scholarly journals Artificial intelligence for the removal of benzene, toluene, ethyl benzene and xylene (BTEX) from aqueous solutions using iron nanoparticles

2017 ◽  
Vol 18 (5) ◽  
pp. 1650-1663 ◽  
Author(s):  
Ahmed S. Mahmoud ◽  
Mohamed K. Mostafa ◽  
Soha A. Abdel-Gawad
Keyword(s):  
Aqueous Solutions ◽  
Removal Efficiency ◽  
Organic Contaminants ◽  
Iron Nanoparticles ◽  
Absolute Error ◽  
Sem Analysis ◽  
Ethyl Benzene ◽  
Uv Spectrophotometry ◽  
Benzene Toluene ◽  
Artificial Neural Network Ann

Abstract Magnetic nanosorbents proved to be highly effective in inorganic and organic contaminants removal from aqueous solutions, especially nano zero valent iron (nZVI). The main purpose of this study is to investigate the effect of using nZVI in removing benzene, toluene, ethyl benzene and xylene (BTEX) contaminants from aqueous solutions. The nZVI and the standard BTEX solution were prepared in the laboratory. X-ray diffraction (XRD), UV spectrophotometry, and scanning electron microscopy (SEM) analysis were used for nZVI characterization. The effects of contact time, initial BTEX mixture concentration, adsorbent dose, temperature, and pH on the amount of BTEX absorbed were investigated. The highest removal efficiency of 97% for the BTEX mixture was achieved at a stirring rate of 100 rpm, temperature of 60°C, and pH 7. The minimum effective time for efficient removal was 30 min, while the effective dose for BTEX compounds removal was 0.22 g/L. The Freundlich model was the best fit of experimental data. An artificial neural network (ANN) was used to predict the BTEX removal efficiency. Modeling results showed that ANN with average absolute error of 0.6272% is reliable in describing the adsorption of BTEX onto the iron nanoparticles. It is estimated that the cost of BTEX removal by nZVI under the optimal conditions will be about 3.5 USD per cubic meter.

Analysis of the organic contaminants in the condensate produced in the in situ underground coal gasification process

2013 ◽  
Vol 67 (3) ◽  
pp. 644-650 ◽  
Author(s):  
Adam Smoliński ◽  
Krzysztof Stańczyk ◽  
Krzysztof Kapusta ◽  
Natalia Howaniec
Keyword(s):  
Organic Contaminants ◽  
Coal Gasification ◽  
Ethyl Benzene ◽  
Hard Coal ◽  
Stable Operation ◽  
Underground Coal Gasification ◽  
Operational Conditions ◽  
Process Stage ◽  
Post Process ◽  
Benzene Toluene

Addressing the environmental risks related to contamination of groundwater with the phenolics, benzene, toluene, ethyl benzene, xylene (BTEX) and polycyclic aromatic hydrocarbons (PAHs), which might be potentially released from the underground coal gasification (UCG) under adverse hydrogeological and/or operational conditions, is crucial in terms of wider implementation of the process. The aim of this study was to determine the main organic pollutants present in the process condensate generated during the UCG trial performed on hard coal seam in the Experimental Mine ‘Barbara’, Poland; 8,933 L of condensate was produced in 813 h of experiment duration (including 456 h of the post-process stage) with average phenolics, BTEX and PAH concentrations of 576,000, 42.3 and 1,400.5 μg/L, respectively. The Hierarchical Clustering Analysis was used to explore the differences and similarities between the samples. The sample collected during the first 48 h of the process duration was characterized by the lowest phenanthrene, anthracene, fluoranthene and pyrene contents, high xylene content and the highest concentrations of phenolics, benzene, toluene and ethyl benzene. The samples collected during the stable operation of the UCG process were characterized by higher concentrations of naphthalene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benzo(a)anthracene, chrysene, while in the samples acquired in the post-process stage the lowest concentrations of benzene, toluene, naphthalene, acenaphthene and fluorene were observed.

