Sargassum myriocystum-mediated TiO2-nanoparticles and their antimicrobial, larvicidal activities and enhanced photocatalytic degradation of various dyes.

Recently, the phyco-synthesis of nanoparticles has been applied as a reliable approach to modern research field, and it has yielded a wide spectrum of diverse uses in fields such as biological science and environmental science. This study used marine natural resource seaweed Sargassum myriocystum due to their unique phytochemicals and their significant attributes in giving effective response on various biomedical applications. The response is created by their stress-tolerant environmental adaptations. This inspired us to make an attempt using the above-mentioned charactersitics. Therfore, the current study performed phycosynthesis of titanium dioxide nanoparticles (TiO2-NPs) utilising aqueous extracts of S. myriocystum. The TiO2-NPs formation was confirmed in earlier UV-visible spectroscopy analysis. The crystalline structure, functional groups (phycomolecules), particle morphology (cubic, square, and spherical), size (∼50-90 nm), and surface charge (negative) of the TiO2-NPs were analysed and confirmed by various characterisation analyses. In addition, the seaweed-mediated TiO2-NPs was investigated, which showed potential impacts on antibacterial activity and anti-biofilm actions against pathogens (Staphylococcus aureus, S. epidermidis, Escherichia coli, Proteus vulgaris, Pseudomonas aeruginosa, and Klebsiella pneumoniae). Additionally, some evaluations were performed on larvicidal activities of TiO2-NPs in oppose to Aedes aegypti and Culex quinquefasciatus mosquitos and the environmental effects of photocatalytic activities against methylene blue and crystal violet under sunlight irradiation. The highest percent of methylene blue degradation was observed at 92.92% within 45 min. Overall, our findings suggested that S. myriocystum mediates TiO2-NPs to be a potent disruptive material for bacterial pathogens and mosquito larvae and also to enhance the photocatalytic dye degradation.

Enhancing performance and sustainability of GGBFS-based self-compacting geopolymer concrete blended with coal bottom ash and metakaolin by using RSM modelling.

This research study is performed on the self-compacting geopolymer concrete (SCGC) combining coal bottom ash (CBA) and metakaolin (MK) as a substitution for GGBFS alone and combined for analysing the fresh properties (slump flow, V-Funnel, and T50 flow), mechanical characteristics (compressive, splitting tensile and flexural strengths) and durability tests (permeability and sulfate attack test). Though, total 195 SCGC samples were made and tested for 28 days. It has been revealed that the consumption of CBA and MK as a substitution for GGBFS alone and combine in the production of SCGC is decreased the workability of SCGC while mechanical characteristics of SCGC are enhanced by utilizing CBA and MK as a substitution for GGBFS alone and combine up to 10%. In addition, the compressive, splitting tensile and flexural strengths were calculated by 59.40 MPa, 5.68 MPa, and 6.12 MPa while using the 5CBA5MK as a substitution for GGBFS in the production of SCGC after 28 days correspondingly. Furthermore, the permeability is decreased by growing the quantity of CBA and MK by the weight of GGBFS alone and jointly in the production of SCGC after 28 days. Besides, the minimum change in length of the SCGC specimen is recorded by 0.062 mm at 7.5MK7.5CBA while the maximum change in length is calculated by 0.11 mm at 10CBA10MK as a substitution for GGBFS at 180 days correspondingly. In addition, the embodied carbon is recorded reduce as the addition of CBA while it is getting higher when the accumulation of MK alone or combined with CBA in SCGC. Besides, response models for prediction were constructed and confirmed using ANOVA at an accuracy rate of 95%. The models' R2 fluctuated from 88 to 99%. It has been observed that the utilization of CBA and MK alone and together up to 10% as substitution for GGBFS in geopolymer concrete provides the best results therefore it is suggested for structural applications.

Experimental and numerical analysis of the thermal performance of pebble solar thermal collector.

