey relational analysis (GRA)-coupled design of the experimental technique was implemented to determine optimal levels of four micromachining parameters (laser power, pulse frequency, scanning speed, and scanning pattern) varied at three levels to achieve minimum surface roughness and to maximise the volume ablation. The results show that to yield minimum surface roughness and maximum volume ablation, laser power and scanning speed are in a higher range. In contrast, the pulse frequency is lower, and the scanning pattern is in a zig-zag manner. ANOVA results manifest that scanning speed is the predominant factor in minimising surface roughness, followed by pulse frequency. Furthermore, the corrosion behaviour of the machined nitinol specimens was evaluated, and the results show that specimens with lower surface roughness had lower corrosion rates.

Integration of photovoltaic (PV) systems, desalination technologies, and Artificial Intelligence (AI) combined with Machine Learning (ML) has introduced a new era of remarkable research and innovation. This review article thoroughly examines the recent advancements in the field, focusing on the interplay between PV systems and water desalination within the framework of AI and ML applications, along with it analyses current research to identify significant patterns, obstacles, and prospects in this interdisciplinary field. Furthermore, review examines the incorporation of AI and ML methods in improving the performance of PV systems. This includes raising their efficiency, implementing predictive maintenance strategies, and enabling real-time monitoring. It also explores the transformative influence of intelligent algorithms on desalination techniques, specifically addressing concerns pertaining to energy usage, scalability, and environmental sustainability. This article provides a thorough analysis of the current literature, identifying areas where research is lacking and suggesting potential future avenues for investigation. These advancements have resulted in increased efficiency, decreased expenses, and improved sustainability of PV system. By utilizing artificial intelligence technologies, freshwater productivity can increase by 10 % and efficiency. This review offers significant and informative perspectives for researchers, engineers, and policymakers involved in renewable energy and water technology. It sheds light on the latest advancements in photovoltaic systems and desalination, which are facilitated by AI and ML. The review aims to guide towards a more sustainable and technologically advanced future.

The rapid development of digitalization, the Internet of Things (IoT), and Industry 4.0 has led to the emergence of the digital twin concept. IoT is an important pillar of the digital twin. The digital twin serves as a crucial link, merging the physical and digital territories of Industry 4.0. Digital twins are beneficial to numerous industries, providing the capability to perform advanced analytics, create detailed simulations, and facilitate informed decision-making that IoT supports. This paper presents a review of the literature on digital twins, discussing its concepts, definitions, frameworks, application methods, and challenges. The review spans various domains, including manufacturing, energy, agriculture, maintenance, construction, transportation, and smart cities in Industry 4.0. The present study suggests that the terminology “3 dimensional (3D) digital twin” is a more fitting descriptor for digital twin technology assisted by IoT. The aforementioned statement serves as the central argument of the study. This article advocates for a shift in terminology, replacing “digital twin” with “3D digital twin” to more accurately depict the technology’s innate potential and capabilities in Industry 4.0. We aim to establish that “3D digital twin” offers a more precise and holistic representation of the technology. By doing so, we underline the digital twin’s analytical ability and capacity to offer an intuitive understanding of systems, which can significantly streamline decision-making processes using the digital twin.

Abstract The use of solar energy is one of the most prominent strategies for addressing the present energy management challenges. Solar energy is used in numerous residential sectors through flat plate solar collectors. The thermal efficiency of flat plate solar collectors is improved when conventional heat transfer fluids are replaced with nanofluids because they offer superior thermo-physical properties to conventional heat transfer fluids. Concentrated chemicals are utilized in nanofluids' conventional synthesis techniques, which produce hazardous toxic bi-products. The present research investigates the effects of novel green covalently functionalized gallic acid-treated multiwall carbon nanotubes-water nanofluid on the performance of flat plate solar collectors. GAMWCNTs are highly stable in the base fluid, according to stability analysis techniques, including ultraviolet–visible spectroscopy and zeta potential. Experimental evaluation shows that the thermo-physical properties of nanofluid are better than those of base fluid deionized water. The energy, exergy and economic analysis are performed using 0.025%, 0.065% and 0.1% weight concentrations of GAMWCNT-water at varying mass flow rates 0.010, 0.0144, 0.0188 kg/s. The introduction of GAMWCNT nanofluid enhanced the thermal performance of flat plate solar collectors in terms of energy and exergy efficiency. There is an enhancement in efficiency with the rise in heat flux, mass flow rate and weight concentration, but a decline is seen as inlet temperature increases. As per experimental findings, the highest improvement in energy efficiency is 30.88% for a 0.1% weight concentration of GAMWCNT nanofluid at 0.0188 kg/s compared to the base fluid. The collector's exergy efficiency increases with the rise in weight concentration while it decreases with an increase in flow rate. The highest exergy efficiency is achieved at 0.1% GAMWCNT concentration and 0.010 kg/s mass flow rate. GAMWCNT nanofluids have higher values for friction factor compared to the base fluid. There is a small increment in relative pumping power with increasing weight concentration of nanofluid. Performance index values of more than 1 are achieved for all GAMWCNT concentrations. When the solar thermal collector is operated at 0.0188 kg/s and 0.1% weight concentration of GAMWCNT nanofluid, the highest size reduction, 27.59%, is achieved as compared to a flat plate solar collector with water as a heat transfer fluid.

