Revolutionizing biochar synthesis for enhanced heavy metal adsorption: Harnessing machine learning and Bayesian optimization

IF 7.4 2区 工程技术 Q1 ENGINEERING, CHEMICAL Journal of Environmental Chemical Engineering Pub Date : 2023-10-01 DOI:10.1016/j.jece.2023.110593
Han Yang, X. Liu, Yingliang Liu, Jianghu Cui, Yong Xiao
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利用机器学习和贝叶斯优化,革命性地合成生物炭以增强重金属吸附
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来源期刊
Journal of Environmental Chemical Engineering
Journal of Environmental Chemical Engineering Environmental Science-Pollution
CiteScore
11.40
自引率
6.50%
发文量
2017
审稿时长
27 days
期刊介绍: The Journal of Environmental Chemical Engineering (JECE) serves as a platform for the dissemination of original and innovative research focusing on the advancement of environmentally-friendly, sustainable technologies. JECE emphasizes the transition towards a carbon-neutral circular economy and a self-sufficient bio-based economy. Topics covered include soil, water, wastewater, and air decontamination; pollution monitoring, prevention, and control; advanced analytics, sensors, impact and risk assessment methodologies in environmental chemical engineering; resource recovery (water, nutrients, materials, energy); industrial ecology; valorization of waste streams; waste management (including e-waste); climate-water-energy-food nexus; novel materials for environmental, chemical, and energy applications; sustainability and environmental safety; water digitalization, water data science, and machine learning; process integration and intensification; recent developments in green chemistry for synthesis, catalysis, and energy; and original research on contaminants of emerging concern, persistent chemicals, and priority substances, including microplastics, nanoplastics, nanomaterials, micropollutants, antimicrobial resistance genes, and emerging pathogens (viruses, bacteria, parasites) of environmental significance.
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