Deciphering the adsorption mechanisms between microplastics and antibiotics: A tree-based stacking machine learning approach

Machine Learning Approaches for Predicting Microplastic Removal

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Researchers applied Bayesian optimization combined with machine learning models — including boosted regression trees, neural networks, and support vector regression — to predict microplastic removal during coagulation, finding the BOA-BRT hybrid outperformed conventional methods by up to 71%, with microplastic particle size identified as the most influential variable.

A Machine-Learning Model for Investigating Microplastics Source–Receptor Relationships in Aquatic Environments

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Researchers developed a machine-learning model to trace where microplastics in aquatic environments come from and where they end up, potentially giving scientists and regulators a more powerful tool to identify pollution sources and prioritize cleanup efforts.

Interaction Between Polyurethane Microplastics and Ciprofloxacin: A Study on Adsorption Behaviour and Ecological Implications

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Polyurethane microplastics adsorb the antibiotic ciprofloxacin, creating combined pollutant complexes with potential ecological implications for aquatic environments. This interaction highlights how microplastics can serve as carriers for toxic co-contaminants, amplifying environmental risks beyond what either pollutant poses alone.

Interaction Between Polyurethane Microplastics and Ciprofloxacin: A Study on Adsorption Behaviour and Ecological Implications

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Polyurethane microplastics demonstrate significant adsorption capacity for the antibiotic ciprofloxacin, suggesting that plastic particles in aquatic environments can act as vectors for pharmaceutical pollutants. This interaction raises ecological concerns about the combined toxicity of microplastic-antibiotic complexes in waterways and their potential impacts on aquatic organisms and antimicrobial resistance.

Revealing the key factors of synergistic transport of microplastics and heavy metals in groundwater: Batch experiments, density functional theory calculations, molecular dynamics simulations, and machine learning modeling