In this work, pebbles of higher specific heat than the conventional absorber materials like aluminium or copper are proposed as a absorber in the solar flat plate collector. The proposed collector are integrated into the building design and constructed with masonry. Tests were conducted by varying the operating parameters which influence its performance, like the flow rate of the heat-absorbing medium, and the tilt of the collector using both coated and uncoated pebbles. The maximum temperature difference that could be measured for a conventional absorber was approximately 8 °C for a flow rate of 0.6 L/min. While for a coated and uncoated absorber, it was 7 °C and 5.5 °C respectively. This difference decreased with an increase in flow rates from 0.6 L/min to 1.2 L/min. For all the flow rates, it was observed that the average difference in efficiency between the coated and the conventional absorber collector is 5.82 %, while the difference between the coated and uncoated absorber collector is 15.68 %. Thus, it is very much evident that by replacing the conventional absorber with the proposed coated pebble absorber, the overall loss in efficiency is just 5.82 %, but the advantages are enormous. Along with the experimental study, numerical analysis was also carried out with CFD modeling. The numerical results agreed well with experimental results with the least error. Therefore, CFD simulation can be further used to optimize the design of the collector.

Multicriteria Decision-Making Technique for Choosing the Optimal Ammonia Energy Share in an Ammonia-Biodiesel-Fueled Reactivity-Controlled Compression Ignition Engine.

Low-temperature combustion paired with the use of carbon-free ammonia and carbon-neutral biofuels is a novel approach for improving performance, reducing greenhouse gases, and reducing regulated emissions. Reactivity-controlled compression ignition (RCCI), a low-temperature combustion technology, dramatically reduces NOx and smoke emissions compared to traditional engines. Ammonia can be projected as a good transit fuel in the journey toward achieving net zero emissions and cleaner energy. This study examines the impact of ammonia energy premixing fraction (AEPF) (20, 30, 40, and 50%) as a low-reactive fuel (LRF) and algal biodiesel as a high-reactive fuel on the performance and emission characteristics of a single-cylinder, water-cooled 3.5 kW CI engine at a constant speed of 1500 rpm under various loading conditions. The research results indicate that the 40% ammonia share RCCI mode exhibited a reduction in carbon dioxide (CO2) by 14.16%, nitrogen oxide (NOx) by 22.6%, and smoke by 42.1%, with an 11.5% improvement in thermal efficiency compared to the neat biodiesel-fueled conventional engine. Furthermore, the analytical hierarchy process (AHP) will be used in conjunction with the technique for order of preference by similarity to ideal solution (TOPSIS) of multiple criteria decision-making techniques to determine the optimal energy share in the RCCI combustion with the goal of achieving superior thermal efficiency and lower emissions. According to the AHP-TOPSIS study findings, AEPF40 is the best choice for all engine loads.

Effect of used engine oil on the mechanical properties and embodied carbon of concrete blended with wheat straw ash as cementitious material.

Every day, more and more binding materials are being used in the construction industry all over the world. However, Portland cement (PC) is used as a binding material, and its production discharges a high amount of undesirable greenhouse gases into the environment. This research work is done to reduce the amount of greenhouse gases discharged during PC manufacturing and to reduce the cost and energy incurred in the cement manufacturing process by making effective consumption of industrial/agricultural wastes in the construction sector. Therefore, wheat straw ash (WSA) as an agricultural waste is utilized as cement replacement material, while used engine oil as an industrial waste is utilized as an air-entraining admixture in concrete. This study's main goal was to examine the cumulative impact of both waste materials on fresh (slump test) and hardened concrete (compressive strength, split tensile strength, water absorption, and dry density). The cement was replaced by up to 15% and used engine oil incorporated up to 0.75% by weight of cement. Moreover, the cubical samples were cast for determining the compressive strength, dry density, and water absorption, while the cylindrical specimen was cast for evaluating the splitting tensile strength of concrete. The results confirmed that compressive and tensile strengths augmented by 19.40% and 16.67%, at 10% cement replacement by wheat straw ash at 90 days, respectively. Besides, the workability, water absorption, dry density, and embodied carbon were decreased as the quantity of WSA increased with the mass of PC, and all of these properties are increased with the incorporation of used engine oil in concrete after 28 days, respectively.

Performance and Emission Analysis of Biodiesel Blends in a Low Heat Rejection Engine with an Antioxidant Additive: An Experimental Study.

