Mechanistic Coupling of Coagulation-Flocculation, and Machine Learning for Removal of Various Contaminants from Water System

Abstract

Water is the most precious compound on the earth. Presence of different pollutants in water is a major cause of pollution. Numerous materials and technologies have been used to remove these pollutants from the water supply. Access to safe water for everyone is the prime aim of sustainable development goal six. To do this, numerous materials and technologies have been created. Coagulation-flocculation and adsorption are the prime steps for treatment of wastewater. Coagulation-flocculation is done in tandem to counter the stabilizing force present to disturb the suspended particles' impurities and toxic materials, so as to allow collision of particles and lead to growth of flocs. Acute and chronic illnesses in humans can result from heavy metal ion concentrations that are higher than advised. Adsorption is effectively applied techniques for removal of these heavy metals and rest of the materials present in water. Machine learning helps to analyze the contaminants in water to develop a suitable technique and materials for removal of contaminants from water. The aim of this paper is to couple the coagulation-flocculation, and machine learning techniques together for removal of all contaminants from the water system and explain the mechanism which helps to know the chemical interaction.