Transesterification of Palm-based Methyl Palmitate into Esteramine Catalyzed by Calcium Oxide Catalyst

The technology for transesterification reactions between methyl esters and alcohols is well established by using classical homogeneous alkaline catalysts, which provide high conversion of methyl esters to specialty or nonindigenous esters. However, in certain products where the purity of the esters is of concern, the removal of homogeneous catalysts after the completion of the reaction is a challenge in terms of production cost and water footprint. Therefore, a study to investigate the potential of heterogeneous catalysts was conducted on reactions between methyl palmitate and triethanolamine. The degree of basicity and active surface area of calcium oxide (CaO), zinc oxide (ZnO), and magnesium oxide (MgO) were first characterized by using temperature-programmed desorption (TPD-CO₂) and Brunauere–Emmett–Teller (BET), respectively. Among the metal oxides investigated, the CaO catalyst showed the best catalytic activity toward the transesterification process as it gave the highest conversion of methyl palmitate and yielded fatty esteramine compositions similar to the conventional homogeneous catalyst. The optimum transesterification condition by using the CaO catalyst utilized a lower vacuum system of approximately 200 mbar, which could minimize a considerable amount of energy consumption. Furthermore, low CaO dosage of 0.1% was able to give a conversion of 94.5% methyl ester and formed esteramine at 170 °C for 2 h. Therefore, the production of esterquats from esteramine may become more economically feasible through the methyl ester route by using the CaO catalyst, which can be recycled three times.     

Zooplankton population in the river tigris: Effects of samarra impoundment

The influences of the Samarra impoundment on the ecology of the downstream sector of the river Tigris are investigated. Zooplankton were collected monthly from July 1987 to July 1988. It was found that zooplankton were most abundant during high river discharges in March. During the month of low river discharge, September, the zooplankton population was greatly reduced immediately below the barrage and remained so to the last downstream station. Several factors seem to explain such differences. The high discharge from the impoundment was found to be the dominating factor and may flush the small backwaters in which zooplankton were abundant, thus increasing the population in the river. Zooplankton species vary in their ability to sustain populations in the river, variations which are due mainly to species-specific characteristics.     

Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants

Neural Computing and Applications - Preserving red-chili quality is of utmost importance in which the authorities demand quality techniques to detect, classify, and prevent it from impurities. For...     

A new application of giant reed waste material for ammonium removal

Excess nitrogen is one of the main causes of eutrophication in water bodies. In this study, the undesirable agricultural lignocellulosic material giant reed was used to remove ammonium ions from aqueous solutions. Batch experiments were conducted to investigate the effect of various parameters such as contact time, initial ammonium concentration, adsorbent dosage, pH, particle size, agitation rate and phosphate coexisting during the ammonium adsorption process. The ammonium sorption capacity of fibrous giant reed (FGR) at equilibrium was 12.49?mg?N/g with a maximum removal efficiency of 76% observed within 30?min at pH range of 6.5–9.5. Results revealed that the Freundlich isotherm model fitted better with the sorption process than the Langmuir model, and the adsorption process was well described by pseudo-second-order kinetic model. FT-IR analyses indicated that complexation and ion exchange could be the main mechanisms for the ammonium removal by FGR. Results revealed that FGR has a sorption capacity comparable to that of other natural sorbents with the advantage of greater availability with no cost.     

Kinetic study for phosphate removal from water by recycled date-palm wastes as agricultural by-products

The presence of excessive amounts of nutrients including phosphates in water is undesirable. They cause the deterioration of water quality and problems in many natural and engineering systems. The recycling of agricultural waste materials as biosorbents for contaminants removal provides a cheap and ecological means to reduce wastes. This study explored the use of date palm wastes for the effective removal of phosphate from aqueous solutions. Granular date stones (GDS) and palm surface fibres (PSF) as raw abundant waste materials were examined for PO₄ ^-3 removal from aqueous solution. The experimental work was performed in a batch mode to investigate the influence of initial phosphate concentration, contact time, and pH of solution on phosphate biosorption. The FT-IR spectra for the waste materials display many adsorption peaks, confirming the complex nature of the GDS and PSF. Phosphate percentage removal up to 87 and 85% were obtained at initial PO₄ ^-3 concentration of 50 mg as P/L using GDS and PSF, respectively. Due to their low cost and high capability, these types of waste can be used for cost-effective removal of phosphate from wastewater.     

New Type Anode for Calcium Ion Batteries Based on Silicon Carbide Monolayer

Silicon - A theoretical research study was conducted into the possibility of using a two-dimensional graphene-like material silicon carbide nano-sheet (2D-SiCNS) as an anode in rechargeable Ca-ion...     

Uptake of Nickel(II) Ion by Silica-o-Phenylenediamine Derived from Rice Husk Ash

Silicon - The silica-ortho-phenylenediamine(RHAOPDA) derived from Rice Husk Ash and o- phenylenediamine (OPDA) were synthesized. The prepared material was characterized by different techniques; N2-...     

Towards sustainable smart IoT applications architectural elements and design: opportunities,challenges, and open directions

The Journal of Supercomputing - The convergence initiatives of cloud technology and the Internet of Things (IoT) have demonstrated a massive rise of the futuristic technologies which ensure...     

Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model

The design and sustainability of reinforced concrete deep beam are still the main issues in the sector of structural engineering despite the existence of modern advancements in this area. Proper understanding of shear stress characteristics can assist in providing safer design and prevent failure in deep beams which consequently lead to saving lives and properties. In this investigation, a new intelligent model depending on the hybridization of support vector regression with bio-inspired optimization approach called genetic algorithm (SVR-GA) is employed to predict the shear strength of reinforced concrete (RC) deep beams based on dimensional, mechanical and material parameters properties. The adopted SVR-GA modelling approach is validated against three different well established artificial intelligent (AI) models, including classical SVR, artificial neural network (ANN) and gradient boosted decision trees (GBDTs). The comparison assessments provide a clear impression of the superior capability of the proposed SVR-GA model in the prediction of shear strength capability of simply supported deep beams. The simulated results gained by SVR-GA model are very close to the experimental ones. In quantitative results, the coefficient of determination (R²) during the testing phase (R² = 0.95), whereas the other comparable models generated relatively lower values of R² ranging from 0.884 to 0.941. All in all, the proposed SVR-GA model showed an applicable and robust computer aid technology for modelling RC deep beam shear strength that contributes to the base knowledge of material and structural engineering perspective.