Present study investigates the effect of palm biodiesel blends with and without oxygenated alcohol dimethyl carbonate (DMC) on compression ignition engine. H2SO4 was used to treat the crude palm oil. Furthermore, acid treated palm oil was converted into palm biodiesel via ultrasound-assisted transesterification process at operating conditions of catalyst (KOH) concentration of 0.75 wt%, methanol to oil ratio of 60 V/V %, reaction time of 38 min, reaction temperature of 60 °C and 59% duty cycle. The antioxidant used in biodiesel blends was dimethyl carbonate. These samples were prepared by adding DMC 10% by volume into biodiesel blends at stirring speed of 2000 rpm for 30 min in order to make a homogenous blend. The key fuel properties of the six fuel samples before being engine tested were measured including kinematic viscosity, dynamic viscosity, density, flash point, acid value and calorific value. Engine performance, emission and combustion characteristics were investigated by operating engine at full load condition and varying engine speeds from 1100 rpm to 2100 rpm. Major findings were average increase of 1.70%, 1.22% and 0.95% in BP; average decrease of 1.31%, 2.93% and 1.08% in BSFC; average increase of 4.30%, 4.77% and 4.90% in BTE; average decrease of 2.63%, 2.80% and 4.54% in EGT; significant reduction of 19.04%, 25% and 26.47% in CO emissions; average reduction of 12.76%, 19.35% and 33.33% in HC emissions observed for B10 + DMC, B20 + DMC and B30 + DMC as compared to biodiesel blends without antioxidant.

It is yet unknown what causes cardiovascular disease (CVD), but we do know that it is associated with a high risk of death, as well as severe morbidity and disability. There is an urgent need for AI-based technologies that are able to promptly and reliably predict the future outcomes of individuals who have cardiovascular disease. The Internet of Things (IoT) is serving as a driving force behind the development of CVD prediction. In order to analyse and make predictions based on the data that IoT devices receive, machine learning (ML) is used. Traditional machine learning algorithms are unable to take differences in the data into account and have a low level of accuracy in their model predictions. This research presents a collection of machine learning models that can be used to address this problem. These models take into account the data observation mechanisms and training procedures of a number of different algorithms. In order to verify the efficacy of our strategy, we combined the Heart Dataset with other classification models. The proposed method provides nearly 96 percent of accuracy result than other existing methods and the complete analysis over several metrics has been analysed and provided. Research in the field of deep learning will benefit from additional data from a large number of medical institutions, which may be used for the development of artificial neural network structures.

Liquid fossil fuels are the main source of energy in transportation vehicles and aviation for many decades. This dependence on fossil fuels can be reduced by liquid biofuels blended with fossil fuels or utilized purely. The purpose of this research is to authenticate a method for different fuels for measurement of injection rate based on the spray momentum measurement and total fuel mass injected. So, in this research B50, B100 and simple diesel fuel hydraulic behavior was investigated. All the measurements have been taken in a chamber/cylinder filled with nitrogen gas at high pressure, which results in the gas density of 22.7kg/m3 and 34.6kg/m3, using the injection pressures 600, 800 and 1000 bar. Spray angle and spray tip penetration measurements presented that an increment in injection pressure boosted fuel spray dispersion whereas increment in ambient pressure showed a reverse effect. All fuels have almost same momentum flux for their regarding conditions. B50 and B100 have a greater momentum efficiency than simple Diesel. Momentum flux increases to a factor of almost 1.4 with every 200 bar rise in injection pressure. The fuel mass injected showed a reduction in fuel mass for B50 2–3% and for B100 5–6% as compared to diesel fuel.

Bioplastics are plastics derived from natural resources like corn starch, biomass, sugarcane bagasse, and food waste. Unlike fossil fuel-based plastics, they are bio-degradable entirely or partially. Therefore, bioplastics are relatively less harmful to the environment. Cellulose and starch-based bioplastics are already used for applications like packaging, cutlery, bowls, straws. However, their cost and performance cannot match the conventional plastics. The present study was aimed to produce bioplastic from food waste material. As a result, orange peel is chosen because of its high cellulose content and good availability. The bio-plastic film from orange peel was produced using simple laboratory techniques. Its identification for potential applications is the new area of work. The developed film blends with glycerol as a plasticizer have indicated consistent and promising results. This has excellent strength, flexibility, and disintegration in soiling conditions, morphologically having a rough surface, and confirms the film's bio-degradability nature. Characterization methods such as Fourier transform infrared (FTIR) spectroscopy, Thermal gravimetric analysis (TGA), powderX-ray diffraction (XRD), and Scanning electron microscope (SEM) analysis confirmed that the developed material's physicochemical and surface morphology belonged to bio-based plastic. A simple, novel, and economic process are described in the manufacturing of bio-based plastic.

