Experimental Analysis for the Performance Assessment and Characteristics of Enhanced Magnesium Composites Reinforced with Nano-Sized Silicon Carbide Developed Using Powder Metallurgy.

Magnesium, which is lightweight and abundant by nature, was widely used in the 19th century to make parts for automobiles and airplanes. Due to their superior strength-to-weight ratios, magnesium alloys were favored for engineering applications over unadulterated magnesium. These alloys result from the combination of magnesium with various metals, including aluminum (Al), titanium (Ti), zinc (Zn), manganese (Mn), calcium (Ca), lithium (Li), and zirconium (Zr). In this study, an alloy of magnesium was created using the powder metallurgy (PM) technique, and its optimal performance was determined through the Taguchi-Gray (TG) analysis method. To enhance the alloy's mechanical properties, diverse weight fractions of silicon carbide (SiC) were introduced. The study primarily focused on the Mg-Zn-Cu-Mn alloy, achieving the optimal composition of Mg-3Zn-1Cu-0.7Mn (ZC-31). Subsequently, composites of ZC-31/SiC were produced via PM and the hot extrusion (HE) process, followed by the assessment of the mechanical properties under various strain rates. The use of silicon carbide (SiC) resulted in enhanced composite densities as a consequence of the increased density exhibited by SiC particles. In addition, the high-energy postsintering approach resulted in a decrease in porosity levels. By integrating silicon carbide (SiC) to boost the microhardness, as well as the ultimate compressive and tensile strength of the composite material, we can observe significant improvements in these mechanical properties. The experimental findings also demonstrated that an augmentation in the weight fraction of SiC and the strain rate led to enhanced ductility and a shift toward a more transcrystalline fracture behavior inside the composite material.

Investigation on effect of cerium oxide additive in waste plastic oil fueled CI engine.

In this study, the effects of incorporating cerium oxide into diesel and WPO blends were investigated to determine the potential of the blend as a fuel additive. The study aimed to assess engine-performance, emission, and combustion properties of the blend. The experiments utilized a single-cylinder diesel engine, and researchers prepared two different blends of WPO with 25% WPO in diesel and 50% WPO in diesel. Cerium oxide was added to these blends at concentrations of 25 ppm and 50 ppm using an ultrasonicator. The results demonstrated that increasing cerium oxide content in the blend (50 ppm) led to reduced CO, HC, and NOx emissions at higher loads. For instance, B50 + 50 ppm exhibited lower CO and NOx emissions, while B25 + 50 ppm demonstrated lower HC and smoke emissions. Furthermore, raising the CeO2 content from 25 ppm to 50 ppm resulted in a 3% increase in brake thermal efficiency. Moreover, cerium oxide positively impacted combustion and performance properties of the blends. Among the tested blends, the B50 + 50 ppm combination showcased the highest brake thermal efficiency, optimal air-fuel ratio, and the lowest specific fuel consumption. In conclusion, employing cerium oxide as a fuel additive in diesel-WPO blends offers a promising approach for realizing a sustainable and environmentally friendly future.

A comprehensive analysis of the emerging modern trends in research on photovoltaic systems and desalination in the era of artificial intelligence and machine learning.

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.

Polyethylene microplastic can adsorb phosphate but is unlikely to limit its availability in soil.