Artificial Neural Networks Used As a Rule Selector for Fuzzy Logic Controllers

1993 ◽  
Author(s):  
Shou-Heng Huang ◽  
Ron M. Nelson
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Absolute Error ◽  
Operating Conditions ◽  
Delta Rule ◽  
Rule Sets ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Set Up ◽  
And Control

Abstract A feedforward, three-layer, partially-connected artificial neural network (ANN) is proposed to be used as a rule selector for a rule-based fuzzy logic controller. This will allow the controller to adapt to various control modes and operating conditions for different plants. A principal advantage of an ANN over a look up table is that the ANN can make good estimates to fill in for missing data. The control modes, operating conditions, and control rule sets are encoded into binary numbers as the inputs and outputs for the ANN. The General Delta Rule is used in the backpropagation learning process to update the ANN weights. The proposed ANN has a simple topological structure and results in a simple analysis and relatively easy implementation. The average square error and the maximal absolute error are used to judge if the correct connections between neurons are set up. Computer simulations are used to demonstrate the effectiveness of this ANN as a rule selector.

scholarly journals Multi-Component Adsorption of Benzene, Toluene, Ethylbenzene, and Xylene from Aqueous Solutions by Montmorillonite Modified with Tetradecyl Trimethyl Ammonium Bromide

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
H. Nourmoradi ◽  
Mehdi Khiadani ◽  
M. Nikaeen
Keyword(s):  
Experimental Data ◽  
Aqueous Solutions ◽  
Structural Changes ◽  
Freundlich Isotherm ◽  
Isotherm Models ◽  
Ammonium Bromide ◽  
Order Kinetic ◽  
Multicomponent Adsorption ◽  
Benzene Toluene ◽  
Kinetic And Isotherm Models

Multicomponent adsorption of benzene, toluene, ethylbenzene, and xylene (BTEX) was assessed in aqueous solutions by montmorillonite modified with tetradecyl trimethyl ammonium bromide (TTAB-Mt). Batch experiments were conducted to determine the influences of parameters including loading rates of surfactant, contact time, pH, adsorbate concentration, and temperature on the adsorption efficiency. Scanning electron microscope (SEM) and X-ray diffractometer (XRD) were used to determine the adsorbent properties. Results showed that the modification of the adsorbent via the surfactant causes structural changes of the adsorbent. It was found that the optimum adsorption condition achieves with the surfactant loading rate of 200% of the cation exchange capacity (CEC) of the adsorbent for a period of 24 h. The sorption of BTEX by TTAB-Mt was in the order ofB<T<E<X. The experimental data were fitted by many kinetic and isotherm models. The results also showed that the pseudo-second-order kinetic model and Freundlich isotherm model could, respectively, be fitted to the experimental data better than other available kinetic and isotherm models. The thermodynamic study indicated that the sorption of BTEX with TTAB-Mt was achieved spontaneously and the adsorption process was endothermic as well as physical in nature. The regeneration results of the adsorbent also showed that the adsorption capacity of adsorbent after one use was 51% to 70% of original TTAB-Mt.

scholarly journals Conditions chimiques contrôlant l'atténuation naturelle des BTEX et solvants chlorés : un état des connaissances

2005 ◽  
Vol 14 (4) ◽  
pp. 419-444 ◽  
Author(s):  
O. Atteia ◽  
M. Franceschi
Keyword(s):  
Cette Technique ◽  
Ethyl Benzene ◽  
Benzene Toluene

