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

引用次数: 1

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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

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.