In plant growth experiments, the presence of microplastics (MPs) often reduces plant growth. We conducted laboratory experiments to investigate the potential of microplastics to adsorb the major soil nutrient phosphate; adsorption to MPs was then compared to adsorption to soil. Adsorption experiments used two contrasting soils, pristine high density polyethylene and artificially weathered material (the same material but exposed to 185 nm UV light for 420 h over 105 days), phosphate solutions (dissolved KH2PO4) ranging from 0.2 to 200 mg L-1 and a solid (g) to liquid (mL) ratio of 1: 150 at different values of pH (2-12) and different concentrations of background electrolyte (0.00-0.10 M NaNO3). The adsorption data were best fitted to linear and Freundlich isotherms. In initial experiments where pH was not fixed and with a background electrolyte of 0.10 M NaNO3, Kd values ranged from 3.37 to 27.65 L kg-1, log Kf from 1.21 to 1.96 and 1/n from 0.36 to 0.84. Exposure of the MP to 185 nm UV radiation led to the appearance of a C=O functional group in the MP; the partition coefficient Kd, calculated from the linear isotherm did not increase but the logKf value derived from fits to the Freundlich isotherm increased by a factor of 1.5. Kd values for soils were 3-7.5 times greater than those for MPs and log Kf values 1.1-1.7 greater. In the experiments in which initial pH and ionic strength were varied, adsorption was similar across all treatments with adsorption parameters for the higher organic content soil sometimes having the highest values and the pristine microplastic the lowest. In the desorption experiments most of the adsorbed phosphate desorbed. Overall our findings indicate that despite their ability to adsorb phosphate, MPs are unlikely to control the fate and behaviour of phosphate in soil.

Advances in identifying and managing emerging contaminants in aquatic ecosystems: Analytical approaches, toxicity assessment, transformation pathways, environmental fate, and remediation strategies.

Emerging contaminants (ECs) are increasingly recognized as threats to human health and ecosystems. This review evaluates advanced analytical methods, particularly mass spectrometry, for detecting ECs and understanding their toxicity, transformation pathways, and environmental distribution. Our findings underscore the reliability of current techniques and the potential of upcoming methods. The adverse effects of ECs on aquatic life necessitate both in vitro and in vivo toxicity assessments. Evaluating the distribution and degradation of ECs reveals that they undergo physical, chemical, and biological transformations. Remediation strategies such as advanced oxidation, adsorption, and membrane bioreactors effectively treat EC-contaminated waters, with combinations of these techniques showing the highest efficacy. To minimize the impact of ECs, a proactive approach involving monitoring, regulations, and public education is vital. Future research should prioritize the refining of detection methods and formulation of robust policies for EC management.

Study of some morphometric and meristic characteristics of Alepes vari (Cuvier, 1833) collected from the Arabian coast / Estudo de características morfométricas e merísticas de Alepes vari (Cuvier, 1833) coletados na costa da Arábia

The present study examines the correlations between fifteen morphometric and ten meristic characters and total length (TL) of males, females, and combined sexes of Alepes vari (Cuvier, 1833) collected from Karachi fish harbor, West Wharf of Karachi Coast. Statistical analyses of linear regression relationships show mostly strong correlations (r≥0.70; p<0.05) between total length (TL) and most morphometric characters in males, females, and combined sexes, except the height of pectoral-fin (PFH), and pelvic-fin base length (PelFL); whereas, meristic characters were found to be constant and indicate weak or negative type correlations (r≤0.50; p>0.05) with total length (TL). Hence, according to our present results, there is a direct relationship between the total length of fish and all morphometric characters, which were found to be the best indicators of positive allometric pattern growth in fish. Moreover, analysis of the 2-sample t-test revealed (t-test; p>0.05) that no sexual dimorphism was reported in Alepes vari. Thus, our present study could be valuable in systematic classification, sexual dimorphism, and management of this species on the Karachi coast.

O presente estudo examina as correlações entre 15 caracteres morfométricos e 10 caracteres merísticos e comprimento total (CT) de machos, fêmeas e sexos combinados de Alepes vari (Cuvier, 1833), coletados do porto de Karachi, West Wharf, na costa de Karachi. As análises estatísticas das relações de regressão linear mostraram, principalmente, correlações fortes (r ≥ 0,70; p < 0,05) entre o CT e a maioria dos caracteres morfométricos em machos, fêmeas e sexos combinados, exceto a altura da nadadeira peitoral e o comprimento da base da nadadeira pélvica, enquanto os caracteres merísticos foram constantes, indicando correlações fracas ou negativas (r ≤ 0,50; p > 0,05) com o CT. Portanto, de acordo com nossos resultados, existe uma relação direta entre o CT dos peixes e todos os caracteres morfométricos, que foram considerados os melhores indicadores de crescimento do padrão alométrico positivo em peixes. Além disso, a análise do teste t de duas amostras revelou (teste t; p > 0,05) que nenhum dimorfismo sexual foi relatado em A. vari.