Alternative fuels are renewable sustainable and address socio-economic and environmental concerns. In this circumstance, this work is conducted in two stages. The first stage of the work involves, the preparation of nanoparticle (NP) blended fuels by adding 20, 40 and 60 ppm of multi-walled carbon nanotube (MWCNT) particles in dairy scum oil methyl ester (DiSOME) biodiesel using a mechanical homogenizer and ultrasonicator. Then, the steadiness characteristics of nanoparticle–mixed biodiesel fuels were studied under static state. In the next stage of the work, the effect of nanofluids on the attributes of combustion and emissions of aengine with 1-cylinder 4-stroke DI-direct injection),CI-compression ignition)which is run on DF-dual-fuel mode using DiSOME and PG-producer gas, has been examined. Investigation results indicated that at 80% load, DiSOME-PG combustion with 40 ppm of MWCNT nanoparticles provided 5.7% increased BTE, 23.5% decreased smoke opacity, 21.8% decreased HC, 22.4% decreased CO and 20.1% amplified NOx emissions related to the same fuel mixer but not with NPs. Adding NPs increased HRR - heat release rate and CP - cylinder pressure.

In the current investigation, the mechanical properties of epoxy composites reinforced with banana pseudostem fibres, specifically focusing on tensile and impact behaviour, are investigated. The manufacturing process employed the meticulous hand-lay-up technique to fabricate six distinct samples. These samples included various combinations of short and woven banana fibres, treated and untreated, as well as a hybrid configuration involving layers of woven and short fibres. A fixed weight ratio of 60% fibres to 40% epoxy matrix was maintained for consistency. To ensure optimal material integrity, a careful application of resin and hardener in a 10 : 1 weight ratio was layered, with each addition of fibre followed by thorough rolling to eliminate any potential bubbles. The density and void fraction of the resulting composites were meticulously assessed to gauge the influence of this layering approach. Additionally, an X-ray diffraction (XRD) analysis was conducted to ascertain the impact of the chemical treatment on the cellulose content of the fibres. Our findings revealed that the tensile and impact properties were notably superior in the woven fibre composites. In particular, the chemically treated woven banana fibre epoxy composite displayed impressive values of 64.95 MPa for tensile strength and 24.37 KJ/m2 for impact strength. To gain deeper insights into the structure-property relationship, test specimens were analyzed using scanning electron micrographs. Lastly, comparative analysis by mapping the tensile properties from our present work with those from existing studies was carried out.

The present research investigates the wear characteristics of an epoxy composite reinforced with a novel Caesalpinia decapetala (CD) shell. The CD is available abundantly worldwide, especially in Ethiopia, particularly in East and West Oromia near West Harar. The composite specimens were processed in the open mould casting technique by varying the vol.% of CD in 10, 20, and 30. EDS is used to evaluate the important elements present in the CD. The density of composites increases with the increase in the content of CD, while the void content estimations reveal good control over the composite fabrication. The wear response of composites is investigated by varying the sliding distance and load and by maintaining a fixed velocity (5 m/s). At a 5 km slide distance and 50 N load, the 30 vol.% Caesalpinia decapetala composition depicts better wear resistance and friction coefficient than other compositions. Experimental results are used to envisage the ideal wear factors and to assess the influence of parameters over the two wear objectives, wear rate and CoF. The grey relational analysis- (GRA-) coupled artificial neural network (ANN) hybrid technique was employed for the prediction and validation. It has been observed that a trivial error of 0.49% amidst GRA and ANN estimation is observed.

