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Machine learning application for predicting key properties of activated carbon produced from lignocellulosic biomass waste with chemical activation

Rongge Zou, Zhibin Yang, Jiahui Zhang, Ryan Lei, W Zhang, Fitria Fnu, Daniel C.W. Tsang, Joshua S. Heyne, Xiao Zhang, Roger Ruan, Hanwu Lei

2024Bioresource Technology29 citationsDOI

Topics & Concepts

Gradient boostingYield (engineering)Boosting (machine learning)Activated carbonBiomass (ecology)Response surface methodologyComputer scienceLignocellulosic biomassEnvironmental sciencePulp and paper industryChemistryMachine learningProcess engineeringBiofuelMaterials scienceEngineeringRandom forestWaste managementBiologyAgronomyOrganic chemistryComposite materialAdsorptionThermochemical Biomass Conversion ProcessesEnvironmental Impact and SustainabilityNatural Fiber Reinforced Composites
Machine learning application for predicting key properties of activated carbon produced from lignocellulosic biomass waste with chemical activation | Litcius