Study of some morphometric and meristic characteristics of Alepes vari (Cuvier, 1833) collected from the Arabian coast

Abstract The present study examines the correlations between fifteen morphometric and ten meristic characters and total length (TL) of males, females, and combined sexes of Alepes vari (Cuvier, 1833) collected from Karachi fish harbor, West Wharf of Karachi Coast. Statistical analyses of linear regression relationships show mostly strong correlations (r0.70; p 0.05) between total length (TL) and most morphometric characters in males, females, and combined sexes, except the height of pectoral-fin (PFH), and pelvic-fin base length (PelFL); whereas, meristic characters were found to be constant and indicate weak or negative type correlations (r0.50; p>0.05) with total length (TL). Hence, according to our present results, there is a direct relationship between the total length of fish and all morphometric characters, which were found to be the best indicators of positive allometric pattern growth in fish. Moreover, analysis of the 2-sample t-test revealed (t-test; p>0.05) that no sexual dimorphism was reported in Alepes vari. Thus, our present study could be valuable in systematic classification, sexual dimorphism, and management of this species on the Karachi coast.

Resumo O presente estudo examina as correlações entre 15 caracteres morfométricos e 10 caracteres merísticos e comprimento total (CT) de machos, fêmeas e sexos combinados de Alepes vari (Cuvier, 1833), coletados do porto de Karachi, West Wharf, na costa de Karachi. As análises estatísticas das relações de regressão linear mostraram, principalmente, correlações fortes (r 0,70; p 0,05) entre o CT e a maioria dos caracteres morfométricos em machos, fêmeas e sexos combinados, exceto a altura da nadadeira peitoral e o comprimento da base da nadadeira pélvica, enquanto os caracteres merísticos foram constantes, indicando correlações fracas ou negativas (r 0,50; p > 0,05) com o CT. Portanto, de acordo com nossos resultados, existe uma relação direta entre o CT dos peixes e todos os caracteres morfométricos, que foram considerados os melhores indicadores de crescimento do padrão alométrico positivo em peixes. Além disso, a análise do teste t de duas amostras revelou (teste t; p > 0,05) que nenhum dimorfismo sexual foi relatado em A. vari. Assim, o presente estudo pode ser valioso na classificação sistemática, dimorfismo sexual e manejo dessa espécie na costa de Karachi.

Exploring the Impact of Al2O3 Additives in Gasoline on HCCI-DI Engine Performance: An Experimental, Neural Network, and Regression Analysis Approach.

This study delves into the influence of incorporating alumina (Al2O3) nanoparticles with waste cooking oil (WCO) biofuels in a gasoline engine that employs premixed fuel. During the suction phase, gasoline blends with atmospheric air homogeneously at the location of the inlet manifold. The biodiesel, enhanced with Al2O3 nanoparticles and derived from WCO, is subsequently directly infused into the combustion chamber at 23° before the top dead center. The results highlight that when gasoline operates in the homogeneous charge compression ignition with direct injection (HCCI-DI) mode, there is a notable enhancement in thermal efficiency by 4.23% in comparison to standard diesel combustion. Incorporating the Al2O3 nanoparticles with the WCO biodiesel contributes to an extra rise of 6.76% in thermal efficiency. Additionally, HCCI-DI combustion paves the way for a reduction in nitrogen oxides and smoke emissions, whereas biodiesel laced with Al2O3 nanoparticles notably reduces hydrocarbon and carbon monoxide discharges. Predictive tools such as artificial neural networks and regression modeling were employed to forecast engine performance variables.

