Figure. Computational and data-driven procedure for optimizing an extraction process with multiple objectives.
近日,“Machine learning-assisted data-driven optimization and understanding of the multiple stage process for extraction of polysaccharides and secondary metabolites from natural products” (《机器学习辅助数据驱动的优化和理解从天然产物中提取多糖和次级代谢产物的多阶段过程》)为题,发表该项成果在英国皇家化学会期刊 Green Chemistry 上,并入选为期刊封面文章 (Back Cover) 和本年度热门文章 (Hot Articles)。
论文信息
Machine learning-assisted data-driven optimization and understanding of the multiple stage process for extraction of polysaccharides and secondary metabolites from natural productsJiamu Ma, Jianling Yao, Xueyang Ren, Ying Dong, Ruolan Song, Xiangjian Zhong,Yuan Zheng, Dongjie Shan, Fang Lv, Xianxian Li, Qingyue Deng, Yingyu He,Ruijuan Yuan* and Gaimei She*(袁瑞娟,折改梅,北京中医药大学)Green Chem., 2023, 25, 3057-3068 https://doi.org/10.1039/D2GC04574E
Green Chemistry 专注于绿色化学和可持续性替代技术的最前沿,报道的跨学科研究工作致力于构建对生物和环境友好的技术基础,以期减少化学生产对环境的影响。该刊发表的原创性研究成果代表了绿色化学研究领域的重大进展,具有广泛的吸引力。该刊的论文必须将所报道的新方法与现有方法进行比较,并证明新方法具有的优势,特别是在减少或消除对环境的不良影响方面。