The preparation of an alternative material for the adsorption of arsenic from aqueous
solution was studied. This adsorbent was obtained from the pyrolysis and ZnCl 2 activation …

Arsenic in drinking water has been recognized as a serious community health problem
because of its toxic nature and therefore, its removal is highly essential. A series of …

Arsenic contamination is a global problem, as it affects the health of millions of people. For
this study, data-driven artificial neural network (ANN) software was developed to predict and …

Arsenic contaminations of groundwater in several parts of the world are the results of natural
and/or anthropogenic sources, and have a large impact on human health. Millions of people …

The application of artificial neural networks on adsorption modeling has significantly
increased during the last decades. These artificial intelligence models have been utilized to …

The estimation capacities of two optimization methodologies, response surface methodology
(RSM) and artificial neural network (ANN) were evaluated for prediction of biosorptive …

Arsenic is a deleterious heavy metal that is usually removed from polluted water based on
adsorption processes. The latest mode of modeling such a process is to implement artificial …

Batch and column operations were performed utilizing thioglycolated sugarcane carbon
(TSCC), a low-cost adsorbent, to remove As (III) and As (V) from aqueous systems. Under …

In this study, the co-precipitation method was used to synthesize the cerium oxide
tetraethylenepentamine (CTEPA) hybrid material with the variation of the molar …

Ordered mesoporous Al 2 O 3 and Fe-Al 2 O 3 materials were synthesized at room
temperature by an easy and environmentally friendly self-assembly sol-gel route, to be …