Mechanical and Wear Studies of Boron Nitride-Reinforced Polymer Composites Developed via 3D Printing Technology.

In the realm of 3D printing, polymers serve as fundamental materials offering versatility to cater to a diverse array of final product properties and tailored to the specific needs of the creator. Polymers, as the building blocks of 3D printing, inherently possess certain mechanical and wear properties that may fall short of ideal. To address this limitation, the practice of reinforcing polymer matrices with suitable materials has become a common approach. One such reinforcement material is boron nitride (BN), lauded for its remarkable mechanical attributes. The integration of BN as a reinforcing element has yielded substantial enhancements in the properties of polylactic acid (PLA). The central objective of this research endeavor is the development of polymer composites based on PLA and fortified with boron nitride. This study undertakes the comprehensive exploration of the compatibility and synergy between BN and PLA with a keen focus on examining their resultant properties. To facilitate this, various percentages of boron nitride were incorporated into the PLA matrix, specifically at 5% and 10% by weight. The compounding process involved the blending of PLA and boron nitride followed by the creation of composite filaments measuring 1.75 mm in diameter and optimized for 3D printing. Subsequently, test specimens were meticulously fabricated in adherence with ASTM standards to evaluate the ultimate tensile strength, dimensional accuracy, wear characteristics, and surface roughness. The findings from these assessments were systematically compared to the wear properties and mechanical behavior of PLA composites reinforced with boron nitride and the unreinforced PLA material. This study serves as a foundational resource that offers insights into the feasibility and methodologies of incorporating boron nitride into PLA matrices, paving the way for enhanced polymer composite development.

Influence of Alloying Materials Al, Cu, and Ca on Microstructures, Mechanical Properties, And Corrosion Resistance of Mg Alloys for Industrial Applications: A Review.

Magnesium is renowned for its favorable low-density attributes, rendering it a viable choice for commercial engineering applications in which weight has substantial design implications. Magnesium (Mg) stands as a readily obtainable metallic element, exhibiting robustness, efficient heat dissipation, and excellent damping properties. The utilization of pure magnesium remains infrequent due to its susceptibility to instability under high temperatures and pronounced vulnerability to corrosion within humid environments. Hence, the incorporation of magnesium alloys into the design process of aircraft, automotive, and biomedical applications assumes paramount importance. This Review presents a comprehensive review of research endeavors and their resultant achievements concerning the advancement of magnesium alloys. Specifically focusing on aerospace, automotive, and biomedical applications, the Review underscores the pivotal role played by alloying constituents, namely aluminum (Al), copper (Cu), calcium (Ca), and PEO coatings, in influencing the microstructural attributes, mechanical potency, and resistance to corrosion.

Effect of silicon carbide on kerf convergence and irregularity of the surface during abrasive water jet machining of fiber-metal hybrid composites.

The traditional way to machine hybrid composites is hard because they tend to break, have a high retraction, have a high service temperature, and have an uneven surface irregularity. For high-strength fiber/metal composite constructions, alternative machining methods have drawn interest as a solution to these problems. Current research focuses on enhancing the Abrasive Water Jet Machining process by optimizing its variables using a composite material of epoxy reinforced with silicon carbide, stainless steel wire mesh, and Kevlar. The variables assessed are the Nozzle-to-substrate gap (S), the Abrasive discharge molding and different percentages of silicon carbide (SiC) filler (0%, 3%, and 6% by weight), three different types of hybrid laminates (H1, H2, and H3) were produced. The response surface method (RSM) was utilized in this learning, specifically on a central composite design, to calculate and optimize machining variables based on the Kerf convergence ratio (Kt) and Surface irregularity (Ra) as responses. According to the results, the traverse feed velocity, Abrasive discharge proportion, and Nozzle-to-substrate gap are the critical factors in determining Surface irregularity and Kerf convergence width (H1 laminate) for a fiber/metal laminate with 0%, 3% and 6% weight fraction. In the case of a 3% weight fraction H2 laminate, the traverse feed velocity was identified as the primary factor affecting the Kerf convergence ratio. In contrast, traverse feed velocity and Nozzle-to-substrate gap had the most significant influence on Surface irregularity. The findings also indicated that S, followed by Abrasive discharge proportion and traverse feed velocity, are the variables that have the most significant influence when cutting 6 wt% SiC filler particle fiber/metal laminate (H3 laminate). For Surface irregularity, the combination of traverse feed velocity and Nozzle-to-substrate gap had the most significant impact. To validate the optimization results, confirmatory tests was conducted, and the findings were very similar to the experimental values, indicating the accuracy and effectiveness of the optimization process. To better understand the manufacturing processes, a scanning electron microscope was used to examine the morphological features of the machined surfaces, such as delamination, fibre breakage, and fibre pull-out.

