AIMC Topic: Charcoal

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Biochar-Augmented Anaerobic Digestion System: Insights from an Interpretable Stacking Ensemble Deep Learning.

Environmental science & technology Jul 18, 2025
This study presents a comprehensive approach for optimizing biochar-augmented anaerobic digestion (AD) system through an interpretable stacking ensemble deep learning model. Extensive experimental data were compiled, incorporating feedstock character...
Anaerobiosis Charcoal Methane Deep Learning
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Addressing data handling shortcomings in machine learning studies on biochar for heavy metal remediation.

Journal of hazardous materials Mar 10, 2025
Recent advancements in machine learning (ML) technologies have significantly enhanced their applications in environmental sciences, particularly in the domains of soil and water remediation. This paper reviews recent studies that employ ML to optimiz...
Charcoal Environmental Restoration and Remediation Adsorption Soil Pollutants Machine Learning Metals, Heavy
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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...
Charcoal Polymers Clay Fluorocarbons Water Pollutants, Chemical Machine Learning Nanoparticles Adsorption
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Integrated learning framework for enhanced specific surface area, pore size, and pore volume prediction of biochar.

Bioresource technology Feb 21, 2025
Specific surface area, pore size, and pore volume are essential biochar properties. Optimization typically reduces yield by focusing on per gram of biochar. This work introduces new indicators and an integrated model to balance quality and quantity, ...
Machine Learning Temperature Charcoal Porosity Surface Properties Biomass Adsorption
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Machine learning unveils the role of biochar application in enhancing tea yield by mitigating soil acidification in tea plantations.

The Science of the total environment Jan 29, 2025
Biochar, a widely utilized soil amendment in environmental applications, has been employed to enhance tea cultivation. This study utilized three machine learning models to investigate the effects of biochar on tea growth and yield, with the random fo...
Tea Charcoal Machine Learning Soil Agriculture Camellia sinensis
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Predicting the adsorption of ammonia nitrogen by biochar in water bodies using machine learning strategies: Model optimization and analysis of key characteristic variables.

Environmental research Dec 14, 2024
Biochar adsorption technology has been widely used to remove ammonia nitrogen from water bodies. However, existing methods for predicting adsorption efficiency often lack sufficient accuracy and practical usability. This study evaluated eight machine...
Nitrogen Ammonia Adsorption Charcoal Water Purification Machine Learning Water Pollutants, Chemical
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Machine learning prediction of fundamental sewage sludge biochar properties based on sludge characteristics and pyrolysis conditions.

Chemosphere Nov 29, 2024
Sewage sludge biochar (SSBC) has significant potential for resource recovery from sewage sludge (SS) and has been widely studied and applied across various fields. However, the variability in SSBC properties, resulting from the diverse nature of SS a...
Sewage Pyrolysis Carbon Charcoal Machine Learning Waste Disposal, Fluid
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Design optimization of bimetal-modified biochar for enhanced phosphate removal performance in livestock wastewater using machine learning.

Bioresource technology Nov 28, 2024
Mg-modified biochar shows high adsorption performance under weakly acidic and neutral water conditions. However, its phosphate removal efficiency markedly decreases in naturally alkaline wastewater, such as that released in livestock farming (anaerob...
Hydrogen-Ion Concentration Phosphates Livestock Water Purification Machine Learning Adsorption Water Pollutants, Chemical Animals Wastewater Charcoal
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Cd adsorption prediction of Fe mono/composite modified biochar based on machine learning: Application for controllable preparation.

Environmental research Nov 26, 2024
In this study, artificial neural network (ANN) and random forest (RF) were constructed to predict the Cd adsorption capacity of Fe-modified biochar. The RF model outperformed ANN model in accuracy and predictive performance (R = 0.98). Through the co...
Neural Networks, Computer Charcoal Machine Learning Water Pollutants, Chemical Iron Adsorption Cadmium
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Insights into the characteristics and toxicity of microalgal biochar-derived dissolved organic matter by spectroscopy and machine learning.

The Science of the total environment Nov 20, 2024
Microalgal biochar has potential applications in various fields; however, there is limited research on the properties and risks of microalgal biochar-derived dissolved organic matter (MBDOM). This study examined how different pyrolysis temperatures (...
Machine Learning Organic Chemicals Spectrum Analysis Nitrogen Microalgae Water Pollutants, Chemical Phosphorus Charcoal
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