AIMC Topic: Charcoal

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Machine learning models for predicting biochar properties from lignocellulosic biomass torrefaction.

Bioresource technology Mar 2, 2024
This study developed six machine learning models to predict the biochar properties from the dry torrefaction of lignocellulosic biomass by using biomass characteristics and torrefaction conditions as input variables. After optimization, gradient boos...
Biomass Charcoal Temperature Machine Learning
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Artificial intelligence-enabled optimization of Fe/Zn@biochar photocatalyst for 2,6-dichlorophenol removal from petrochemical wastewater: A techno-economic perspective.

Chemosphere Feb 19, 2024
While numerous studies have addressed the photocatalytic degradation of 2,6-dichlorophenol (2,6-DCP) in wastewater, an existing research gap pertains to operational factors' optimization by non-linear prediction models to ensure a cost-effective and ...
Wastewater Zinc Artificial Intelligence Charcoal Phenols Chlorophenols
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Tree-structured parzen estimator optimized-automated machine learning assisted by meta-analysis for predicting biochar-driven NO mitigation effect in constructed wetlands.

Journal of environmental management Feb 17, 2024
Biochar is a carbon-neutral tool for combating climate change. Artificial intelligence applications to estimate the biochar mitigation effect on greenhouse gases (GHGs) can assist scientists in making more informed solutions. However, there is also e...
Wetlands Nitrous Oxide Nitrogen Machine Learning Artificial Intelligence Charcoal Soil
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Efficient remediation of different concentrations of Cr-contaminated soils by nano zero-valent iron modified with carboxymethyl cellulose and biochar.

Journal of environmental sciences (China) Dec 18, 2023
Nano zero-valent iron (nZVI) is widely used in soil remediation due to its high reactivity. However, the easy agglomeration, poor antioxidant ability and passivation layer of Fe-Cr coprecipitates of nZVI have limited its application scale in Cr-conta...
Carboxymethylcellulose Sodium Charcoal Chromium Metal Nanoparticles Iron Environmental Restoration and Remediation Soil Pollutants Soil
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Multitask Deep Learning Enabling a Synergy for Cadmium and Methane Mitigation with Biochar Amendments in Paddy Soils.

Environmental science & technology Dec 12, 2023
Biochar has demonstrated significant promise in addressing heavy metal contamination and methane (CH) emissions in paddy soils; however, achieving a synergy between these two goals is challenging due to various variables, including the characteristic...
Methane Oryza Charcoal Cadmium Artificial Intelligence Deep Learning Soil
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Predicting the efficiency of arsenic immobilization in soils by biochar using machine learning.

Journal of environmental sciences (China) Nov 27, 2023
Arsenic (As) pollution in soils is a pervasive environmental issue. Biochar immobilization offers a promising solution for addressing soil As contamination. The efficiency of biochar in immobilizing As in soils primarily hinges on the characteristics...
Models, Chemical Machine Learning Charcoal Arsenic Soil Pollutants Soil
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Transformer-based deep learning models for adsorption capacity prediction of heavy metal ions toward biochar-based adsorbents.

Journal of hazardous materials Oct 12, 2023
Biochar adsorbents synthesized from food and agricultural wastes are commonly applied to eliminate heavy metal (HM) ions from wastewater. However, biochar's diverse characteristics and varied experimental conditions make the accurate estimation of th...
Metals, Heavy Charcoal Ions Adsorption Deep Learning
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Role of modeling and artificial intelligence in process parameter optimization of biochar: A review.

Bioresource technology Oct 10, 2023
Enhancement of crop yield, conservation and quality upgradation of soil, and efficient water management are the main objectives of sustainable agriculture and mitigating climate change's impact on agriculture. In recent days, biochar, obtained via th...
Agriculture Artificial Intelligence Charcoal Soil
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Prediction model for biochar energy potential based on biomass properties and pyrolysis conditions derived from rough set machine learning.

Environmental technology Mar 29, 2023
Biochar is a high-carbon-content organic compound that has potential applications in the field of energy storage and conversion. It can be produced from a variety of biomass feedstocks such as plant-based, animal-based, and municipal waste at differe...
Biomass Pyrolysis Machine Learning Charcoal
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Comparative study of machine learning methods integrated with genetic algorithm and particle swarm optimization for bio-char yield prediction.

Bioresource technology Sep 22, 2022
In this study, Machine learning (ML) models integrated with genetic algorithm (GA) and particle swarm optimization (PSO) have been developed to predict, evaluate, and analyze biochar yield using biomass properties and process operating conditions. Co...
Pyrolysis Charcoal Machine Learning Algorithms
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