Abstract
Industrial dye wastewater is one of the major water pollution problems. Adsorbent materials are promising strategies for the removal of water dye contaminants. Herein, we provide a statistical and artificial intelligence study to evaluate the adsorption efficiency of graphene oxide-based hydrogels in wastewater dye removal by applying Principal Component Analysis (PCA). This study aims to assess the adsorption quality of 35 different hydrogels. We adopted different approaches and showed the pros and cons of each one of them. PCA showed that alginate graphene oxide-based hydrogel (without polyvinyl alcohol) had better tolerance in a basic medium and provided higher adsorption capacity. Polyvinyl alcohol sulfonated graphene oxide-based hydrogels are suitable when higher adsorbent doses are required. In conclusion, PCA represents a robust way to delineate factors affecting hydrogel selection for pollutant removal from aqueous solutions.
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