scholarly journals Application of ANN to the Sorption Equilibrium Modelling of Heavy Metal Ions on Clinoptilolite

2012 ◽  
Vol 19 (2) ◽  
pp. 227-237 ◽  
Author(s):  
Elwira Tomczak ◽  
Wladyslaw Kaminski
Keyword(s):  
Heavy Metal ◽  
Metal Ions ◽  
Heavy Metal Ions ◽  
Sorption Isotherms ◽  
Initial Step ◽  
Training Data ◽  
Sorption Equilibrium ◽  
Network Training ◽  
Mineral Sorbent ◽  
Number Of Publications

Application of ANN to the Sorption Equilibrium Modelling of Heavy Metal Ions on Clinoptilolite The latest achievements in the field of mathematical modelling include the application of artificial neural networks (ANN). A growing interest in the ANN is confirmed by the number of publications devoted to the applicability of ANN in chemical, process and environmental engineering. A recent dynamic development of ANN provided an efficient and universal tool that is used to solve many tasks, including modelling, approximation and identification of objects. The initial step of applying the network to a given process consists in the determination of weights of the proposed neural network structure. This is performed on the basis of training data. A network that is properly trained allows correct information to be obtained on the basis of other data which have not been used in the network training. In most cases the network training is performed on the basis of a known mathematical model. However, the training of a network can be also performed using experimental data. In this paper, the sorption isotherms were predicted by means of a multilayer perceptron (MLP). Calculations were made using a training program written in Matlab, which took advantage of the Lavenberg-Marquardt procedure. In the last decade a growing interest is observed in inexpensive and very cheap adsorbents to remove heavy metal ions. Clinoptilolite is the mineral sorbent extracted in Poland used to remove heavy metal ions from diluted solutions. Equilibrium experiments were carried out to estimate sorptivity of a clinoptilolite and its selectivity towards Cu(II), Zn(II) and Ni(II) ions for multicomponent solution. Calculations with the use of MLP enabled description of sorption isotherms for one, two and three ions which were present at the same time in the solution. The network also enabled an analysis of sorption of the single ion, taking into account the effect of its concentration.

scholarly journals Mie scattering and microparticle-based characterization of heavy metal ions and classification by statistical inference methods

2019 ◽  
Vol 6 (5) ◽  
pp. 190001 ◽  
Author(s):  
Katherine E. Klug ◽  
Christian M. Jennings ◽  
Nicholas Lytal ◽  
Lingling An ◽  
Jeong-Yeol Yoon
Keyword(s):  
Heavy Metal ◽  
Support Vector Machine ◽  
Metal Ions ◽  
Heavy Metal Ions ◽  
Mie Scattering ◽  
Training Data ◽  
Scattering Data ◽  
Support Vector ◽  
Linear Discriminant ◽  
Machine Analysis

A straightforward method for classifying heavy metal ions in water is proposed using statistical classification and clustering techniques from non-specific microparticle scattering data. A set of carboxylated polystyrene microparticles of sizes 0.91, 0.75 and 0.40 µm was mixed with the solutions of nine heavy metal ions and two control cations, and scattering measurements were collected at two angles optimized for scattering from non-aggregated and aggregated particles. Classification of these observations was conducted and compared among several machine learning techniques, including linear discriminant analysis, support vector machine analysis, K-means clustering and K-medians clustering. This study found the highest classification accuracy using the linear discriminant and support vector machine analysis, each reporting high classification rates for heavy metal ions with respect to the model. This may be attributed to moderate correlation between detection angle and particle size. These classification models provide reasonable discrimination between most ion species, with the highest distinction seen for Pb(II), Cd(II), Ni(II) and Co(II), followed by Fe(II) and Fe(III), potentially due to its known sorption with carboxyl groups. The support vector machine analysis was also applied to three different mixture solutions representing leaching from pipes and mine tailings, and showed good correlation with single-species data, specifically with Pb(II) and Ni(II). With more expansive training data and further processing, this method shows promise for low-cost and portable heavy metal identification and sensing.

scholarly journals Sorption performance of cysteine-modified bentonite in heavy metals uptake

2009 ◽  
Vol 74 (7) ◽  
pp. 833-843 ◽  
Author(s):  
Hossein Faghihian ◽  
Massoud Nejati-Yazdinejad
Keyword(s):  
Heavy Metal ◽  
Metal Ions ◽  
Metal Binding ◽  
Heavy Metal Ions ◽  
Sorption Isotherms ◽  
Local Clay ◽  
Lead And Cadmium ◽  
Sorption Parameters ◽  
Thiol Ligand ◽  
Heavy Metals Uptake

A local clay, bentonite (N-Ben), was modified by the biologically-based ligand, cysteine (Cys), through a simple sorption technique. The modified sorbent (Cys-Ben) demonstrated affinity for soft and moderately soft heavy metal ions (HMI), such as Cd(II) and Pb(II), probably as a result of the soft basic character of the thiol ligand side chains. The resulting modified system was effective for metal binding with capacities of 0.503 and 0.525 mmol g-1, for Pb(II) and Cd(II), respectively. Comparative batch experiments were performed for removing lead and cadmium from aqueous solutions. The sorption parameters were derived from a Langmuir fit to the sorption isotherms of the studied ions. The study showed that the sorption capacity of Cys-Ben was higher than that of N-Ben for these ions. The effect of pH was examined over the range 2.0-6.0. The sorption capacities of Cys-Ben showed that this modified clay is a good sorbent for the examined heavy metal ions.

