AIMC Topic: Water Purification

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Machine learning-guided prediction of chlorinated/chloraminated disinfection by-product formation in drinking water treatment.

Water research
Chlorination and chloramination as common water disinfection methods are challenged by the unintended formations of hazardous disinfection by-products (DBPs). Accurately predicting DBP formation is essential for improving water treatment processes an...

Generative deep learning model assisted multi-objective optimization for wastewater nitrogen to protein conversion by photosynthetic bacteria.

Bioresource technology
For decades, the photosynthetic bacteria (PSB)-based nitrogen treatment and valorization from wastewater have been explored. However, balancing nitrogen removal performance and resource recovery potential in PSB has remained a key unresolved issue fo...

A Multi-Model Ensemble for Advanced Prediction of Reverse Osmosis Performance in Full-Scale Zero-Liquid Discharge Systems.

Environmental science & technology
The growing reliance on reverse osmosis (RO) in zero liquid discharge (ZLD) and seawater desalination has underscored membrane fouling as a critical challenge, requiring predictive tools for proactive management. This study proposes a novel multidime...

Performance analysis of machine learning algorithms for the prediction of disinfection byproducts formation during chlorination: Effect of background water characteristics.

Journal of environmental management
This study investigated the comparison of the nonlinear machine learning algorithms and linear regression models to predict the formation of trihalomethanes (THM4), haloacetic acids (HAA5 and HAA9), and haloacetonitriles (HAN4 and HAN6) under uniform...

Potential risks and hazards posed by the pressure of pharmaceuticals and personal care products on water treatment plants.

Environmental pollution (Barking, Essex : 1987)
Pharmaceuticals and personal care products (PPCPs) are widely used in various industrial and commercial products, contributing to their substantial presence in the environment. In recent years, numerous studies have focused on the environmental behav...

Electrochemical activation of alum sludge for the adsorption of lead (Pb(II)) and arsenic (As): Mechanistic insights and machine learning (ML) analysis.

Bioresource technology
Alum sludge (AlS) has emerged as an effective adsorbent for anionic contaminants, with traditional activation methods like acid/base treatments and calcination employed to enhance its adsorption capacity. However, these approaches encounter significa...

DFT-assisted machine learning for polyester membrane design in textile wastewater recovery applications.

Water research
Resource recovery from textile wastewater has attracted increasing interest because it simultaneously addresses wastewater treatment and maximizes the utilization of the residual dyes. Although polyester membranes have demonstrated great potential fo...

Machine Learning Reveals Key Adsorption Mechanisms for Oxyanions Based on Combination of Experimental and Published Literature Data.

Environmental science & technology
The development of new adsorbents for water treatment often involves complex adsorption mechanisms, whose individual contributions are unclear, thereby limiting the understanding of adsorption driving forces, making it difficult to achieve precise de...

Prediction of enhanced coagulation with varied pre-oxidations for seasonal variations of cyanobacteria-dominated algae-laden water quality.

Journal of environmental management
Enhanced coagulation with pre-oxidation is a cost-effective approach for managing seasonal water quality pollution caused by algal outbreaks and deaths. The synergistic application of pre-oxidants and coagulants, coupled with intelligent and precise ...

Chitosan-based adsorbents for remediation of toxic dyes from wastewater: A review on adsorption mechanism, reusability, machine learning based modeling and future perspectives.

International journal of biological macromolecules
The disposal of recalcitrant dyes in aquatic environments from various industrial sectors is a threat to both the plant and animal kingdom. The presence of dyes in various water bodies undermines the availability of uncontaminated drinking water and ...