Response surface methodology based optimization of keratinase from Bacillus velezensis strain ZBE1 and nanoparticle synthesis, biological and molecular characterization.

The increasing demands of keratinases for biodegradation of recalcitrant keratinaceous waste like chicken feathers has lead to research on newer potential bacterial keratinases to produce high-value products with biological activities. The present study reports a novel keratinolytic bacterium Bacillus velezensis strain ZBE1 isolated from deep forest soil of Western Ghats of Karnataka, which possessed efficient feather keratin degradation capability and induced keratinase production. Production kinetics depicts maximum keratinase production (11.65 U/mL) on 4th day with protein concentration of 0.61 mg/mL. Effect of various physico-chemical factors such as, inoculum size, metal ions, carbon and nitrogen sources, pH and temperature influencing keratinase production were optimized and 3.74 folds enhancement was evidenced through response surface methodology. Silver (AgNP) and zinc oxide (ZnONP) nanoparticles with keratin hydrolysate produced from chicken feathers by the action of keratinase were synthesized and verified with UV-Visible spectroscopy that revealed biological activities like, antibacterial action against Bacillus cereus and Escherichia coli. AgNP and ZnONP also showed potential antioxidant activities through radical scavenging activities by ABTS and DPPH. AgNP and ZnONP revealed cytotoxic effect against MCF-7 breast cancer cell lines with IC50 of 5.47 µg/ml and 62.26 µg/ml respectively. Characterizations of nanoparticles were carried out by Fourier transform infrared spectroscopy, scanning electron microscopy with energy dispersive X-ray, X-ray diffraction, thermogravimetric analysis and atomic force microscopy analysis to elucidate the thermostability, structure and surface attributes. The study suggests the prospective applications of keratinase to trigger the production of bioactive value-added products and significant application in nanotechnology in biomedicine.

Optimization of subtilisin production from Bacillus subtilis strain ZK3 and biological and molecular characterization of synthesized subtilisin capped nanoparticles.

The increase and dissemination of multi-drug resistant bacteria have presented a major healthcare challenge, making bacterial infections a significant concern. The present research contributes towards the production of bioactive subtilisin from a marine soil isolate Bacillus subtilis strain ZK3. Custard apple seed powder (raw carbon) and mustard oil cake (raw nitrogen) sources showed a pronounced effect on subtilisin production. A 7.67-fold enhancement in the production was evidenced after optimization with central composite design-response surface methodology. Subtilisin capped silver (AgNP) and zinc oxide (ZnONP) nanoparticles were synthesized and characterized by UV-Visible spectroscopy. Subtilisin and its respective nanoparticles revealed significant biological properties such as, antibacterial activity against all tested pathogenic strains with potential against Escherichia coli and Pseudomonas aeruginosa. Prospective antioxidant behavior of subtilisin, AgNP and ZnONP was evidenced through radical scavenging assays with ABTS and DPPH. Subtilisin, AgNP and ZnONP revealed cytotoxic effect against cancerous breast cell lines MCF-7 with IC50of 83.48, 3.62 and 7.57 µg/mL respectively. Characterizations of nanoparticles were carried out by Fourier transform infrared spectroscopy, scanning electron microscopy with energy dispersive X-ray, X-ray diffraction, thermogravimetric analysis and atomic force microscopy analysis to elucidate the structure, surface and thermostability properties. The study proposes the potential therapeutic applications of subtilisin and its nanoparticles, a way forward for further exploration in the field of healthcare.

