AIMC Topic: Fluorocarbons

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Occurrence, Sources, and Prioritization of Per- and Polyfluoroalkyl Substances (PFASs) in Drinking Water from Yangtze River Delta, China: Focusing on Emerging PFASs.

Molecules (Basel, Switzerland) May 25, 2025
As regulations ban legacy PFASs, many emerging PFASs are being developed, leading to their release into the aquatic environment and drinking water. However, research studies on these emerging PFASs in drinking water are limited, and current standards...
Drinking Water Environmental Monitoring Water Pollutants, Chemical Fluorocarbons Rivers China
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Unveiling PFAS hazard in European surface waters using an interpretable machine-learning model.

Environment international Apr 30, 2025
Per- and polyfluoroalkyl substances (PFAS), commonly known as "forever chemicals", are ubiquitous in surface waters and potentially threaten human health and ecosystems. Despite extensive monitoring efforts, PFAS risk in European surface waters remai...
Europe Fluorocarbons Water Pollution, Chemical Environmental Monitoring Water Pollutants, Chemical Machine Learning Risk Assessment
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Assessing the association of multi-environmental chemical exposures on metabolic syndrome: A machine learning approach.

Environment international Apr 17, 2025
Metabolic syndrome (MetS) is a major global public health concern due to its rising prevalence and association with increased risks of cardiovascular disease and type 2 diabetes. Emerging evidence suggests that environmental chemical exposures may pl...
Female Aged Machine Learning Republic of Korea Middle Aged Risk Assessment Metabolic Syndrome Adult Male Fluorocarbons Humans Environmental Pollutants Environmental Exposure
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Modeling PFAS Sorption in Soils Using Machine Learning.

Environmental science & technology Apr 11, 2025
In this study, we introduce PFASorptionML, a novel machine learning (ML) tool developed to predict solid-liquid distribution coefficients () for per- and polyfluoroalkyl substances (PFAS) in soils. Leveraging a data set of 1,274 entries for PFAS in ...
Machine Learning Soil Soil Pollutants Fluorocarbons Adsorption
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Comparative immobilization of 30 PFAS mixtures onto biochar, clay, nanoparticle, and polymer derived engineered adsorbents: Machine learning insights into carbon chain length and removal mechanism.

Journal of hazardous materials Feb 25, 2025
Per- and polyfluoroalkyl substances (PFAS) are a group of fluorinated chemicals that cause potential risk in PFAS-impacted soil and water. The adsorption efficiency of 30 PFAS mixtures using different adsorbents in environmentally relevant concentrat...
Nanoparticles Water Pollutants, Chemical Machine Learning Polymers Fluorocarbons Adsorption Clay Charcoal
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Screening of estrogen receptor activity of per- and polyfluoroalkyl substances based on deep learning and in vivo assessment.

Environmental pollution (Barking, Essex : 1987) Feb 11, 2025
Over the past decades, exposure to per- and polyfluoroalkyl substances (PFAS), a group of synthetic chemicals notorious for their environmental persistence, has been shown to pose increased health risks. Despite that some PFAS were reported to have e...
Humans Fluorocarbons Environmental Pollutants Endocrine Disruptors Receptors, Estrogen Animals Zebrafish Estrogen Receptor alpha Deep Learning
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Data-Driven Insights into Resin Screening for Targeted Per- and Polyfluoroalkyl Substances Removal Using Machine Learning.

Environmental science & technology Feb 11, 2025
In this study, we address the challenge of screening resins and optimizing operation conditions for the removal of 43 perfluoroalkyl and polyfluoroalkyl substances (PFASs), spanning both long- and short-chain fluorocarbon variants, across diverse wat...
Water Pollutants, Chemical Machine Learning Fluorocarbons Water Purification
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Ecological risks of PFAS in China's surface water: A machine learning approach.

Environment international Jan 16, 2025
The persistence of per- and polyfluoroalkyl substances (PFAS) in surface water can pose risks to ecosystems, while due to data limitations, the occurrence, risks, and future trends of PFAS at large scales remain unknown. This study investigated the e...
Ecosystem Water Pollutants, Chemical Risk Assessment Machine Learning China Fluorocarbons Environmental Monitoring
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Perfluorooctanoic Acids (PFOA) removal using electrochemical oxidation: A machine learning approach.

Journal of environmental management Oct 11, 2024
The urgent need to eliminate Perfluorooctanoic Acid (PFOA) has positioned electrooxidation (EO) as a key solution for pollutant degradation. This study evaluates several machine learning (ML) models, including K-Nearest Neighbors (KNN), Decision Tree...
Fluorocarbons Oxidation-Reduction Machine Learning Caprylates Water Pollutants, Chemical
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Molecular designing of potential environmentally friendly PFAS based on deep learning and generative models.

The Science of the total environment Sep 6, 2024
Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are widely used across a spectrum of industrial and consumer goods. Nonetheless, their persistent nature and tendency to accumulate in biological systems pose substantial environmental and health t...
Environmental Pollutants Neural Networks, Computer Fluorocarbons Deep Learning
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