Hydrodeoxygenation is one of the promising technologies for the transformation of triglycerides into long-chain hydrocarbon fuel commonly known as green diesel. The hydrodeoxygenation (HDO) of rubber seed oil into diesel range (C15-C18) hydrocarbon over non-sulphided bimetallic (Ni-Mo/γ-Al2O3 solid catalysts were studied. The catalysts were synthesized via wet impregnation method as well as sonochemical method. The synthesized catalysts were subjected to characterization methods including FESEM coupled with EDX, XRD, BET, TEM, XPS, NH3-TPD, CO-chemisorption and H2-TPR in order to investigate the effects of ultrasound irradiations on physicochemical properties of the catalyst. All the catalysts were tested for HDO reaction at 350 °C, 35 bar, H2/oil 1000 N (cm3/cm3) and WHSV = 1 h-1 in fixed bed tubular reactor. The catalyst prepared via sonochemical method showed comparatively higher specific surface area, particles in nano-size and uniform distribution of particle on the external surface of the support, higher crystallinity and lower reduction temperature as well as higher concentration of Mo4+ deoxygenating metal species. These physicochemical properties improved the catalytic activity compared to conventionally synthesized catalyst for HDO of rubber seed oil. The catalytic performance of sonochemically synthesized Ni-Mo/γ-Al2O3 catalyst (80.87%) was higher than the catalyst prepared via wet impregnation method (63.3%). The sonochemically synthesized Ni-Mo/γ-Al2O3 catalyst is found to be active, produces 80.87 wt% of diesel range hydrocarbons, and it gives high selectivity for Pentadecane (18.7 wt%), Hexadecane (16.65 wt%), Heptadecane (24.45 wt%) and Octadecane (21.0 wt%). The product distribution revealed that the deoxygenation reaction pathway was preferred. Higher conversion and higher HDO yield in this study are associated mainly with the change in concentration ratio between oxidation states of molybdenum (Mo4+, Mo5+, and Mo6+) on the external surface of the catalyst due to ultrasound irradiation during the synthesis process. Consequently, the application of sonochemically synthesized non-sulphided catalysts favored mainly hydrodeoxygenation of diesel range hydrocarbon.
Throughout the application of enhanced oil recovery (EOR), surfactant adsorption is considered the leading constraint on both the successful implementation and economic viability of the process. In this study, a comprehensive investigation on the adsorption behaviour of nonionic and anionic individual surfactants; namely, alkyl polyglucoside (APG) and alkyl ether carboxylate (AEC) was performed using static adsorption experiments, isotherm modelling using (Langmuir, Freundlich, Sips, and Temkin models), adsorption simulation using a state-of-the-art method, binary mixture prediction using the modified extended Langmuir (MEL) model, and artificial neural network (ANN) prediction. Static adsorption experiments revealed higher adsorption capacity of APG as compared to AEC, with sips being the most fitted model with R2 (0.9915 and 0.9926, for APG and AEC respectively). It was indicated that both monolayer and multilayer adsorption took place in a heterogeneous adsorption system with non-uniform surfactant molecules distribution, which was in remarkable agreement with the simulation results. The (APG/AEC) binary mixture prediction depicted contradictory results to the experimental individual behaviour, showing that AEC had more affinity to adsorb in competition with APG for the adsorption sites on the rock surface. The adopted ANN model showed good agreement with the experimental data and the simulated adsorption values for APG and AEC showed a decreasing trend as temperature increases. Simulating the impact of binary surfactant adsorption can provide a tremendous advantage of demonstrating the binary system behaviour with less experimental data. The utilization of ANN for such prediction procedure can minimize the experimental time, operating cost and give feasible predictions compared to other computational methods. The integrated workflow followed in this study is quite innovative as it has not been employed before for surfactant adsorption studies.
Recently, nano-EOR has emerged as a new frontier for improved and enhanced oil recovery (IOR & EOR). Despite their benefits, the nanoparticles tend to agglomerate at reservoir conditions which cause their detachment from the oil/water interface, and are consequently retained rather than transported through a porous medium. Dielectric nanoparticles including ZnO have been proposed to be a good replacement for EOR due to their high melting point and thermal properties. But more importantly, these particles can be polarized under electromagnetic (EM) irradiation, which provides an innovative smart Nano-EOR process denoted as EM-Assisted Nano-EOR. In this study, parameters involved in the oil recovery mechanism under EM waves, such as reducing mobility ratio, lowering interfacial tensions (IFT) and altering wettability were investigated. Two-phase displacement experiments were performed in sandpacks under the water-wet condition at 95°C, with permeability in the range of 265-300 mD. A crude oil from Tapis oil field was employed; while ZnO nanofluids of two different particle sizes (55.7 and 117.1 nm) were prepared using 0.1 wt. % nanoparticles that dispersed into brine (3 wt. % NaCl) along with SDBS as a dispersant. In each flooding scheme, three injection sequential scenarios have been conducted: (i) brine flooding as a secondary process, (ii) surfactant/nano/EM-assisted nano flooding, and (iii) second brine flooding to flush nanoparticles. Compare with surfactant flooding (2% original oil in place/OOIP) as tertiary recovery, nano flooding almost reaches 8.5-10.2% of OOIP. On the other hand, EM-assisted nano flooding provides an incremental oil recovery of approximately 9-10.4% of OOIP. By evaluating the contact angle and interfacial tension, it was established that the degree of IFT reduction plays a governing role in the oil displacement mechanism via nano-EOR, compare to mobility ratio. These results reveal a promising way to employ water-based ZnO nanofluid for enhanced oil recovery purposes at a relatively high reservoir temperature.
Over the past decades, Ionic liquids (ILs) have gained considerable attention from the scientific community in reason of their versatility and performance in many fields. However, they nowadays remain mainly for laboratory scale use. The main barrier hampering their use in a larger scale is their questionable ecological toxicity. This study investigated the effect of hydrophobic and hydrophilic cyclic cation-based ILs against four pathogenic bacteria that infect humans. For that, cations, either of aromatic character (imidazolium or pyridinium) or of non-aromatic nature, (pyrrolidinium or piperidinium), were selected with different alkyl chain lengths and combined with both hydrophilic and hydrophobic anionic moieties. The results clearly demonstrated that introducing of hydrophobic anion namely bis((trifluoromethyl)sulfonyl)amide, [NTF2] and the elongation of the cations substitutions dramatically affect ILs toxicity behaviour. The established toxicity data [50% effective concentration (EC50)] along with similar endpoint collected from previous work against Aeromonas hydrophila were combined to developed quantitative structure-activity relationship (QSAR) model for toxicity prediction. The model was developed and validated in the light of Organization for Economic Co-operation and Development (OECD) guidelines strategy, producing good correlation coefficient R2 of 0.904 and small mean square error (MSE) of 0.095. The reliability of the QSAR model was further determined using k-fold cross validation.