219 research outputs found

    Leverage of Environmental Pollutant Crump Rubber on the Dry Sliding Wear Response of Epoxy Composites.

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    The effect of crump rubber on the dry sliding wear behavior of epoxy composites is investigated in the present study. Wear tests are carried out for three levels of crump rubber (10, 20, and 30 vol.%), normal applied load (30, 40, and 50 N), and sliding distance (1, 3, and 5 km). The wear behavior of crump rubber-epoxy composites is investigated against EN31 steel discs. The hybrid mathematical approach of Taguchi-coupled Grey Relational Analysis (GRA)-Principal Component Analysis (PCA) is used to examine the influence of crump rubber on the tribological response of composites. Mathematical and experimental results reveal that increasing crump rubber content reduces the wear rate of composites. Composites also show a significant decrease in specific wear values at higher applied loads. Furthermore, the coefficient of friction also shows a decreasing trend with an increase in crump rubber content, indicating the effectiveness of reinforcing crump rubber in a widely used epoxy matrix. Analysis of Variance (ANOVA) results also reveal that the crump rubber content in the composite is a significant parameter to influence the wear characteristic. The post-test temperature of discs increases with an increase in the applied load, while decreasing with an increase in filler loading. Worn surfaces are analyzed using scanning electron microscopy to understand structure-property correlations. Finally, existing studies available in the literature are compared with the wear data of the present study in the form of a property map

    Microwave assisted biodiesel production using heterogeneous catalysts

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    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 (5ā€“60 min) while maintaining or improving catalytic activity (>90%) when compared to traditional heating

    Exploring copyrolysis characteristics and thermokinetics of peach stone and bituminous coal blends

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    Copyrolysis, being an active area of research due to its synergistic impact in utilizing diverse fuel resources, including waste materials, like, peach stone (PS), has been the focal point for this study. PS, produced in vast quantities annually and typically intended for landscaping or insulation purposes, is being studied in combination with lowā€grade bituminous coal for energy utilization focusing on thermokinetics and synergistic aspects. Coalā€peach stone (Cā€PS) blends were formulated at different ratios and subjected to comprehensive characterization techniques, including ultimate analysis (CHNā€S), gross calorific value (GCV), Fourier transform infrared spectroscopy, and thermogravimetric analyzer (TGA). The ultimate analysis revealed an enhancement in carbon and hydrogen content from 45.38% to 68.08% and from 3.89% to 6.96%, respectively. Additionally, a reduction in sulfur and nitrogen content from 0.54% to 0.11% and from 1.16% to 0.42%, respectively, was observed with an increase in the ratio of PS in the Cā€PS blends. The GCV of Cā€PS blends ranged from 20.75 to 26.01ā€‰MJā€‰kgāˆ’1. The pyrolysis conditions simulated in TGA are pivotal for evaluating thermokinetics and synergistic effects. The 60C:40PS blend shows a positive synergy index (SI) value of 0.0203% concerning total mass loss (MLT) indicating a favorable condition for bioā€oil generation. Coatsā€“Redfern modelā€fitting method reveals that the activation energy (Ea) of Cā€PS blends increases in Section II with the addition of PS, and conversely, it decreases in Section III. The Ea for 100PS and 100C was 106.76 and 45.85ā€‰kJā€‰molāˆ’1 through (D3) and (F1), respectively, which was improved through the optimal blend 60C:40PS with an Ea of 94.56 and 27.58ā€‰kJā€‰molāˆ’1 through (D3) and (F2), respectively. The values obtained from linear regression prove that the kinetic models are effective while the thermodynamic analysis indicates that the pyrolytic behavior of Cā€PS blends is characterized as endothermic, nonspontaneous, and capable of achieving thermodynamic equilibrium more rapidly

    Effect of additivized biodiesel blends on diesel engine performance, emission, tribological characteristics, and lubricant tribology

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    Ā© 2020 by the authors. This research work focuses on investigating the lubricity and analyzing the engine characteristics of diesel-biodiesel blends with fuel additives (titanium dioxide (TiO2) and dimethyl carbonate (DMC)) and their effect on the tribological properties of a mineral lubricant. A blend of palm-sesame oil was used to produce biodiesel using ultrasound-assisted transesterification. B30 (30% biodiesel + 70% diesel) fuel was selected as the base fuel. The additives used in the current study to prepare ternary fuel blends were TiO2 and DMC. B30 + TiO2 showed a significant reduction of 6.72% in the coefficient of friction (COF) compared to B30. B10 (Malaysian commercial diesel) exhibited very poor lubricity and COF among all tested fuels. Both ternary fuel blends showed a promising reduction in wear rate. All contaminated lubricant samples showed an increment in COF due to the dilution of combustible fuels. Lub + B10 (lubricant + B10) showed the highest increment of 42.29% in COF among all contaminated lubricant samples. B30 + TiO2 showed the maximum reduction (6.76%) in brake-specific fuel consumption (BSFC). B30 + DMC showed the maximum increment (8.01%) in brake thermal efficiency (BTE). B30 + DMC exhibited a considerable decline of 32.09% and 25.4% in CO and HC emissions, respectively. The B30 + TiO2 fuel blend showed better lubricity and a significant improvement in engine characteristics