There is an increased demand for cement nanocomposites in the twenty-first century due to their composition, higher strength, high efficiency, and multiscale nature. As carbon nanotubes (CNTs) possess extremely high strength, resilience, and stiffness, inclusion of carbon nanotubes in small quantities to the concrete mix makes them a multifunctional material. A molecular level understanding is significant to capacitate the macrolevel properties of these composites. In the proposed work, molecular dynamics (MD) simulations are used to understand the behaviour of the composites at the atomic level and continuum mechanics with representative volume element (RVE) homogenization modelling is carried out for interfacial interaction study of composites. The mechanical properties such as Young’s modulus, shear modulus, and poisons are evaluated using previous methods of simulations for different compositions of nanomaterials in cement matrix. The FORCITE module of MD simulation and square RVE model is used to determine the mechanical, electrical properties, and elastic constants of the cement nanocomposite. The MD simulation describes the linking effect of CNT into cement matric, and the RVE modelling study reveals the pull-out effect of CNT from matrix. From experimental and analytical studies, it is found that increase in CNT till 0.5% weight fraction increases the mechanical properties about 12% and further increasing of CNT weight fraction causes a reduction in mechanical properties about 5% due to the agglomeration of nanotubes. The density of states method in MD simulation indicates that mobility of the electrons increases with an increase in carbon nanotube proportion in the composites. The experimental test results substantiate the analytical studies, and the error obtained from both approaches is less than 20%. From the analytical study, the average maximum Young’s modulus, shear modulus, and bulk modulus are obtained as 46 GPa, 31 GPa, and 32 GPa for 0.5% weight fraction of CNT in cement matrix. Hence, it is concluded that 0.5% weight fraction of CNT is considered as optimum dosage to obtain better electrical and mechanical properties.

This study discusses the acoustic property variations by introducing new absorption materials. An experimental set up established to simulate virtually as well as experimentally with various biodegradable, biocompatible and naturally absorbable materials for a truck cabin of carrier capacity 3.5Tonnes. The materials were embedded on the sidewall and base of the cabin covering the entire cabin not leaving any air pockets. Experimental and simulation study was carried out for six materials and in the later part a combination of these materials also carried out to see through the possible optimal cases providing due Weightage to cost and weight. A sound quality index study being made to see with each case of material how the sound pressure level affects the rider and the subordinates seating in a cabin. A detailed simulation study carried out to understand the material behavioral characteristics along with convergence study using ANSYS Workbench. The exhaustive work emphasis on percentage error study with simulation and experimental work and proposes an optimal material from sound pressure level and rider comfort aspects.

Excessive fuel demand thrusts the Pakistani government to import large volumes of fuel from foreign sources, creating adverse effects on the country’s economy. Therefore, exploring an alternative to fossil fuels is unavoidable. The option of environmentally friendly fuel like biodiesel produced from indigenous waste is an additional bonus for the populous developing country like Pakistan where likelihood of waste generation is huge. There exists a potential option for sustainable biodiesel production utilizing excessive waste cooking oil available in the country which otherwise is an ecological burden. The present work is focused to sturdily vindicate the appropriateness of waste cooking oil-based biodiesel generation and utilization in Pakistan through SWOT-AHP, TOWS and PESTLE analysis. The prioritization of SWOT through AHP in view of experts’ perception displayed the strengths and opportunities in highest group priority values (Strengths: 0.51, Opportunities: 0.29). Furthermore, TOWS analysis suggests promising strategies for the sustainable implementation of commercial aspect of waste oil-based biodiesel in Pakistan. Political, Economic, Social, Technological, Legal and Environmental (PESTLE) analysis favors the strengths and opportunities factors of SWOT and TOWS strategies for the application of waste cooking oil based biodiesel in country. At the end, regional recommendations have been provided for the implementation of biodiesel production scenario in country.

The demand for renewable energy sources is gradually escalating due to the spontaneously growing population and global economic development. The access to fossil fuels is gradually declining due to the limited available reserves. Hence, renewable energy resources, technology choice, and energy policy are always being revised due to the modernization of society. Meanwhile, the liquid energy sources such as methyl ester from locally produced vegetable oils are readily accepted by many countries globally, although it is currently being blended (up to 20%) with diesel. Oxides of nitrogen are the most substantial emissions from diesel engines produced due to high combustion temperature. The addition of alcohol in the fuel reduces the NOxformation since alcohols have high latent heat of evaporation. The present study’s primary purpose is to investigate the effect of different alcohol types on engine performance and emission characteristics. For this purpose, seven test fuels and neat diesel were used. The test fuels P20 (20% palm biodiesel with 70% neat diesel and 10% alcohol on a volume basis), D70P20E10, D70P20Pr10, D70P20B10, D70P20Pe10, D70P20H10 were prepared and tested on a single-cylinder, 4-stroke, DI-diesel engine at different speeds at 100 % load. The P20E10 ternary fuel blend illustrated the most practical combination of all the bioethanol-based blends, which considerably improves the BTE, BSFC and reduces NOxformation at high speed compared to other types of alcoholic fuel blends. Also, the P20E10 fuel blend improved the cloud point of neat diesel.

