فهرست مطالب
Journal of Applied Chemical Research
Volume:14 Issue: 2, Spring 2020
- تاریخ انتشار: 1399/02/16
- تعداد عناوین: 6
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Pages 8-22Heavy metal pollution is propagating throughout the world with the enlargement of industrial activities. The elimination of heavy metal ions from industrial wastewaters has drawn much attention because of the hazardous effects of the heavy metal ions on different organisms. According to these facts, poly (2, 2, 3, 3- tetracyanocyclopropyl) phenyl acrylate (PTCP) with multi cyanocyclopropane functionalities in the pendant group were prepared by reacting benzoyl peroxide with p-(2,2,3, 3-tetracyanocyclopropyl) phenylacrylate (TCP) monomer. (TCP) monomer was synthesized by reacting cyanogen bromide and malononitrile with p-acryloyloxybenzaldehyde at 0 °C in a short time. The synthesized PTCP momopolymer were examined in heavy metal ions adsorption such as Ni (II), Cu (II), Cr (III) and Zn (II) under competitive and non-competitive conditions in aqueous solutions at different pH. The high adsorption rate (<65 min) was seen. The synthesized polymer and its metal chelates were investigated by thermogravimetric analysis (TGA),Fourier-transform infrared spectroscopy (FT-IR), atomic absorption techniques (AAS), UV-vis spectroscopy and scanning electron microscopy (SEM).Keywords: Heavy Metal Ions, Phenylacrylate, Malononitrile, Cyanogenbromide, Radical polymerization
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Pages 23-35
In this work, the artificial neural networks (ANN) technology was applied to the simulation of oleuropein extraction process. For this technology, a 3-layer network structure is applied, and the operation factors such as amount of flow intensity ratio, temperature, residence time, and pH are used as input variables of the network, whereas the extraction yield is considered as response value. Performance indicators RMSE, SSE, R2adj, R2 have been used to determine the number of optimal midway neurons. Neural network trained with an error back-propagation algorithm, was used to evaluate the effects of parameters on extraction yield.The obtained optimal architecture of artificial neural network model involved a feed-forward neural network with 4 input neurons, 1 hidden layer with 6 neurons and one output layer including single neuron.The trained network gave the minimum value in the RMSE of 1.6423 and the maximum value in the = 0.9641, which implied a good agreement between the predicted value and the actual value, and confirmed a good generalization of the network.Functional structure of modeling, related to education,validation and test were obtained 0.99229,0.95591and 0.99224 respectively. The overall agreement between the experimental data and ANN predictions was satisfactory showing a determination coefficient of 0.9838.The neural network tools implemented in MATLAB software were used to predict the change process.
Keywords: Artificial Neural Networks, Extraction, Microfluidic, Oleuropein -
Pages 36-47
Known as a Lewis acid which acts as a natural catalyst, bentonite can be used to produce several arylidene (thio) barbituric acid derivatives through conducting a Knoevenagel reaction between aromatic aldehydes and (thio) barbituric acid. Water is considered as the medium for this reaction and the results are at arange of good to excellent over a reasonable reaction time. This method is natural and economic as well as convenient to work with, while the reaction time is also short. In addition to excellent results, this method is also environment-friendly due to the use of water as solvent that broadens the domain of organic synthesis in aqueous medium.
Keywords: Natural catalyst, Bentonite (Al2O3.4SiO.H2), Arylidene (thio) barbituric acids, Water media, Knoevenagel Condensation -
Pages 48-57
In this work, aluminum nitride (AlN) thin films with different thicknesses were deposited on quartz and silicon substrates using single ion beam sputtering technique. The physical and chemical properties of prepared films were investigated by different characterization technique. X-ray diffraction (XRD) spectra revealed that all of the deposited films have an amorphous structure. The Al-N bond information of deposited films on silicon substrates was identified by Fourier transform infrared (FTIR) spectroscopy. FTIR results confirmed the formation of AlN films in prepared samples. Atomic force microscopy (AFM) revealed that the surface of films was smooth with low values of roughness. The low values of roughness can be caused the low acoustic loss in AlN films, which is interesting for applications in electro-acoustic devices.
Keywords: AlN, Ion beam sputtering, Film thickness, Morphology, optical properties -
Pages 58-69In this study, a novel acidic magnetic dicationic ionic liquid was prepared in three steps to serve as a green catalyst in organic synthesis. The newly synthesized catalyst was characterized UV- VIS, and VSM analysis. Additionally, the decomposition steps acatalyst were investigated by thermal analysis techniques (TGA/DSC). The synthesized acidic magnetic dicationic ion liquid has a magnetization of about 0.3 emu/g, which is less than FeCl emu.g- 1). Moreover, the catalytic activity of this acidic ionic liquid was successfully tested in the straight forward one-pot synthesis reaction between β-naphthol, aldehyde, and acetamide or Benzamide. The pure products were determined by analyzing their physical data (melting points, IR method has several advantages such as easy work yield, and high atom economy. The catalyst can be reused and recovered without losing activity.Keywords: 1-amidoalkyl-2-naphthols, Multicomponent reaction, acidic dicationic ionic liquid, Solvent-free
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Pages 70-81Nickel (Ni) as a heavy metal due to its toxicity should be removed from wastewater and aquatic environments using efficient technology. The aim of this study was to remove Ni from an aqueous solution using palm leaf ash produced in a furnace. To do so, kinetic and thermodynamic experiments were conducted on the adsorption process. Moreover, the effect of time, pH, adsorbent and initial concentration of Ni was studied on Ni adsorption. The results of the experiment indicated that the Ni adsorption process followed the Freundlich isotherm model. The study of kinetic data also displayed the removal of Ni ions from the pseudo-second-order kinetics. The results showed that the percentage removal of Ni (II) and maximum adsorption capacity of an adsorbent for Ni (II) ions were 94.67% and 40.81 mgg-1, respectively. Furthermore, the enthalpy of the adsorption process (ΔH) was 62706.8 j.mol-1.Keywords: Biosorbent, Nickel Adsorption, Palm Leaf Ash