Distribution of Carbon Nanotubes in an Aluminum Matrix by a Solution-Mixing Process.

In order to overcome the limitations of standard ball-mill mixing processes to fabricate a uniformly dispersed carbon nanotube (CNT) reinforcement composite without damaging CNTs in matrix powder, a unique and easy solution-mixing process was developed. The present study aims to synthesize Al-0.5 wt % CNT composites using ball-milling and solution-mixing processes and compares their CNT dispersion and structural and thermal properties. Compared with the ball-milling process, the solution-mixing process was simple and effective for the uniform distribution of CNTs without structural damage. Various methods were utilized to examine the structural characteristics of the composite powder. These techniques included high-resolution transmission electron microscopy (HRTEM), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Raman spectroscopy, and particle size analysis. Raman spectroscopy observes an increase of defects in ball-milled composites, and the particle size analyzer confirms the structural deformation, resulting in the degradation of composite powder mechanical properties. In the solution-mixing process, aluminum particles and the structure of CNTs are well-preserved even after mixing. Thermogravimetric analysis (TGA) was used to research the thermal stability of the composite materials. The results validated the impact of CNTs on thermal characteristics enhancement (improved thermal resistance) when compared with pure aluminum, suggesting potential uses in the aerospace industry, transport, and construction sectors.

Iron pill aspiration syndrome: A case report and literature review.

Aspiration of iron pill containing ferrous sulfate into the airway can induce fulminant chemical burn and necrosis of the airway mucosa. Acute chemical burn and inflammatory response can result in life-threatening airway compromise. It can also result in long-term sequelae including but not limited to fibrosis and airway stenosis. Considering the common use of iron supplements, and the potential severity of aspiration related airway injury, clinicians should be fully cognizant of the interaction between aspirated iron and airway passages. Herein, we present a case report with pertinent review of the literature.

Molecular dynamics and simulation analysis against superoxide dismutase (SOD) target of Micrococcus luteus with secondary metabolites from Bacillus licheniformis recognized by genome mining approach.

Micrococcus luteus, also known as M. luteus, is a bacterium that inhabits mucous membranes, human skin, and various environmental sources. It is commonly linked to infections, especially among individuals who have compromised immune systems. M. luteus is capable of synthesizing the enzyme superoxide dismutase (SOD) as a component of its protective response to reactive oxygen species (ROS). This enzyme serves as a promising target for drug development in various diseases. The current study utilized a subtractive genomics approach to identify potential therapeutic targets from M. luteus. Additionally, genome mining was employed to identify and characterize the biosynthetic gene clusters (BGCs) responsible for the production of secondary metabolites in Bacillus licheniformis (B. licheniformis), a bacterium known for its production of therapeutically relevant secondary metabolites. Subtractive genomics resulted in identification of important extracellular protein SOD as a drug target that plays a crucial role in shielding cells from damage caused by ROS. Genome mining resulted in identification of five potential ligands (secondary metabolites) from B. licheniformis such as, Bacillibactin (BAC), Paenibactin (PAE), Fengycin (FEN), Surfactin (SUR) and Lichenysin (LIC). Molecular docking was used to predict and analyze the binding interactions between these five ligands and target protein SOD. The resulting protein-ligand complexes were further analyzed for their motions and interactions of atoms and molecules over 250 ns using molecular dynamics (MD) simulation analysis. The analysis of MD simulations suggests, Bacillibactin as the probable candidate to arrest the activities of SOD. All the five compounds reported in this study were found to act by directly/indirectly interacting with ROS molecules, such as superoxide radicals (O2-) and hydrogen peroxide (H2O2), and transforming them into less reactive species. This antioxidant activity contributes to its protective effects against oxidative stress-induced damage in cells making them likely candidate for various applications, including in the development of antioxidant-based therapies, nutraceuticals, and functional foods.

