Determination of best-fit isotherm model for the sorption of Lead (II) and Manganese (II) ions onto acid-activated shale using selected non-linear error functions

The focus of this research is to apply the selected error function equation to establish the equilibrium isotherm model that best describes the adsorption of Pb2+ and Mn2+ onto acid-activated shale. Data collected from the batch experiment were analyzed using selected isotherm models (Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Sips and Redlich-Peterson). To compute the isotherm parameters used in choosing the best-fit isotherm model, selected non-linear error functions, namely, error sum of the square, normalized standard deviation, hybrid error function, root mean square error and Marquardt’s percent standard deviation were employed. From the scanning electron microscope results, it was observed that the surface characteristics of the shale change considerably with calcination and acid treatment but the acid-treated shale shows better uneven porous surface characteristics. Error function computation shows that the Dubinin-Radushkevich isotherm model had the least sum of normalized error of 0.3623 for Pb2+ adsorption and 0.5465 for Mn2+ adsorption; hence, it was selected as the best isotherm model for explaining the sorption of Pb(II) and Mn(II) ions unto acid-activated shale.

Mathematical Modeling of Sorption on Novel Sorbent Materials

<p>The emission of metal ions in the environment has increased in recent times and since metal ions are not biodegradable, they belong to the cumulative toxins. Contamination of the environment with metal ions poses a serious danger to the entire ecosystem, agricultural production, quality of food and water, as well as to the health of humans and animals. This study investigates sorption as one of the processes which can be used for pollutants removal and efficiency of certain sorbent materials. Specifically, we focus on development and validation of non-linear Langmuir model and non-linear Freundlich model. Their application in sorption experiments is examined by applying different error functions and statistical methods which are employed to calculate the error divergence between observed data and predicted data of sorbate-sorbent system. Presented non-linear sorption models are developed by using programming language Fortran, and the data analysis is obtained by using different tools and packages in programming language R. Many authors are using linear sorption models in the way that they would linearize non-linear sorption models. It is evident that linear sorption models are used due to their simplicity in parameters estimation. We use approach of trying different algorithms and tools in programming language R in order to find the best objective function. This study shows that both non-linear Langmuir model and non-linear Freundlich model can be used for experimental data representation. The results also denote that better estimation and the better fit is given by Langmuir model due to divergence in error functions and graphical representation itself. The choice of sorption model has a great influence on the prediction of solute transfer and great care should be taken in selection of convenient approach.</p>

Searching for optimum adsorption curve for metal sorption on soils: comparison of various isotherm models fitted by different error functions

Studies comparing numerous sorption curve models and different error functions are lacking completely for soil-metal adsorption systems. We aimed to fill this gap by studying several isotherm models and error functions on soil-metal systems with different sorption curve types. The combination of fifteen sorption curve models and seven error functions were studied for Cd, Cu, Pb, and Zn in competitive systems in four soils with different geochemical properties. Statistical calculations were carried out to compare the results of the minimizing procedures and the fit of the sorption curve models. Although different sorption models and error functions may provide some variation in fitting the models to the experimental data, these differences are mostly not significant statistically. Several sorption models showed very good performances (Brouers-Sotolongo, Sips, Hill, Langmuir-Freundlich) for varying sorption curve types in the studied soil-metal systems, and further models can be suggested for certain sorption curve types. The ERRSQ error function exhibited the lowest error distribution between the experimental data and predicted sorption curves for almost each studied cases. Consequently, their combined use could be suggested for the study of metal sorption in the studied soils. Besides testing more than one sorption isotherm model and error function combination, evaluating the shape of the sorption curve and excluding non-adsorption processes could be advised for reliable data evaluation in soil-metal sorption system.

Application of the Efros Theorem to the Function Represented by the Inverse Laplace Transform of s−μ exp(−sν)

Using a special case of the Efros theorem which was derived by Wlodarski, and operational calculus, it was possible to derive many infinite integrals, finite integrals and integral identities for the function represented by the inverse Laplace transform. The integral identities are mainly in terms of convolution integrals with the Mittag–Leffler and Volterra functions. The integrands of determined integrals include elementary functions (power, exponential, logarithmic, trigonometric and hyperbolic functions) and the error functions, the Mittag–Leffler functions and the Volterra functions. Some properties of the inverse Laplace transform of s−μexp(−sν) with μ≥0 and 0<ν<1 are presented.