Studies on the Removal of Malachite Green from Its Aqueous Solution Using Water-Insoluble ß-Cyclodextrin Polymers.

The rising global pollution of natural waters by dyes has brought to light the need for adaptable and efficient removal techniques. To create water-insoluble ß-cyclodextrin (ß-CD) polymers like CA/-CD, TA/-CD, and MA/-CD, several organic acids including citric acid (CA), tartaric acid (TA), and malic acid (MA) were cross-linked with ß-cyclodextrin in this study. The obtained polymers were characterized by different advanced analytical techniques such as FTIR, SEM, and UV-vis spectrophotometry. Malachite green dye was removed from aqueous solutions using the synthesized polymers by adsorption. The adsorption investigation was conducted under several conditions, including pH, adsorbent mass, dye concentration, temperature, contact time, adsorption isotherm, and kinetics. The adsorbent CA/ß-CD shows the highest adsorption of MG dye in all of the conditions because it contains a high number of carboxyl groups. The negatively charged carboxyl ions of CA/ß-CD attract the positively charged MG dye electrostatically and remove MG from aqueous media with an efficiency of 91%. As a result, the findings indicated that water-insoluble polymers based on ß-cyclodextrin are well-suited as inexpensive adsorbents to remove colors from aqueous media.

Expanded DEMATEL for determining cause and effect group in bidirectional relations.

Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology has been proposed to solve complex and intertwined problem groups in many situations such as developing the capabilities, complex group decision making, security problems, marketing approaches, global managers, and control systems. DEMATEL is able to realize casual relationships by dividing important issues into cause and effect group as well as making it possible to visualize the casual relationships of subcriteria and systems in the course of casual diagram that it may demonstrate communication network or a little control relationships between individuals. Despite of its ability to visualize cause and effect inside a network, the original DEMATEL has not been able to find the cause and effect group between different networks. Therefore, the aim of this study is proposing the expanded DEMATEL to cover this deficiency by new formulations to determine cause and effect factors between separate networks that have bidirectional direct impact on each other. At the end, the feasibility of new extra formulations is validated by case study in three numerical examples of green supply chain networks for an automotive company.