Studies on Evaluation of the Thermal Conductivity of Alumina Titania Hybrid Suspension Nanofluids for Enhanced Heat Transfer Applications.

Extensive investigations were made and empirical relations were proposed for the thermal conductivity of mono-nanofluids. The effect of concentration, diameter, and thermal properties of participating nanoparticles is missing in the majority of existing thermal conductivity models. An attempt is made to propose a model that considers the influence of such missing parameters on the thermal conductivity of hybrid nanofluids. Al2O3-TiO2 hybrid nanofluids have a 0.1% particle volume concentration prepared with distinct particle volume ratios (k - 1:6 - k, k = 1 to 6) in DI water. The samples were characterized, and the size and shape of the nanoparticles were verified. Also, the influence of varying particle volume ratios and the fluid temperature (varying from 283 to 308 K) were examined. 2.4 and 2.1% enhancements were observed in the thermal conductivity of alumina (5:0) and titania (0:5) nanofluids (having 0.1% volume concentration), respectively. Due to the low thermal conductivity of titania nanoparticles, the conductivity of the hybrid solution is above that of titania and below that of alumina nanofluids. An empirical relation for the thermal conductivity of hybrid nanofluids is established and validated considering the individual particle size, volume ratio, and thermal conductivity of particles.

Utilization of additives in biodiesel blends for improving the diesel engine performance and minimizing emissions through a modified Taguchi approach.

Biodiesel from Jatropha oil is produced through catalyzed homogeneous transesterification. Hydrogen peroxide (H2O2) is considered as additive. Blends of Jatropha considered in the present study are 60% diesel, (40-A)% biodiesel and A% additive, varying A from 0 to 10. Identifying optimal input variables (such as additive volume percentage, injection pressure, and load) is important for improving the engine performance and reducing emissions. Air-fuel ratio; brake specific fuel consumption (BSFC); and brake thermal efficiency (BTE) are the engine performance characteristics. Carbon monoxide (CO); carbon dioxide (CO2); exhaust gas temperature (EGT); nitrogen oxide (NOx); and smoke opacity are the emission characteristics. 27 experiments need to be performed for the assigned 3 levels and 3 input variables. The Taguchi's L9 orthogonal array (OA) is chosen to perform only 9 experiments to obtain the optimal solution. The expected range of performance characteristics and emissions was obtained following a modified Taguchi approach. Empirical relationships are developed and verified through engine performance and emission characteristics.

Advancements in algal membrane bioreactors: Overcoming obstacles and harnessing potential for eliminating hazardous pollutants from wastewater.

This paper offers a comprehensive analysis of algal-based membrane bioreactors (AMBRs) and their potential for removing hazardous and toxic contaminants from wastewater. Through an identification of contaminant types and sources, as well as an explanation of AMBR operating principles, this study sheds light on the promising capabilities of AMBRs in eliminating pollutants like nitrogen, phosphorus, and organic matter, while generating valuable biomass and energy. However, challenges and limitations, such as the need for process optimization and the risk of algal-bacterial imbalance, have been identified. To overcome these obstacles, strategies like mixed cultures and bioaugmentation techniques have been proposed. Furthermore, this study explores the wider applications of AMBRs beyond wastewater treatment, including the production of value-added products and the removal of emerging contaminants. The findings underscore the significance of factors such as appropriate algal-bacterial consortia selection, hydraulic and organic loading rate optimization, and environmental factor control for the success of AMBRs. A comprehensive understanding of these challenges and opportunities can pave the way for more efficient and effective wastewater treatment processes, which are crucial for safeguarding public health and the environment.