This study focused on evaluating the lubricity of diesel–biodiesel fuel with oxygenated alcoholic and nano-particle additives. Fuel injection system lubrication depended primarily on the fuel used in the diesel engine. Palm–sesame oil blend was used to produce biodiesel using the ultrasound-assisted technique. B30 fuel sample as a base fuel was blended with fuel additives in different proportions prior to tribological behavior analysis. The lubricity of fuel samples measured using HFRR in accordance with the standard method ASTM D6079. All tested fuels’ Tribological behavior examined through worn steel balls and plates using scanning electron microscopy (SEM) to assess wear scar diameter and surface morphology. During the test run, the friction coefficient was measured directly by the HFRR tribometer system. The results exhibited that B10 (diesel) had a very poor coefficient of friction and wear scar diameter, among other tested fuels. The addition of oxygenated alcohol (ethanol) as a fuel additive in the B30 fuel sample decreased the lubricity of fuel and increased the wear and friction coefficient, among other fuel additives. B30 with DMC showed the least wear scar diameter among all tested fuels. B30 with nanoparticle TiO2exhibited the best results with the least wear scar diameter and lowest friction coefficient among all other fuel samples. B30+DMC demonstrated significant improvement in engine performance (BTE) and carbon emissions compared to different tested samples. B30+TiO2 also showed considerable improvement in engine characteristics.

Dilution of engine oil with unburned fuels alters its lubricity and tribological properties. In this research paper, SAE-40 lubricating oil samples were contaminated with known percentages (5%) of fuels (diesel, palm-sesame biodiesel blend (B30), B30 + ethanol, B30 + dimethyl carbonate, B30 + carbon nanotubes and, B30 + titanium oxide). The effect of all these fuels on wear and frictional characteristics of lubricating oil was determined by using a 4-ball tribo tester and wear types on worn surfaces were analyzed by using SEM. Lubricating oil diluted with B10 (commercial diesel) showed highest COF (42.95%) with severe abrasive and adhesive wear than mineral lubricant among other fuels. Lubricating oil diluted with palm-sesame biodiesel (B30 blend) with alcoholic additives showed comparatively less COF, less wear scar diameter and polishing wear due to presence of ester molecules. Lub + B30 + Eth exhibited increment in COF value (35.81%) compared to SAE-40 mineral lubricant. While lubricating oil contaminated with B30 with nanoparticles showed least frictional characteristics with abrasive wear. Lub + B30 + TiO2 showed least increment in COF value (13.78%) among all other contaminated fuels compared to SAE-40 mineral lubricant. It is concluded that nanoparticles in biodiesel blends (B30) helps in reducing degradation of lubricants than alcoholic fuel additives and commercial diesel.

This experimental study is focused on heat transfer performance and pressure drop characteristics of ZnO/DIW-based nanofluids (NFs) in horizontal mini tubes of different (1.0–2.0 mm) diameters. Different mass concentrations (0.012–0.048 wt %) of nanoparticles (NPs) were tested with varying fluid flow rates (12–24 ml/min) of NFs. The thermal conductivity (TC) and viscosity (VC) of stable NFs were tested at 20–60 ᵒC, at a fixed temperature (40 °C), and concentration of NPs (0.048 wt%) the maximum rise was 18.27% and 20.31%, respectively. The local and average heat transfer coefficients (HTCs) and the pressure gradient were noticed to be directly proportional to volume flow rate of NFs and the mass concentration of NPs. However, an inverse trend was noticed with the test section's diameter. At 0.048 wt % of NPs and 24.0 ml/min flow rate of NFs, the maximum rise in local and average HTCs and pressure gradient was 17.11–11.61% and 13.05–9.79%, and 29.19–12.25%, respectively, in a tube's diameter of 1.0–2.0 mm. The friction factor increased with NP's loading while the same reduced with the fluid flow rate. The corresponding maximum change in the friction factor was 28.85–12.72% for the tubes with 1.0–2.0 mm diameters, respectively, at a 12.0 ml/min flow rate of NFs. The comparison of experimental findings for the HTCs, pressure gradients and friction factors with the standard Shah and Darcy's correlations showed that the observations are in good agreement with the predicted ones.

The improvement in performance has been observed by changing the injector nozzle's geometry of the dual-fuel liquid–gas engine. The combined effect of injector parameters and producer gas (PG) derived from the redgram stalk on the performance and emission characteristics of a dual-fuel diesel/Honge Oil Methyl Ester (HOME)-PG operated CI engine has been studied. The injector nozzles with 4, 5, and 6 holes (diameter of 0.2, 0.25, and 0.3 mm) were analyzed. Diesel-PG operation with 4 holes, 0.25 mm diameter nozzle and HOME-PG operation with 6 holes, 0.25 mm diameter nozzle resulted in better performance and lower emissions. Diesel-PG operation has 4.5% higher BTE (brake thermal efficiency) with a 4 hole nozzle and 0.7% higher for a 0.25 mm diameter 6 holes nozzle than HOME-PG operation. The HOME-PG operation results showed that the with an injection opening pressure of 240 bar, 6-hole nozzle, and a diameter of 0.25 mm have an improved BTE of 5.8% with emission levels 15–30% lower than those of other geometries.

