AIMC Topic: Adsorption

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Activated biochar production from young coconut waste (Cocos nucifera) as bioadsorbent: a pathway through Artificial Neural Network (ANN) optimization.

Environmental monitoring and assessment Sep 20, 2024
This pioneering work explores the immense potential of young coconut waste, a continuously marginalized residue of the food and beverage industry, to serve as an indispensable feedstock in the production of biochar. Through an examination of the key ...
Cocos Adsorption Charcoal Neural Networks, Computer
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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 Sep 16, 2024
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...
Iron Kinetics Water Pollutants, Chemical Adsorption Hydrogen-Ion Concentration Machine Learning Water Purification Selenium
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Predicting the performance of lithium adsorption and recovery from unconventional water sources with machine learning.

Water research Sep 7, 2024
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...
Water Purification Lithium Adsorption Machine Learning Water Supply
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Machine learning-driven prediction of phosphorus adsorption capacity of biochar: Insights for adsorbent design and process optimization.

Journal of environmental management Sep 4, 2024
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...
Water Pollutants, Chemical Adsorption Charcoal Phosphorus Algorithms Machine Learning Water Purification
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Leveraging experimental and computational tools for advancing carbon capture adsorbents research.

Environmental science and pollution research international Sep 3, 2024
CO emissions have been steadily increasing and have been a major contributor for climate change compelling nations to take decisive action fast. The average global temperature could reach 1.5 °C by 2035 which could cause a significant impact on the e...
Carbon Carbon Dioxide Machine Learning Adsorption Climate Change Carbon Sequestration
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Exploiting Metal-Organic Frameworks for Vinylidene Fluoride Adsorption: From Force Field Development, Computational Screening to Machine Learning.

Environmental science & technology Sep 1, 2024
Metal-organic frameworks (MOFs) represent a distinctive class of nanoporous materials with considerable potential across a wide range of applications. Recently, a handful of MOFs has been explored for the storage of environmentally hazardous fluorina...
Machine Learning Adsorption Metal-Organic Frameworks
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Refining hydrogel-based sorbent design for efficient toxic metal removal using machine learning-Bayesian optimization.

Journal of hazardous materials Aug 30, 2024
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...
Machine Learning Water Purification Metals Bayes Theorem Water Pollutants, Chemical Adsorption Hydrogels Metals, Heavy
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Deep learning artificial neural network framework to optimize the adsorption capacity of 3-nitrophenol using carbonaceous material obtained from biomass waste.

Scientific reports Aug 30, 2024
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...
Nitrophenols Biomass Deep Learning Adsorption Carbon Neural Networks, Computer Water Pollutants, Chemical Water Purification
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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 Aug 28, 2024
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...
Kinetics Hydrogen-Ion Concentration beta-Cyclodextrins Solutions Chitosan Water Pollutants, Chemical Iron Deep Learning Adsorption Diclofenac Water Water Purification Cryogels
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Adsorption behavior and mechanism of heavy metals onto microplastics: A meta-analysis assisted by machine learning.

Environmental pollution (Barking, Essex : 1987) Jul 29, 2024
Microplastics (MPs) have the potential to adsorb heavy metals (HMs), resulting in a combined pollution threat in aquatic and terrestrial environments. However, due to the complexity of MP/HM properties and experimental conditions, research on the ads...
Metals, Heavy Adsorption Microplastics Machine Learning Water Pollutants, Chemical
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