L'atténuation naturelle des BTEX (Benzène, Toluène, Ethyl-benzène, Xylène) et des solvants chlorés est de plus en plus étudiée en raison des potentialités offertes par cette technique de gestion. Cet article, après avoir présenté les aspects abiotiques de l'atténuation détaille les conditions chimiques nécessaires à la réalisation des réactions de biodégradation des polluants organiques. Les aspects thermodynamiques sont abordés afin de décliner les réactions possibles et celles qui ne le sont pas selon les environnements chimiques. La dégradation des BTEX est focalisée sur le benzène, produit le plus toxique et le moins dégradable sur la plupart des sites. Les détails de la dégradation du benzène sur le terrain sont analysés dans la littérature et leur comparaison permet de décrire les mécanismes responsables de celle-ci. Dans le cas des solvants chlorés, l'attention est portée sur le TCE (Trichloréthylène), produit le plus couramment rencontré sur les sites pollués. Une mise en parallèle des évolutions de teneurs observées et des conditions chimiques locales permet de mettre en évidence les conditions nécessaires à la dégradation du TCE, et de ses congénères, ainsi que les cinétiques de dégradation dans différentes conditions. La mise en évidence du rôle prépondérant des conditions chimiques conduit à remettre en cause l'utilisation répandue des constantes de dégradation du premier ordre et donne des pistes pour les modèles nécessaires à une prédiction plus fine de l'atténuation naturelle.

scholarly journals Effects of Gum Arabic-Coated Magnetite Nanoparticles on the Removal of Pb Ions from Aqueous Solutions

2021 ◽  
pp. 889-896
Author(s):  
Hanan J. Mustafa ◽  
Tagreed M. Al-Saadi
Keyword(s):  
Aqueous Solutions ◽  
Crystallite Size ◽  
Magnetite Nanoparticles ◽  
Gum Arabic ◽  
Xrd Analysis ◽  
Sem Analysis ◽  
Absorption Bands ◽  
X Ray ◽  
Ft Ir ◽  
Pb Ions

To study the removal of lead (Pb) ions from aqueous solutions, novel magnetite nanoparticles (NPs) of Ni0.31Mg0.15Ag0.04Fe2.5O4 were synthesized by coprecipitation synthesis using metal sulfates, and then coated with Gum Arabic (GA). The prepared NPs were analyzed using various spectroscopic and analytical methods, such as X-Ray diffraction analysis (XRD), Field Emission Scanning Electron Microscopy (FE-SEM), Energy Dispersive X-ray spectroscopy (EDX), Fourier Transform Infra-Red spectroscopy (FT-IR), and Atomic Absorption Spectrophotometer (AAS). By using XRD analysis, the cubic inverse spinel structure of the prepared NPs was proven, showing average values of crystallite size, lattice constant, and density of 28.57nm, 8.32582Å, and 5.2890 g/cm3, respectively. FE-SEM analysis revealed the sphere-like shape of the nanoparticles with a measured crystallite size of 25.93nm. The existence of constituent elements was evidenced by EDX. FT-IR test proved the success of the coating process of magnetite NPs by the presence of the main characteristic absorption bands of GA in the FT-IR spectrum of GA-magnetite NPs. The adsorption of Pb ions by GA- magnetite NPs was shown by AAS analysis, where the concentration of Pb ions decreased from 25ppm to 6.6ppm, reaching 1.1ppm at the time of 25min. The porosity of the NPs and the carboxyl groups in GA played an important role in the process.

scholarly journals Synthesis, characteristics, and photocatalytic activity of zinc oxide nanoparticles stabilized on the stone surface for degradation of metronidazole from aqueous solution

2021 ◽  
Vol 8 (1) ◽  
pp. 55-63
Author(s):  
Amir Nasser Alibeigi ◽  
Neda Javid ◽  
Majid Amiri Gharaghani ◽  
Zhila Honarmandrad ◽  
Fatemeh Parsaie
Keyword(s):  
Zinc Oxide ◽  
Removal Efficiency ◽  
Zno Nanoparticles ◽  
Advanced Oxidation Process ◽  
Degradation Kinetics ◽  
Hexagonal Wurtzite Structure ◽  
Sem Analysis ◽  
Thermal Method ◽  
Average Crystalline Size ◽  
Stone Surface