Abstract The main goal of the present work was to develop a value-added product of biodegradable material for sustainable packaging. The use of agriculture waste-derived carboxymethyl cellulose (CMC) mainly is to reduce the cost involved in the development of the film, at present commercially available CMS is costly. The main focus of the research is to translate the agricultural waste-derived CMC to useful biodegradable polymer suitable for packaging material. During this process CMC was extracted from the agricultural waste mainly sugar cane bagasse and the blends were prepared using CMC (waste derived), gelatin, agar and varied concentrations of glycerol; 1.5% (sample A), 2% (sample B), and 2.5% (sample C) was added. Thus, the film derived from the sample C (gelatin + CMC + agar) with 2.0% glycerol as a plasticizer exhibited excellent properties than other samples A and B. The physiochemical properties of each developed biodegradable plastics (sample A, B, C) were characterized using Fourier Transform Infra-Red (FTIR) spectroscopy and Differential Scanning Calorimetry (DSC), Thermogravimetric analysis (TGA). The swelling test, solubility in different solvents, oil permeability coefficient, water permeability (WP), mechanical strength of the produced material was claimed to be a good material for packaging and meanwhile its biodegradability (soil burial method) indicated their environmental compatibility nature and commercial properties. The reflected work is a novel approach, and which is vital in the conversion of organic waste to value-added product development. There is also another way to utilize commercial CMC in preparation of polymeric blends for the packaging material, which can save considerable time involved in the recovery of CMC from sugarcane bagasse.

Vegetable oils have emerged as insulating fluids in transformer applications and as a prominent and effective alternative for traditional dielectric fluids. However, most of vegetable oils are edible causing their application on a large scale to be limited. In the present work, a novel non-edible vegetable oil is developed as an insulating fluid. The developed oil is oxidation-inhibited cottonseed oil (CSO) based nanofluids. Tertiary butylhydroquinone was used as antioxidant. The concept of nanofluids was used to overcome the limited dielectric and thermal properties of cottonseed oil. Hexagonal Boron Nitride (h-BN) nanoparticles at low weight fractions (0.01 - 0.1 wt%) were proposed as nanofillers to achieve adequate dielectric strength and improved thermal conductivity. Stability of prepared CSO based nanofluids was analyzed using Ultraviolet-visible (UV-Vis) spectroscopy. Then, the prepared nanofluids were tested for dielectric and thermal properties under a temperature range between 45 °C and 90 °C. The dielectric properties include breakdown strengths under AC and lightning impulse voltages, dielectric constant, dissipation factor, and resistivity, while thermal properties include thermal conductivity and thermogram analysis. The dielectric and thermal properties were significantly improved in CSO based nanofluids. The creation of electric double layer at nanoparticle/oil interface and the lattice vibration of nanoparticles were used to clarify the obtained results. The proposed CSO based h-BN nanofluids open up a great opportunity in both natural ester insulating fluid applications and thermal energy management systems.

Due to the rapid economic growth and rising Oman population, Oman's annual energy demand has increased by approximately 9%. This percentage signifies that there is a considerable expansion of industries and other manufacturing sectors as the population increases. A study of the energy audit of International Maritime College Oman (IMCO) was conducted to determine the opportunities to save energy efficiency costs, which will be reflected positively in reducing the operational costs of the buildings. In this study, the annual energy consumption of IMCO buildings was simulated using DesignBuilder software. The validation of the simulation results was performed using monthly electricity consumption billing records, with an average of 7.4% during all months. Two strategies were proposed to manage energy consumption: replacing the traditional fluorescent lamp with a LED lamp light control and installing window solar films that are able to control solar heat. The simulation results of the two strategies showed 16% and 7.6% reductions, respectively, in energy consumption. A cost analysis of the findings was performed and showed a payback period of less than 2.5 years for both proposals.

The primary objective of the research was to investigate the ideal resin coating on the mild steel surface among various resin coatings which are in use. These resin coatings are used as an anti-corrosive material for mild steel surfaces with enhanced mechanical properties. The resins (epoxy, polyurethane, polyester, and phenolic) on mild steel surface were applied by the pneumatic spray coating method. In addition, immersion test and salt spray test methods were followed using sodium chloride (NaCl) solution. Furthermore, the rate of corrosion and mechanical properties of mild steel coated with different resins was evaluated by conducting various experiments (immersion test, salt spray test, tensile strength test, and scratch hardness test) and was compared with a bare mild steel surface. The results of the current research showed that the mild steel surface coated with epoxy resin was found to be the most effective corrosion resistance material with better mechanical properties compared to other tested mild steel resin-coated surfaces.

