AIMC Topic: Water Pollutants, Chemical

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Machine-Learning-Assisted CRISPR/Cas12a Biosensors for Monitoring Organophosphorus Pesticide Degradation.

Analytical chemistry
Owing to the severe environmental and health issues posed by organophosphorus pesticides (OPs), a dual-enzyme cascade biosensing platform based on manganese dioxide (MnO) and CRISPR/Cas12a was developed in this study. Smartphones were innovatively in...

A Machine Learning-Assisted Liquid Crystal Droplet Array Platform for the Sensitive and Selective Detection of Per- and Polyfluoroalkyl Substances (PFAS) in Water.

ACS sensors
We report a machine learning (ML)-assisted liquid crystal (LC) droplet array platform for the detection of per- and polyfluoroalkyl substances (PFAS) in water. Our approach uses an autoencoder network to process thousands of images obtained from arra...

Unveiling chemical space, scaffold diversity, critical structural features of pesticides: A comprehensive QSAR, qRASAR, machine learning studies to predict pesticides toxicity.

The Science of the total environment
The increasing use of pesticides in agriculture and urban areas has led to significant contamination of aquatic ecosystems, posing risks to non-target species. Fish, particularly the rainbow trout (Oncorhynchus mykiss), are highly vulnerable due to t...

Neuronal Membrane-Functionalized Biohybrid Microrobots for Active Decontamination of Neurotoxins in Aqueous Environments.

ACS nano
The emergence of biohybrid microrobots offers a promising platform for environmental remediation; however, their potential for neurotoxin decontamination remains largely unexplored. Neurotoxins, such as tetrodotoxin (TTX), pose acute threats to aquat...

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...

Distribution patterns and source contributions of emerging contaminants in urban wastewater systems: from pumping stations to wastewater treatment plants.

Environmental pollution (Barking, Essex : 1987)
Sewage pumping stations and wastewater treatment plants (WWTPs) serve as critical nodes through which emerging pollutants (ECs) migrate from urban and industrial sources into aquatic environments. However, research on the co-occurrence, source dynami...

Predicting the Fate and Source of Groundwater PFAS in the Pearl River Delta Region Based on Machine Learning.

Environmental science & technology
Extensive investigations into the increasingly severe contamination of perfluoroalkyl and polyfluoroalkyl substances (PFAS) in groundwater are currently causing high costs and long duration. Machine learning provides useful tools for predicting the o...

Hydrogeochemical and machine learning evidences for release and attenuation mechanisms of chromium contamination in a partially PRB remediation of shallow groundwater.

Environmental pollution (Barking, Essex : 1987)
This study aimed to investigate the release and attenuation mechanisms of Cr(VI) in a shallow aquifer system and evaluate the remediation performance of a permeable reactive barrier (PRB) in central China. A hydrogeochemical and machine learning fram...

Deconvoluting and Interpreting Nontargeted Chemical Data: A Data-Driven Forensic Workflow for Identifying the Most Prominent Chemical Sources in Receiving Waters.

Environmental science & technology
Chemical forensics aims to identify major contamination sources, but existing workflows often rely on predefined targets and known sources, introducing bias. Here, we present a data-driven workflow that reduces this bias by applying an unsupervised m...

Assessing biodegradability potential of organic chemicals in aquatic and soil environment through classification-based machine learning models developed in accordance with OECD standards.

The Science of the total environment
Information on the biodegradation potential of organic chemicals in the ecosystem helps us analyze their persistence, bioaccumulation, and toxicity (PBT) behaviour. The environment is exposed to many chemicals from various sources, both intentionally...