用于催化葡萄糖转化优化的统计驱动自动化方法。
Statistically driven automated method for catalytic glucose conversion optimisation.
作者信息
Install Joseph, Zhang Rui, Hietala Jukka, Repo Timo
机构信息
Department of Chemistry, University of Helsinki A. I. Virtasen aukio 1, P.O. Box 55 00014 Finland
Neste Oyj, Technology Centre Kilpilahti, P.O. Box 310 06101 Porvoo Finland.
出版信息
RSC Adv. 2024 Nov 7;14(48):35578-35584. doi: 10.1039/d4ra06038e. eCollection 2024 Nov 4.
A statistically driven, automated approach to optimize glucose transformations to platform chemicals, methyl lactate and levulinic acid, is reported. The combination of a robotic synthesis platform with design of experiments methods enabled efficient and precise modelling of glucose conversion catalysed by SnCl·5HO with 0-100% HO and methanol as a cosolvent. Using this strategy, optimal reaction conditions within the available reaction space were identified in 58 runs, showcasing the excellent efficiency of this method in producing high yields of methyl lactate (75.9%) and levulinic acid (64.5%) in independent reactions distinct retro-aldol condensation and dehydration pathways, respectively.
报道了一种基于统计驱动的自动化方法，用于优化葡萄糖向平台化学品乳酸甲酯和乙酰丙酸的转化。将机器人合成平台与实验设计方法相结合，能够对由五水合氯化亚锡在0-100%水和甲醇作为共溶剂存在下催化的葡萄糖转化进行高效且精确的建模。使用该策略，在58次运行中确定了可用反应空间内的最佳反应条件，分别通过不同的逆羟醛缩合和脱水途径，在独立反应中展示了该方法在高产率生产乳酸甲酯（75.9%）和乙酰丙酸（64.5%）方面的卓越效率。
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