The present experimental examination was carried out to suggest a better fuel blend with an optimised dosage level of alumina nanoparticles (Al2O3)—in a mixture of Fish Oil Methyl Ester (FOME) biodiesel and diesel—and injection pressure, wherein enhanced performance and reduced emissions were obtained via a diesel engine. The aluminium nanoparticles were added to the mixture in 5 mg/l steps through varying concentrations from 5 to 20 mg/L. The experimental results showed that engine performance quietly reduces with increased emission characteristics with the addition of raw FOME biodiesel compared to diesel. Furthermore, the addition of aluminium nanoparticles (Al2O3) improved the performance as well as the emission characteristics of the engine. Among all the test blends, the B40D60A20 blend provided a maximum brake thermal efficiency of 30.7%, which is 15.63% superior to raw FOME and 3.90% inferior to diesel fuel. The blend also showed reduced emissions, for instance, a reduction of 48.38% in CO, 17.51% in HC, 16.52% in NOx, and 20.89% in smoke compared to diesel fuel. Lastly, it was concluded that B40D60A20 at 260 bar is the optimised fuel blend, and 20 mg/l is the recommended dose level of aluminium nanoparticles (Al2O3) in the FOME–diesel mixture biodiesels in order to enhance the performance and emission parameters of a diesel engine.

Whether it is a plant- or animal-based bio-inspiration design, it has always been able to address one or more product/component optimisation issues. Today’s scientists or engineers look to nature for an optimal, economically viable, long-term solution. Similarly, a proposal is made in this current work to use seven different bio-inspired structures for automotive impact resistance. All seven of these structures are derived from plant and animal species and are intended to be tested for compressive loading to achieve load-bearing capacity. The work may even cater to optimisation techniques to solve the real-time problem using algorithm-based generative shape designs built using CATIA V6 in unit dimension. The samples were optimised with Rhino 7 software and then simulated with ANSYS workbench. To carry out the comparative study, an experimental work of bioprinting in fused deposition modelling (3D printing) was carried out. The goal is to compare the results across all formats and choose the best-performing concept. The results were obtained for compressive load, flexural load, and fatigue load conditions, particularly the number of life cycles, safety factor, damage tolerance, and bi-axiality indicator. When compared to previous research, the results are in good agreement. Because of their multifunctional properties combining soft and high stiffness and lightweight properties of novel materials, novel materials have many potential applications in the medical, aerospace, and automotive sectors.

Perovskite solar cells (PSCs) are rapidly emerging as efficient solar cells due to the efficient photovoltaic and physiochemical properties. Ideally, the absorber layer in PSCs is sandwiched between highly conductive electron transport layer (ETL) and highly stable hole transport layer (HTL). The interfaces between these layers highly affect the performance of PSCs. In this study Magnesium (Mg) doped TiO2 based ETL is systematically investigated to enhance the optical and morphological properties of the layer and the interface. It was observed that with Mg doping in mesoporous TiO2, morphology of TiO2 based ETL film was significantly improved thereby providing an interface for the growth of absorber layer. Optoelectronic studies suggested that band gap was effectively reduced with the addition of Mg and absorption range was also enhanced. Electrical analysis yielded, Mg doped TiO2 based ETL showed enhanced conduction and better sheet carrier mobility as compared to undoped films. Thermal studies indicate fabrication of a thermally stable ETL material for PSCs. Moreover, Current density-Voltage (J-V) measurements indicated more than two-fold increase in photovoltaic efficiency of 3 wt% Mg.

In the current study, an effort is carried out to study the influence of pentanol as low reactive fuel (LRF) along with diesel and Thevetia peruviana methyl ester (TPME) as high reactive fuels (HRF) in reactivity controlled compression ignition (RCCI) engine. The experiments are conducted on dual fuel engine at 50% load for RCCI mode of operation by varying pentanol percentage in injected fuels. The results revealed that RCCI mode of operation at 10% of pentanol in injected fuels exhibited higher brake thermal efficiency (BTE) of 22.15% for diesel and pentanol fuel combination, which is about 9.1% and 27.3% higher than other B20 and pentanol, B100 and pentanol fuel combinations respectively. As the percentage of pentanol increased in injected fuels, hydrocarbon (HC) and carbon monoxide (CO) emissions are increased while nitrogen oxide (NOx) and smoke emissions are decreased. Among various fuel combinations tested diesel and pentanol fuel combination gives lower HC, CO and smoke emissions and higher NOx emissions. At 10% pentanol in injected fuels, the highest heat release rate (HRR) and in-cylinder pressure are found for diesel and pentanol fuel combinations compared with other fuels.

