STUDIA UBB CHEMIA, LXIV, 2,Tom I, 2019 (p. 139-157) (RECOMMENDED CITATION) DOI:10.24193/subbchem.2019.2.12 Dedicated to Professor Florin Dan Irimie on the Occasion of His 65 th Anniversary MATHEMATICAL MODELLING AND PREDICTION OF CONGO RED ADSORPTION ON CHERRY STONES ACTIVATED CARBON ANDREI SIMION a , CRISTINA GRIGORAȘ a* , LIDIA FAVIER b , LUCIAN GAVRILĂ a* ABSTRACT. The present paper was aimed to establish mathematical models useful to reduce the time required to discover the appropriate adsorption conditions of Congo Red (an intensively used organic dye) on an activated carbon prepared from cherry stones through calcination. To this purpose, various values of three parameters known as influencing the process, namely dye initial concentration (200 mg/L to 1000 mg/L), pH (2 to 12) and contact time (10 to 180 minutes) between the adsorbent and the adsorbate were variated. The recorded results of the adsorption process were used as data for Response Surface Methodology and Artificial Neural Network and several mathematical equations were generated. The conducted statistical analyses revealed that these equations can accurately express the Congo Red elimination from aqueous solutions. Moreover, the developed procedure is able to predict the process evolution in different conditions than those experimentally tested. Keywords: Adsorption, Artificial Neural Network, cherry stone, Congo Red, mathematical modelling, Response Surface Methodology, water treatment INTRODUCTION Colored wastewater coming from various industries is considered a major source of environmental concerns. Besides being responsible for the unwanted visual effect, due to their chemical structures, dyes are often characterized by a reduced biodegradability being difficult to remove by classical wastewater treatments [1]. Moreover, most of the dyes can also negatively affect a “Vasile Alecsandri” University of Bacău; Faculty of Engineering; Department of Food and Chemical Engineering; Calea Mărășești 157, RO-600115, Bacău, România b Univ. Rennes, Ecole Nationale Supérieure de Chimie de Rennes; CNRS, UMR 6226; 11 Allée de Beaulieu, CS 50837, 35708 Rennes Cedex 7, France *Corresponding authors: cristina.grigoras@ub.ro, lgavrila@ub.ro