AIMC Topic: Charcoal

Clear Filters Showing 11 to 20 of 65 articles

Optimizing the early-stage of composting process emissions - artificial intelligence primary tests.

Scientific reports Nov 8, 2024
Although composting has many advantages in treating organic waste, many problems and challenges are still associated with emissions, like NH, CO and HS, as well as greenhouse gases such as CO. One promising approach to enhancing composting conditions...
Soil Bayes Theorem Charcoal Artificial Intelligence Machine Learning Neural Networks, Computer Greenhouse Gases Hydrogen Sulfide Carbon Dioxide Composting Ammonia
View on PubMed DOI

Global meta-analysis and machine learning reveal the critical role of soil properties in influencing biochar-pesticide interactions.

Environment international Nov 6, 2024
Biochar application in soils is increasingly advocated globally for its dual benefits in enhancing agricultural productivity and sequestering carbon. However, lingering concerns persist regarding its environmental impact, particularly concerning its ...
Soil Pollutants Charcoal Pesticide Residues Pesticides Soil Agriculture Machine Learning
View on PubMed DOI

Biosorption of cobalt and chromium from wastewater using manganese dioxide and iron oxide nanoparticles loaded on cellulose-based biochar: Modeling and optimization with machine learning (artificial neural network).

International journal of biological macromolecules Oct 28, 2024
In this study, two nanomaterials with excellent adsorption capacities were developed to remove heavy metals efficiently from wastewater. Manganese dioxide MnO nanoparticles and iron oxide FeO nanoparticles were successfully synthesized using cassava ...
Adsorption Manganese Compounds Oxides Cellulose Water Pollutants, Chemical Kinetics Hydrogen-Ion Concentration Cobalt Charcoal Chromium Neural Networks, Computer Machine Learning Water Purification Temperature Wastewater Ferric Compounds Thermodynamics
View on PubMed DOI

Synergistic biochar and Serratia marcescens tackle toxic metal contamination: A multifaceted machine learning approach.

Journal of environmental management Sep 20, 2024
Metal contamination in soil poses environmental and health risks requiring effective remediation strategies. This study introduces an innovative approach of synergistically employing biochar and bacterial inoculum of Serratia marcescens to address to...
Machine Learning Soil Charcoal Metals Serratia marcescens Soil Pollutants
View on PubMed DOI

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 ...
Adsorption Charcoal Cocos Neural Networks, Computer
View on PubMed DOI

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...
Adsorption Charcoal Phosphorus Water Purification Water Pollutants, Chemical Machine Learning Algorithms
View on PubMed DOI

Predicting and refining acid modifications of biochar based on machine learning and bibliometric analysis: Specific surface area, average pore size, and total pore volume.

The Science of the total environment Jul 6, 2024
Acid-modified biochar is a modified biochar material with convenient preparation, high specific surface area, and rich pore structure. It has great potential for application in the heavy metal remediation, soil amendments, and carrying catalysts. Spe...
Adsorption Charcoal Porosity Machine Learning Bibliometrics
View on PubMed DOI

Optimal biochar selection for cadmium pollution remediation in Chinese agricultural soils via optimized machine learning.

Journal of hazardous materials Jun 27, 2024
Biochar is effective in mitigating heavy metal pollution, and cadmium (Cd) is the primary pollutant in agricultural fields. However, traditional trial-and-error methods for determining the optimal biochar remediation efficiency are time-consuming and...
Charcoal China Environmental Restoration and Remediation Agriculture Machine Learning Cadmium Soil Pollutants Soil
View on PubMed DOI

The use of artificial neural network for modelling adsorption of Congo red onto activated hazelnut shell.

Environmental monitoring and assessment Jun 19, 2024
Activated hazelnut shell (HSAC), an organic waste, was utilized for the adsorptive removal of Congo red (CR) dye from aqueous solutions, and a modelling study was conducted using artificial neural networks (ANNs). The structure and characteristic fun...
Charcoal Neural Networks, Computer Models, Chemical Kinetics Waste Disposal, Fluid Hydrogen-Ion Concentration Water Pollutants, Chemical Corylus Adsorption Congo Red
View on PubMed DOI

Multi-output neural network model for predicting biochar yield and composition.

The Science of the total environment Jun 14, 2024
In biomass pyrolysis for biochar production, existing prediction models face computational challenges and limited accuracy. This study curated a comprehensive dataset, revealing pyrolysis parameters' dominance in biochar yield (54.8 % importance). Py...
Pyrolysis Biomass Neural Networks, Computer Charcoal Machine Learning
View on PubMed DOI
Popular Topics
Recent Journals