Environmental concerns have urged a search for eco-friendly refrigerants in the refrigeration industry to overcome ozone depletion and global warming problems. Therefore, current research emphasizes frictional pressure drop during flow boiling of environment-friendly refrigerants (GWP

The aim of the present work is the synthesis and characterization of iron oxide (Fe3O4) nanoparticles. These nanoparticles are coated with oleic acid and polyvinyl butyral and mixed with microspheres and further developed ferrofluids with silicon oil. Studies of the performance of the nanoparticles in these ferrofluids with and without coating agents were carried out. The nanoparticles were synthesized using the chemical co-precipitation technique and coated with oleic acid and polyvinyl butyral, and it further mixed with microsphere ferrofluids and developed using silicon oil. The prepared Fe3O4 nanoparticles and their coated forms of oleic acid and polyvinyl butyral were mixed with microspheres; furthermore, ferrofluids were developed with silicon oil. All forms of these ferrofluids are characterized for morphology and phase purity (SEM, XRD, and FTIR). The iron oxide (Fe3O4) nanoparticles have shown different magnetic properties, differentiating macroscopic iron oxide in suspended particles. The ratio of surface to volume increases along with the decrease in atomic size, essential for assessing the surface morphological properties. The magneto-rheological (MR) fluids were determined, and shear stress of Expancel microsphere mixed iron oxide nanoparticle with and without them was found almost equal. However, the ferrofluid with PVB coated nanoparticles and microspheres emerged as a stable rheological ferrofluid, sustaining high shear stress and low viscosity with increasing shear rate. Also, shear rates up to 650 s−1 have been observed, showing very high shear stress withstanding capacity. The stability and performance of the magnetic colloidal ferrofluids depend on the thermal contribution and the balance between attractive/repulsive interactions.

As a promising renewable fuel, biodiesel has gained worldwide attention to replace fossil-derived mineral diesel due to the threats concerning the depletion of fossil reserves and ecological constraints. Biodiesel production via transesterification involves using homogeneous, heterogeneous and enzymatic catalysts to speed up the reaction. The usage of heterogeneous catalysts over homogeneous catalysts are considered more advantageous and cost-effective. Therefore, several heterogeneous catalysts have been developed from variable sources to make the overall production process economical. After achieving optimum performance of these catalysts and chemical processes, the research has been directed in other perspectives, such as the application of non-conventional methods such as microwave, ultrasonic, plasma heating etc, aiming to enhance the efficiency of the overall process. This mini review is targeted to focus on the research carried out up to this date on microwave-supported heterogeneously catalysed biodiesel production. It discusses the phenomenon of microwave heating, synthesis techniques for heterogeneous catalysts, microwave mediated transesterification reaction using solid catalysts, special thermal effects of microwaves and parametric optimisation under microwave heating. The review shows that using microwave technology on the heterogeneously catalysed transesterification process greatly decreases reaction times (5–60 min) while maintaining or improving catalytic activity (>90%) when compared to traditional heating.

An existing diesel engine was fitted with a common rail direct injection (CRDi) facility to inject fuel at higher pressure in CRDi mode. In the current work, rotating blades were incorporated in the piston cavity to enhance turbulence. Pilot fuels used are diesel and biodiesel of Ceiba pentandra oil (BCPO) with hydrogen supply during the suction stroke. Performance evaluation and emission tests for CRDi mode were carried out under different loading conditions. In the first part of the work, maximum possible hydrogen substitution without knocking was reported at an injection timing of 15° before top dead center (bTDC). In the second part of the work, fuel injection pressure (IP) was varied with maximum hydrogen fuel substitution. Then, in the third part of the work, exhaust gas recirculation (EGR), was varied to study the nitrogen oxides (NOx) generated. At 900 bar, HC emissions in the CRDi engine were reduced by 18.5% and CO emissions were reduced by 17% relative to the CI mode. NOx emissions from the CRDi engine were decreased by 28% relative to the CI engine mode. At 20%, EGR lowered the BTE by 14.2% and reduced hydrocarbons, nitrogen oxide and carbon monoxide by 6.3%, 30.5% and 9%, respectively, compared to the CI mode of operation.

A set of lab-scale experiments were designed and conducted to remedy Direct Blue 15 (DB15) dye using nontoxic halloysite nanotubes (HNT) with the view to be utilized in a textile industrial effluent (TIE). The DB15 adsorbed-HNT “sludge” was used as a reinforcing agent and plastic waste to fabricate the composite. To advance the knowledge and further understand the chemical phenomena associated with DB15 adsorption on HNT, different factors like pH value, adsorbate initial concentration, adsorbent dosage, and temperature on the composite were affected experimentally tested. To estimate the adsorption capacity of HNT, nine isotherm models were applied, and it was identified that the Brouers–Sotolongo adsorption isotherm model represented the best accuracy for predicting the adsorption behavior of the HNT. Likewise, the pseudo-second-order reaction was the predominant mechanism for the overall rate of the multi-step dye adsorption process. Additionally, it was demonstrated that the mass transfer during the process is diffusion-controlled, and thermodynamic assessments showed that the process is physisorption.