AIMC Topic: Water Purification

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Floc image-driven deep learning enhanced by temporal windows and transformers for carbon emission reduction in drinking water treatment plants.

Water research
Using machine learning (ML) and deep learning (DL) algorithms for precise coagulant dosing in drinking water treatment plants (DWTPs) helps ensure drinking water safety and supports greenhouse gas (GHG) emission reduction. The effectiveness of these ...

Integrating AI-based neural network modeling with experimental characterization for Cd(II) ion adsorption using Sargassum fusiforme biosorbent.

Environmental research
Cadmium (Cd) contamination in wastewater presents serious environmental and public health challenges, requiring efficient mitigation strategies. This research focuses on assessing the biosorption capability of Sargassum fusiforme (SF) biosorbent for ...

Bridging Dissolved Organic Matter Reactivity to Ozonation Catalysts for Cu@AlO from the Molecular Level by Machine Learning.

Environmental science & technology
Catalytic ozonation is a widely used advanced oxidation process for treating refractory organic wastewater; yet, the variability in dissolved organic matter (DOM) composition complicates reaction mechanisms. A critical challenge lies in designing opt...

A machine learning model guided by physical principles for biofilter performance prediction.

Scientific reports
Despite the critical role of biofilters in water quality and sustainability, predicting their performance remains challenging due to the complexity of microbial interactions and limitations of sparse, high-dimensional datasets. Here, we introduce Env...

Regression model and artificial neural network model to predict halonitromethane formation from amino acids during UV/monochloramine disinfection in bromide-containing real water.

Environmental pollution (Barking, Essex : 1987)
Halonitromethanes (HNMs) were high-toxicity nitrogenous disinfection byproducts generated by amino acids (AAs) during UV/monochloramine (UV/NHCl) disinfection in bromide-containing water. HNM concentrations fell over time, highlighting disinfection t...

Explainable machine learning for comprehensive characterization of poly (6-(Ethoxybenzothiazole acrylamide)) resin for removal of Th(IV), As(V), and Hg(II) ions from aqueous solution.

Environmental geochemistry and health
Adsorption is a promising technique with significant potential for water purification. In this context, the present study examines the adsorption efficiency of poly(6-(ethoxybenzothiazole acrylamide) (PEBTA) in removing high-valent metal ions from aq...

Comparative analysis of multiple machine learning models: identifying impact factors in biochar heavy metal adsorption mechanisms.

Environmental geochemistry and health
The contribution analysis of influencing factors governing biochar-mediated heavy metal adsorption in aqueous systems holds significant implications for cost-effective water remediation. Current studies predominantly rely on single-model approaches t...

Proof-of-concept evaluation at Cox's Bazar of the Safe Water Optimization Tool: water quality modelling for safe water supply in humanitarian emergencies.

BMJ global health
INTRODUCTION: Waterborne diseases are leading concerns in emergencies. Humanitarian guidelines stipulate universal water chlorination targets, but these fail to reliably protect water as postdistribution chlorine decay can leave water vulnerable to p...

A Machine Learning-Based Modeling Approach for Dye Removal Using Modified Natural Adsorbents.

Journal of chemical information and modeling
This study used machine learning models to investigate the potential of biosorbents derived from natural fruit seed waste (apricot, almond, and walnut) for removing a cationic dye. Levulinic acid (LA)-modified powders of almond shell (ASh), apricot k...

Conversion of ozone into hydroxyl radical by granular activated carbon with and without biofilms: Implications for micropollutant abatement.

Journal of hazardous materials
The transformation of ozone (O) into hydroxyl radical (OH) during the ozonation was evaluated in the presence of granular activated carbon (GAC) and biofilm-covered granular activated carbon (BGAC). While both GAC and BGAC accelerated O decomposition...