Sadaf Zaidi

Zeolites as Inorganic Ion Exchangers for Environmental Applications: An Overview

Zeolites are rendering important service in areas crucial for the sustenance of modern civilization. Their attractive attributes of ion exchange, adsorption, dehydration-rehydration, and catalysis make their use invaluable in a number of applications of great significance. In this chapter, starting with the current understanding of the general aspects of zeolites, an attempt has been made to provide an overview to the reader about the role of zeolites as inorganic ion exchangers for environmental applications. In this regard, the developments in the use of zeolites for water and wastewater treatment, detergent building, and radionuclide separation have been reviewed.

Support Vector Regression Prediction and Analysis of the Copper (II) Biosorption Efficiency

Abstract Support vector regression (SVR) has been used for the prediction of biosorption efficiency of Cu(II) using litter of natural trembling poplar (Populus tremula) forest (LNTPF) as a low-cost biosorbent. The proposed SVR model has been compared with the most widely used multiple linear regression (MLR) model based on statistical parameters for the unseen test data set in terms of coefficient of determination (R2), average absolute relative error, root mean square error and standard deviation. The SVR-based model is found to be superior to the MLR model. The effect of various parameters (adsorbent concentration, pH, particle size, initial Cu(II) concentration, agitating speed and temperature) on the Cu(II) biosorption efficiency using the SVR-based model has also been studied. The simulation results of the SVR-based model agree appreciably with the available experimental results. This novel application of SVR can be successfully applied to model other such systems with good accuracy and high generalization ability.

An Improved Restarted Adomian-based Solution for the Minimum Reflux Ratio of Multicomponent Distillation Columns

Abstract An improved version of powerful Adomian decomposition method (ADM), namely Restarted Adomian decomposition method (RADM), has been employed to find the roots of Underwood’s equations. Underwood’s equations frequently appear in the design of multi-component distillation columns and are used to get a quick estimate of minimum reflux ratio. However, due to highly nonlinear nature and presence of singularities, these equations pose convergence-related difficulties. In this communication, it is shown that RADM is not only capable of overcoming these difficulties but also the values of residual errors show that the RADM-based solutions are superior to the recently developed ADM-based solutions as well as to those obtained by using the well-known Newton–Raphson method. Besides, unlike ADM, the proposed RADM does not require convergence accelerators such as Shanks transformation and only few terms are needed to get the accurate results.