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.     

Development of an integrated model for airflow in building spaces

In building energy simulation, an integrated modelling of airflow in the building needed. Therefore, in this paper two approaches are used for building energy simulation: zonal network for modelling of the building segments and Computational Fluid Dynamics (CFD) for modelling of the airflow. It is noted that a synchronize solution process is needed for the building and the CFD equation-sets. For this purpose an iterative procedure is used to corresponding solution of these equations.     

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...     

Optimum loading of machines in a flexible manufacturing system using a mixed-integer linear mathematical programming model and genetic algorithm

Machine loading problem in a flexible manufacturing system (FMS) encompasses various types of flexibility aspects pertaining to part selection and operation assignments. The evolution of flexible manufacturing systems offers great potential for increasing flexibility by ensuring both cost-effectiveness and customized manufacturing at the same time. This paper proposes a linear mathematical programming model with both continuous and zero-one variables for job selection and operation allocation problems in an FMS to maximize profitability and utilization of system. The proposed model assigns operations to different machines considering capacity of machines, batch-sizes, processing time of operations, machine costs, tool requirements, and capacity of tool magazine. A genetic algorithm (GA) is then proposed to solve the formulated problem. Performance of the proposed GA is evaluated based on some benchmark problems adopted from the literature. A statistical test is conducted which implies that the proposed algorithm is robust in finding near-optimal solutions. Comparison of the results with those published in the literature indicates supremacy of the solutions obtained by the proposed algorithm for attempted model.     

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.     

Determining Flow Friction Factor in Irrigation Pipes Using Data Mining and Artificial Intelligence Approaches

The implicit Colebrook–White equation has been widely used to estimate the friction factor for turbulent fluid in irrigation pipes. A fast, accurate, and robust resolution of the Colebrook–White equation is, in particular, necessary for scientific intensive computations. In this study, the performance of some artificial intelligence approaches, including gene expression programming (GEP), which is a variant of genetic programming (GP); adaptive neurofuzzy inference system (ANFIS); and artificial neural network (ANN) has been compared to the M5 model tree, which is a data mining technique and, to most available approximations, is based on root mean squared error (RMSE), mean absolute error (MAE) and correlation coefficient (R). Results show that Serghides and Buzzelli approximations with RMSE (0.00002), MAE (0.00001), and R (0.99999) values had the best performances. Among the data mining and artificial intelligence approaches, the GEP with RMSE (0.00032), MAE (0.00026), and R (0.99953) values performed better. However, all 20 explicit approximations except Wood, Churchill (full range of turbulence including laminar regime) and Rau and Kumar estimated the friction factor more accurately than the GEP.     

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...     

Nonisothermal crystallization behavior and mechanical properties of PEEK/SCF/nano-SiO2 composites

Nonisothermal crystallization of hybrid PEEK composites reinforced with short carbon fibers (SCF) and nano-SiO₂ (1, 1.5 and 2 wt%) was investigated using DSC. Composites were fabricated by melt-mixing process at 400 °C. The Size of the nanoparticles was 13 nm. Samples were cooled from 410 °C to 25 °C with cooling rates of 10, 30, 50 and 70 °C min⁻¹. The onset, peak and end crystallization temperatures were investigated as well as absolute crystallization percentage and crystallization time. Avrami, Ozawa and Ozawa–Avrami equations were fitted to the data in order to investigate the crystallization kinetics. Mechanical behaviors of the composites were examined using nanoindentation and nanoscratching. DSC results revealed that absolute crystallization percentage increases in PEEK/SCF/1%SiO₂ and PEEK/SCF/1.5%SiO₂ samples compared to PEEK/SCF, however it decreases by adding more nano-SiO₂. Ozawa–Avrami is proved to be the best model for describing crystallization behavior of the composites while Avrami equation was suitable for describing a part of the crystallization process. The Avrami and Ozawa–Avrami constants were calculated. Besides, adding SCFs and nano-SiO₂ into PEEK results in a significant decrease in plasticity index, while increases the resistance to plastic deformation of the composite.