Background: The presence of antibiotics such as metronidazole in wastewater even at low concentrations requires searching for a suitable process such as advanced oxidation process (AOP) to reduce the level of pollutants to a standard level in water. Methods: In this study, zinc oxide (ZnO) nanoparticles were synthesized by thermal method using zinc sulfate (ZnSO4 ) as a precursor, then, stabilized on stone and was used as a catalyst, in order to degrade metronidazole by photocalytic process. Effective factors on the removal efficiency of metronidazole including the initial metronidazole concentration, contact time, pH, and 0.9 gL-1 ZnO stabilized on the stone surface were investigated. Results: The X-ray diffraction (XRD) studies showed that the synthesized nanomaterials have hexagonal Wurtzite structure. Also, scanning electron microscopy (SEM) analysis revealed that the average crystalline size of the synthesized ZnO particles was in the range of 1.9-3.2 nm. The spectra represented a sharp absorption edge at 390 nm for ZnO nanoparticles corresponding to band gap of 3.168 eV. The BET-BJH specific surface area of the synthesized ZnO nanoparticles was 25.504 m2 /g. The EDS spectrum of ZnO nanoparticles showed four peaks, which were identified as Zn and O. The maximum removal efficiency was 98.36% for the synthetic solution under a specific condition (pH = 11, reaction time = 90 minutes, ZnO concentration = 0.9 gL-1, and the initial concentration of metronidazole = 10 mgL-1). The photocatalytic degradation was found to follow pseudo-first-order degradation kinetics. Conclusion: Therefore, the ZnO nanoparticles synthesized by thermal decomposition are suitable and effective photocatalytic materials for degradation of pharmaceutical contaminants.

scholarly journals Electrochemical oxidation of sulfamethoxazole using Ti/SnO2-Sb/Co-PbO2 electrode through ANN-PSO

2019 ◽  
Vol 84 (7) ◽  
pp. 713-727 ◽  
Author(s):  
Jiteng Wan ◽  
Chunji Jin ◽  
Banghai Liu ◽  
Zonglian She ◽  
Mengchun Gao ◽  
...  
Keyword(s):  
Aqueous Solution ◽  
Electrochemical Oxidation ◽  
Removal Efficiency ◽  
Current Density ◽  
Ph Value ◽  
Ann Model ◽  
Solution Ph ◽  
Pbo2 Electrode ◽  
Artificial Neural Network Ann ◽  
Major Factors

Even in a trace amounts, the presence of antibiotics in aqueous solution is getting more and more attention. Accordingly, appropriate technologies are needed to efficiently remove these compounds from aqueous environments. In this study, we have examined the electrochemical oxidation (EO) of sulfamethoxazole (SMX) on a Co modified PbO2 electrode. The process of EO of SMX in aqueous solution followed the pseudo-first-order kinetics, and the removal efficiency of SMX reached the maximum value of 95.1 % within 60 min. The effects of major factors on SMX oxidation kinetics were studied in detail by single-factor experiments, namely current density (1?20 mA cm-2), solution pH value (2?10), initial concentration of SMX (10?500 mg L-1) and concentration of electrolytes (0.05?0.4 mol L-1). An artificial neural network (ANN) model was used to simulate this EO process. Based on the obtained model, particle swarm optimization (PSO) was used to optimize the operating parameters. The maximum removal efficiency of SMX was obtained at the optimized conditions (e.g., current density of 12.37 mA cm-2, initial pH value of 4.78, initial SMX concentration of 74.45 mg L-1, electrolyte concentration of 0.24 mol L-1 and electrolysis time of 51.49 min). The validation results indicated that this method can ideally be used to optimize the related parameters and predict the anticipated results with acceptable accuracy.

scholarly journals Evaluation of Malathion Pesticide Removal Efficiency by g-C3N4/ Fe3O4/Ag Nanocomposites from Aqueous Solutions in the Presence of UV Irradiation

2020 ◽  
Vol 7 (3) ◽  
pp. 261-279
Author(s):  
Ali Esrafili ◽  
Soudabeh Ghodsi ◽  
Roshanak Rezaei Kalantary ◽  
Mitra Gholami ◽  
◽  
...  
Keyword(s):  
Aqueous Solutions ◽  
Removal Efficiency ◽  
Uv Irradiation ◽  
Pesticide Removal
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