AIMC Topic: Water Purification

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Effective Removal of Selenium from Aqueous Solution using Iron-modified Dolochar: A Comprehensive Study and Machine Learning Predictive Analysis.

Environmental research
Selenium (Se) is an essential micronutrient for human beings, but excess concentration can lead to many health issues and degrade the ecosystem. This study focuses on the removal of selenium from an aqueous solution using iron-doped dolochar. SEM, ED...

Unveiling the role of artificial intelligence in tetracycline antibiotics removal using UV/sulfite/phenol advanced reduction process.

Journal of environmental management
UV/sulfite-based advanced reduction processes (ARP) have attracted increasing attention due to their high capability for removing a wide range of pollutants. Therefore, developing UV/sulfite ARP systems with assisted Artificial Intelligence (AI) mode...

Evaluation of enhanced chemical coagulation method for a case study on colloidal liquid particle in wastewater treatment: Statistical optimization analysis and implementation of machine learning.

Journal of environmental management
Coal mines are one of the largest sources of energy supply and generate significant volumes of wastewater. Chemical coagulation is one of the most effective methods for wastewater treatment. In this research, ferric and aluminum-based coagulants, alo...

Predicting the performance of lithium adsorption and recovery from unconventional water sources with machine learning.

Water research
Selective lithium (Li) recovery from unconventional water sources (UWS) (e.g., shale gas waters, geothermal brines, and rejected seawater desalination brines) using inorganic lithium-ion sieve (LIS) materials can address Li supply shortages and distr...

Application and innovation of artificial intelligence models in wastewater treatment.

Journal of contaminant hydrology
At present, as the problem of water shortage and pollution is growing serious, it is particularly important to understand the recycling and treatment of wastewater. Artificial intelligence (AI) technology is characterized by reliable mapping of nonli...

Machine learning-driven prediction of phosphorus adsorption capacity of biochar: Insights for adsorbent design and process optimization.

Journal of environmental management
Phosphorus (P) pollution in aquatic environments poses significant environmental challenges, necessitating the development of effective remediation strategies, and biochar has emerged as a promising adsorbent for P removal at the cost of extensive re...

Machine learning models for predicting the rejection of organic pollutants by forward osmosis and reverse osmosis membranes and unveiling the rejection mechanisms.

Water research
While forward osmosis (FO) and reverse osmosis (RO) processes have been proven effective in rejecting organic pollutants, the rejection rate is highly dependent on compound and membrane characteristics, as well as operating conditions. This study aim...

Refining hydrogel-based sorbent design for efficient toxic metal removal using machine learning-Bayesian optimization.

Journal of hazardous materials
Hydrogel-based sorbents show promise in the removal of toxic metals from water. However, optimizing their performance through conventional trial-and-error methods is both costly and challenging due to the inherent high-dimensional parameter space ass...

Deep learning artificial neural network framework to optimize the adsorption capacity of 3-nitrophenol using carbonaceous material obtained from biomass waste.

Scientific reports
The presence of toxic chemicals in water, including heavy metals like mercury and lead, organic pollutants such as pesticides, and industrial chemicals from runoff and discharges, poses critical public health and environmental risks leading to severe...

Synthesis and characterization of Fe(III)-doped beta-cyclodextrin-grafted chitosan cryogel beads for adsorption of diclofenac in aqueous solutions: Adsorption experiments and deep-learning modeling.

International journal of biological macromolecules
Diclofenac (DCF) is frequently detected in aquatic environments, emphasizing the critical need for its efficient removal globally. Here, we present the synthesis of Fe(III)-doped β-CD-grafted chitosan (Fe/β-CD@CS) cryogel beads designed for adsorbing...