The rapid depletion of crude oil and environmental degradation necessitate the search for alternative fuel sources for internal combustion engines. Biodiesel is a promising alternative fuel for compression ignition (CI) engines due to its heat content and combustion properties. Biodiesel blends are used in various vehicles and equipment, such as cars, trucks, buses, off-road vehicles, and oil furnaces. Biodiesel can reduce emissions from CI engines by up to 75% and improve engine durability due to its high lubricity. However, biodiesel has some drawbacks, including a performance reduction and increased nitrogen oxide emissions. Therefore, this study aims to investigate using environmentally available biodiesel in a low-heat rejection engine and an antioxidant additive to enhance the performance and reduce nitrogen oxide emissions. India currently has several biodiesel sources, including mango seed oil, mahua oil, and pongamia oil, which can be effectively utilized in CI engines by adding l-ascorbic acid. The experimental work involves a single-cylinder 4-stroke water-cooled direct injection CI engine with a power output of 5.2 kW. The engine's cylinder head, piston head, and valves are coated with lanthanum oxide using the plasma spray coating technique, with a thickness of 0.5 mm. The coated and uncoated engines are tested with different proportions of mahua oil, mango seed oil, and pongamia oil. The results show that the engine's performance is significantly improved compared to the baseline engine at all loads. Additionally, these biodiesels exhibit a notable reduction in nitrogen oxide emissions when combined with l-ascorbic acid.

Use of waste recycling coal bottom ash and sugarcane bagasse ash as cement and sand replacement material to produce sustainable concrete.

Concrete is widely used as a building material all over the world, and its use is increasing the demand of cement and sand in the construction industry. However, the limited resources and environmental degradation are driving scientists to develop alternative materials from vast volumes of agro-industrial wastes as a partial replacement for conventional cement. In the manufacture of concrete, cement is a major binding resource. This study looked into recycling agro-industrial wastes into cement, such as sugarcane bagasse ash (SCBA), coal bottom ash (CBA), and others, to create sustainable and environmentally friendly concrete. This study aims to see how the combined effects of agricultural by-product wastes affected the characteristics of concrete. SCBA is used to replace fine aggregate (FA) ranging from 0 to 40% by weight of FA, while CBA is used to replace cement content ranging from 0 to 20% by weight of the total binder. In this case, a total of 204 concrete samples (cubes and cylinders) are made using a mixed proportion of 1:1.5:3 and a water-cement ratio of 0.54. Workability, density, water absorption, and mechanical characteristics in terms of compressive and splitting tensile strengths were examined in this study. In addition, for each mix percentage, the total embodied carbon was determined. Workability, density, and water absorption were found to be considerably decreased when CBA and SCBA concentration increased. Due to the pozzolanic nature of CBA and SCBA, an increase in compressive and splitting tensile strengths were seen for specific concrete mixtures, and further addition of CBA and SCBA, the decrease in strength. The embodied carbon of SCBA has augmented the total embodied carbon of concrete, though it can be seen that C15S40, which comprises of 15% CBA and 40% SCBA, is the optimum mix that attained tensile and compressive strength by 3.05 MPa and 28.75 MPa correspondingly, with a 4% reduction in total embodied carbon.

Marshall Stability Prediction with Glass and Carbon Fiber Modified Asphalt Mix Using Machine Learning Techniques.

Pavement design is a long-term structural analysis that is required to distribute traffic loads throughout all road levels. To construct roads for rising traffic volumes while preserving natural resources and materials, a better knowledge of road paving materials is required. The current study focused on the prediction of Marshall stability of asphalt mixes constituted of glass, carbon, and glass-carbon combination fibers to exploit the best potential of the hybrid asphalt mix by applying five machine learning models, i.e., artificial neural networks, Gaussian processes, M5P, random tree, and multiple linear regression model and further determined the optimum model suitable for prediction of the Marshall stability in hybrid asphalt mixes. It was equally important to determine the suitability of each mix for flexible pavements. Five types of asphalt mixes, i.e., glass fiber asphalt mix, carbon fiber asphalt mix, and three modified asphalt mixes of glass-carbon fiber combination in the proportions of 75:25, 50:50, and 25:75 were utilized in the investigation. To measure the efficiency of the applied models, five statistical indices, i.e., coefficient of correlation, mean absolute error, root mean square error, relative absolute error, and root relative squared error were used in machine learning models. The results indicated that the artificial neural network outperformed other models in predicting the Marshall stability of modified asphalt mix with a higher value of the coefficient of correlation (0.8392), R2 (0.7042), a lower mean absolute error value (1.4996), and root mean square error value (1.8315) in the testing stage with small error band and provided the best optimal fit. Results of the feature importance analysis showed that the first five input variables, i.e., carbon fiber diameter, bitumen content, hybrid asphalt mix of glass-carbon fiber at 75:25 percent, carbon fiber content, and hybrid asphalt mix of glass-carbon fiber at 50:50 percent, are highly sensitive parameters which influence the Marshall strength of the modified asphalt mixes to a greater extent.