The Studies of Adsorption of Heavy Metal Ions of Lead and Copper by Distillers' Grains

2011 ◽  
Vol 695 ◽  
pp. 77-80 ◽  
Author(s):  
Juan Feng ◽  
Xiao Yan Lin ◽  
Xue Gang Luo ◽  
Jia Quan Rao ◽  
Chun Yan Zhang
Keyword(s):  
Heavy Metal ◽  
Metal Ions ◽  
Heavy Metal Ions ◽  
Removal Rate ◽  
Structural Characteristics ◽  
Sorption Isotherms ◽  
Distillers Grains ◽  
Sorption Data ◽  
Adsorption Behaviors ◽  
Heavy Metal Wastewater

The absorption of Cu2+ and Pb2+ in the heavy metal wastewater by distillers' grains can not only solve the problem of environmental pollution, but also change distillers' grains waste into resource. Structural characteristics of distillers' grains and its adsorption behaviors for the heavy metal ions of Cu2+ and Pb2+ were studied and effects of various parameters including pH, temperature, distillers' grains dose, initial Cu2+ and Pb2+ concentration and absorbed time on the absorption of Pb2+ and Cu2+ were evaluated. Sorption isotherms were also investigated. Results show that the rough surface, loose internal structure and hydroxy and amide groups of the distillers' grains are beneficial to the adsorption of Cu2+ and Pb2+ in the wastewater. The removal rate of the distillers' grains for Pb2+ (20.00 mg L−1) and Cu2+ (20.00 mg L−1) are, respectively, 96.72% and 87.70% under optimized conditions. The equilibrium sorption data are well demonstrated by Langmuir model.

scholarly journals Water purification from heavy metal ions by nano-sized Fe0/kaolinite composites

2020 ◽  
pp. 96-103
Author(s):  
I.A. Kovalchuk ◽  
◽  
V.Yu. Tobilko ◽  
A.I. Bondarieva ◽  
Yu.M. Kholodko ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Metal Ions ◽  
Heavy Metal Ions ◽  
Sorption Isotherms ◽  
Active Surface ◽  
Toxic Heavy Metal ◽  
Physicochemical Features ◽  
Sorbent Materials ◽  
Effective Sorbent ◽  
Sorption Characteristics

We have investigated the physicochemical features of the purification of wastewater that are complex on its content and include a mixture of heavy metal ions (Cu(II), Cd(II), Zn(II), Co(II), Cr(VI)). The phase of a composition and structural-sorption characteristics of synthesized nano-sized Fe0/kaolinite composites were studied. It was found that the obtained materials have much better sorption properties for the extraction of heavy metals from aqueous solutions in comparison with natural kaolinite. Calculations of sorption isotherms according to the Freundlich equation are done. Based on isotherms, the average values of specific sorption per unit of an active surface of the mineral at the content of heavy metal ions in the initial solutions of 300 μmol/dm3 were determined. They range from 0.42 to 17.1 μmol/g for Cr(VI) to Cu(II) ions. It has also been found that similar values for the modified samples are much larger and range from 13.8 to 80.27 μmol/g for ions from Cr(VI) to Cu(II). It is shown that composite sorbents based on nano-sized zero-valent iron and dispersed kaolinite silicate are effective sorbent materials for the purification of water contaminated with toxic heavy metal ions that are commonly found in wastewater of the galvanic and hydrometallurgical industries.

Bioadsorption of Multiple Heavy Metal Ions by Rhizophora Apiculate sp. and Elaesis Guineensis sp.

2017 ◽  
Vol 14 (1) ◽  
pp. 15
Author(s):  
M.B. Nicodemus Ujih ◽  
Mohammad Isa Mohamadin ◽  
Milla-Armila Asli ◽  
Bebe Norlita Mohammed
Keyword(s):  
Heavy Metal ◽  
Metal Ions ◽  
Removal Efficiency ◽  
Heavy Metal Ions ◽  
Agricultural Waste ◽  
Living Organism ◽  
Heavy Metal Concentration ◽  
Industrial Area ◽  
Electrochemical Treatment ◽  
Chemical Oxidation

Heavy metal ions contamination has become more serious which is caused by the releasing of toxic water from industrial area and landfill that are very harmful to all living organism especially human and can even cause death if contaminated in small amount of heavy metal concentration. Currently, peoples are using classic method namely electrochemical treatment, chemical oxidation/reduction, chemical precipitation and reverse osmosis to eliminate the metal ions from toxic water. Unfortunately, these methods are costly and not environmentally friendly as compared to bioadsorption method, where agricultural waste is used as biosorbent to remove heavy metals. Two types of agricultural waste used in this research namely oil palm mesocarp fiber (Elaesis guineensis sp.) (OPMF) and mangrove bark (Rhizophora apiculate sp.) (MB) biomass. Through chemical treatment, the removal efficiency was found to improve. The removal efficiency is examined based on four specification namely dosage, of biosorbent to adsorb four types of metals ion explicitly nickel, lead, copper, and chromium. The research has found that the removal efficiency of MB was lower than OPMF; whereas, the multiple metals ions removal efficiency decreased in the order of Pb2+ > Cu2+ > Ni2+ > Cr2+.

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