AIMC Topic: Water Pollutants, Chemical

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Sensitivity-driven control strategy and analysis of operating parameter MLSS in the stacking total nitrogen prediction model.

Environmental monitoring and assessment
The operation of wastewater treatment plants (WWTPs) is frequently characterized by complexity, largely attributable to the properties of the influent and the nonlinear fluctuations that occur throughout the wastewater treatment process. Accurate mod...

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...

Machine learning-based prediction of drinking water quality index in Western Tehran using KAN, MLP, and traditional models.

Environmental monitoring and assessment
In this study, the water quality index (WQI) was calculated using multivariate statistics, incorporating physical, chemical, and microbiological analysis of water samples taken from water supply networks in the western district of Tehran from 2021 to...

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...

River water quality forecasting: a novel LSTM-Transformer approach enhanced by multi-source data.

Environmental monitoring and assessment
Water quality prediction holds crucial importance as a fundamental technical support for efficient water resource management and strong ecological protection. In this study, aiming to meet the pressing requirement for eutrophication prevention and co...

Phosphorus removal and recovery in wastewater biological treatment from the perspective of phosphine: Current status, action mechanisms and future potential.

The Science of the total environment
This work presents a comprehensive review of phosphorus removal and resource recovery driven by phosphine (PH) in biological wastewater treatment processes, with a particular focus on PH generation. Through a bibliometric analysis using VOSviewer and...

Simulation, prediction and optimization of heavy metal adsorption by metal-organic frameworks with machine learning.

Environmental research
The unique structures and complex characteristics of Metal-organic frame (MOFs) obscure understanding the processes and mechanisms of heavy metal (HM) removal. This study established an interpretable machine learning (ML) framework predicting adsorpt...

Integrated deep eutectic solvent with amorphous metal-organic framework for highly sensitive electrochemical determination of dicofol in milk and water.

Food chemistry
High-throughput screening of deep eutectic solvents (DESs) was performed using artificial intelligence/quantum mechanical models. Ni-amorphous metal-organic frameworks (aMOFs) was synthesized through amine-DES aqueous solution. The target-specific DE...

Machine learning-assisted triple-emission Ln-MOFs sensor array for detection of multiple PFCs in aqueous environments.

Biosensors & bioelectronics
Perfluorinated compounds (PFCs) are persistent environmental pollutants with potential carcinogenicity, posing a major threat to ecosystems and human health. Rapid identification of PFCs in complex environmental matrices remains challenging due to th...

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...