The growing demand for sustainable and high-performance asphalt binders has prompted the exploration of waste-derived modifiers. This study investigates the performance enhancement of Natural Asphalt (NA) using Sugarcane Molasses (SM) and Waste Engine Oil (WEO). The modified blends were prepared by partially replacing 50 % NA with varying proportions of SM and WEO ranging from 10 % to 40 % of the total weight of NA. Comprehensive testing was conducted, including penetration, softening point, ductility, viscosity, Bending Beam Rheometer (BBR), Multiple Stress Creep Recovery (MSCR), Energy Dispersive X-ray Spectroscopy (EDX), Fourier Transform Infrared (FTIR) spectroscopy, and Scanning Electron Microscopy (SEM). The results demonstrated that modified blends with a high WEO content significantly increased fluidity, reducing rotational viscosity by up to 91 % for the blend with 40 % WEO and 10 % SM at 135 ◦C. Conversely, higher SM content increased stiffness, as seen in the blend with 40 % SM and 10 % WEO, with penetration values rising by 305 % compared to unmodified NA. Rheological testing showed that the 40 % SM and 10 % WEO blend achieved the highest rutting resistance with a Performance Grade (PG) of 88 ◦C, while the 40 % WEO and 10 % SM blend exhibited the best fatigue resistance with a 55 % reduction in G* .sinδ. Low-temperature performance was significantly improved across all blends, with the 40 % WEO and 10 % SM blend achieving the lowest creep stiffness and highest m-value, ensuring superior thermal cracking resistance. Chemical analysis revealed increased oxygen content (18.6 %) and reduced sulfur content (60 %) in the 40 % SM and 10 % WEO blend, indicating enhanced oxidation resistance. SEM analysis confirmed the development of dense morphology in the 40 % SM and 10 % WEO blend, correlating with superior structural integrity. Grey decision analysis identified the 40 % SM and 10 % WEO blend as the optimal blend with the lowest bull’s-eye distance, reflecting balanced performance across all parameters. These findings highlight the complementary effects of SM and WEO in enhancing the performance of NA, with the 40 % SM and 10 % WEO blend emerging as the most promising blend for bio-asphalt applications.
Eight new complexes with the general formula [M(L)2(H2O)2] were prepared resulting from the reaction of the new Schiff base ligand [(E)-5- ((2-hydroxybenzylidene)amino)-2-phenyl-2,4-dihydro-3H-pyrazol-3- one(L)] with metal ions [manganese, cadmium, zinc, copper, nickel, cobalt, Mercury Bivalent and tetravalent platinum. This ligand was derived from the reaction of the amine (5-amino-2-phenyl-2,4-dihydro3H-pyrazol-3-one) with Salicylaldehyde, which is linked to the metal ions via two atoms. The nitrogen is the isomethene group, and the oxygen is the hydroxide group of the pyrazoline ring. The prepared compounds were characterized using infrared spectroscopy, nuclear magnetic resonance spectroscopy, and ultraviolet spectroscopy, and from the
... Show MoreThe reaction of [Benzoyl hydrazine] with [Diphenyl mono oxime] and Glacial acetic acid was carried out in methanol gave a new tridentate ligand [Benzoic acid (2- hydroxyimino- 1, 2-diphyneylethylidene) - hydrazide]. This ligand was reacted with some metal ions (Fe(II), Co(II), Ni(II), and Cu(II)) in methanol with (1:1) metal : ligand ratio to give a series of new complexes of the general formula [M(L)Cl2.H2O], where M= Fe(11), Co(11), Ni(11) and Cu(11) . All compounds were characterized by spectroscopic methods (I.R, UV-Vis), elemental microanalysis (C.H.N), atomic absorption, magnetic susceptibility, and conductivity measurements. From the obtained data the proposed molecular structures were suggested for the complexes of Fe (II), Co (II)
... Show MoreBy reading the book (Endless Forms Most Beautiful: The New Science of Evo Devo) by Sean B. Carroll, new horizons opened up about the nature of the formation of the living organism. Although he presented the idea that the artist was influenced by the material assets of nature in his holographic art formations, the new science of Evo-Devo (Evolutionary Developmental Science) provided models worth standing on when comparing the similarity of the formation of living organisms on the one hand, and the formation of works of art with holographic organic bodies on the other. But the excitement lies in the fact that the formation of living natural organisms is often driven by subtle intelligent mechanisms that are different from the mechanisms us
... Show MoreThis paper reports a numerical study of flow behaviors and natural convection heat transfer characteristics in an inclined open-ended square cavity filled with air. The cavity is formed by adiabatic top and bottom walls and partially heated vertical wall facing the opening. Governing equations in vorticity-stream function form are discretized via finite-difference method and are solved numerically by iterative successive under relaxation (SUR) technique. A computer program to solve mathematical model has been developed and written as a code for MATLAB software. Results in the form of streamlines, isotherms, and average Nusselt number, are obtained for a wide range of Rayleigh numbers 103-106 with Prandtl number 0.71
... Show MoreThis work presents a comparison between the Convolutional Encoding CE, Parallel Turbo code and Low density Parity Check (LDPC) coding schemes with a MultiUser Single Output MUSO Multi-Carrier Code Division Multiple Access (MC-CDMA) system over multipath fading channels. The decoding technique used in the simulation was iterative decoding since it gives maximum efficiency at higher iterations. Modulation schemes used is Quadrature Amplitude Modulation QAM. An 8 pilot carrier were
used to compensate channel effect with Least Square Estimation method. The channel model used is Long Term Evolution (LTE) channel with Technical Specification TS 25.101v2.10 and 5 MHz bandwidth bandwidth including the channels of indoor to outdoor/ pedestrian
Four complexes of Co(II),Ni(II),Cu(II) and Zn(II) with the azo ligand (4-chloro-N-(2-(dimethylamino)ethyl)-5-((2-hydroxy- 4,6-dimethylphenol)diazenyl)-2-methoxybenzamide) L. The structure of ligand and complexes were confirmed on the basis of their analytical and spectral data, these dyes were tested as dyeing in cotton fabric, and also testing in light and cleaner firmness. Also, antimicrobial and antifungal activities of ligand and their complexes were evaluated and the results showed that the ZnL compound showed the higher antibacterial activity with inhibition zone of 13mm against Staphyloco-ccus epidermidis, Steptococcus sp. and Escherichia coli compared with ligand and other metal complexes .In case of ZnL compound the antifungal acti
... Show MoreFour complexes of Co(II),Ni(II),Cu(II) and Zn(II) with the azo ligand (4-chloro-N-(2-(dimethylamino)ethyl)-5-((2-hydroxy-4,6-dimethylphenol)diazenyl)-2-methoxybenzamide) L. The structure of ligand and complexes were confirmed on the basis of their analytical and spectral data, these dyes were tested as dyeing in cotton fabric, and also testing in light and cleaner firmness. Also, antimicrobial and antifungal activities of ligand and their complexes were evaluated and the results showed that the ZnL compound showed the higher antibacterial activity with inhibition zone of 13mm against Staphyloco-ccus epidermidis, Steptococcus sp. and Escherichia coli compared with ligand and other metal complexes .In case of ZnL compound the antifungal activ
... Show MoreDeep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
... Show MoreHydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO2 NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil at dif
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