    Artificial neural network led optimization of oxyhydrogen hybridized diesel operated engine

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    The prevailing massive exploitation of conventional fuels has staked the energy accessibility to future generations. The gloomy peril of inflated demand and depleting fuel reservoirs in the energy sector has supposedly instigated the urgent need for reliable alternative fuels. These very issues have been addressed by introducing oxyhydrogen gas (HHO) in compression ignition (CI) engines in various flow rates with diesel for assessing brake-specific fuel consumption (BSFC) and brake thermal efficiency (BTE). The enrichment of neat diesel fuel with 10 dm3/min of HHO resulted in the most substantial decrease in BSFC and improved BTE at all test speeds in the range of 1000ā€“ 2200 rpm. Moreover, an Artificial Intelligence (AI) approach was employed for designing an ANN performance-predicting model with an engine operating on HHO. The correlation coefficients (R) of BSFC and BTE given by the ANN predicting model were 0.99764 and 0.99902, respectively. The mean root errors (MRE) of both parameters (BSFC and BTE) were within the range of 1%ā€“3% while the root mean square errors (RMSE) were 0.0122 kg/kWh and 0.2768% for BSFC and BTE, respec-tively. In addition, ANN was coupled with the response surface methodology (RSM) technique for comprehending the individual impact of design parameters and their statistical interactions gov-erning the output parameters. The R2 values of RSM responses (BSFC and BTE) were near to 1 and MRE values were within the designated range. The comparative evaluation of ANN and RSM predicting models revealed that MRE and RMSE of RSM models are also well within the desired range but to be outrightly accurate and precise, the choice of ANN should be potentially endorsed. Thus, the combined use of ANN and RSM could be used effectively for reliable predictions and effective study of statistical interactions

    RSM and Artificial Neural Networking based production optimization of sustainable Cotton bio-lubricant and evaluation of its lubricity & tribological properties

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    Depletion of mineral reservoirs along with health and environmental concerns have led to a greater focus on bio-lubricants. The purpose of this study was to analyze and optimize the reaction conditions of the transesterification process for cotton biolubricant synthesis by using Response Surface Methodology (RSM). In RSM, Rotatable central composite design was selected to examine the effect of reaction input factors on the yield of cotton bio-lubricant during the transesterification process. ANOVA analysis showed that temperature was the most significant factor followed by time, pressure and catalyst-concentration. Optimum reaction conditions obtained by RSM for maximum TMP tri-ester (cotton bio-lubricant) yield of about 37.52% were 144 Ā°C temperature, 10 h time, 25 mbar pressure, and 0.8% catalyst-concentration. RSM predicted results were successfully validated experimentally and by artificial neural networking. About 90%ā€“94% cotton seed oil bio-lubricant was obtained after purification and its physiochemical, lubricity and tribological properties were evaluated and found comparable with ISO VG-46 and SAE-40 mineral lubricant. Hence, cottonseed oil is a potential source for the bio-lubricant industry

    Production and utilization aspects of waste cooking oil based biodiesel in Pakistan

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    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 expertsā€™ 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

    Dynamic Profiling of Ī²-Coronavirus 3CL Mpro Protease Ligand-Binding Sites

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    Ī²-coronavirus (CoVs) alone has been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a backup against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensable role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand-protein interactions. Herein, we provide a comprehensive comparison of all nonredundant ligand-binding sites available for SARS-CoV2, SARS-CoV, and MERS-CoV Mpro. Extensive adaptive sampling has been used to investigate structural conservation of ligand-binding sites using Markov state models (MSMs) and compare conformational dynamics employing convolutional variational auto-encoder-based deep learning. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across Ī²-CoV homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor

    Dynamic Profiling of Ī²-Coronavirus 3CL M<sup>pro</sup>Protease Ligand-Binding Sites

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    Data availability statement: The trajectories of Mpro simulations and models of the metastable states can be downloaded from 10.5281/zenodo.4782284.Ī²-coronavirus (CoVs) alone has been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a backup against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensable role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligandā€“protein interactions. Herein, we provide a comprehensive comparison of all nonredundant ligand-binding sites available for SARS-CoV2, SARS-CoV, and MERS-CoV Mpro. Extensive adaptive sampling has been used to investigate structural conservation of ligand-binding sites using Markov state models (MSMs) and compare conformational dynamics employing convolutional variational auto-encoder-based deep learning. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across Ī²-CoV homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor.There was no funding for this wor

    Effect of primary and secondary alcohols as oxygenated additives on the performance and emission characteristics of diesel engine

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    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 NOx formation 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
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