Design of Experiments for Optimization of Polyoxometalate Syntheses
Design of Experiments for Optimization of Polyoxometalate Syntheses
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DOI：
10.1021/acs.chemmater.1c01401
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发表时间：
2021-09-14
影响因子：
8.6
通讯作者：
Cronin, Leroy
中科院分区：
文献类型：
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作者：
Bell, Nicola L.;Kupper, Manuel;Cronin, Leroy
实验设计（DOE）是一种通过同时改变多个变量来评估其效果的优化物理过程的关键方法。在化学领域，DOE探索的参数空间比占主导地位的“一次一个因素”（OFAT）方法更宽，为探索可用于优化产率、纯度的因素以及探索新化合物的化学空间提供了更大的机会。聚氧乙烯簇科学是一个产率低、重复性差、但充满难以预测和有趣材料的化学领域。在此，我们开发了DOE分析方法来探索聚氧乙烯簇形成的参数空间，以探索已知在制备条件下对产物发现、纯度和稳定性具有影响的微妙输入效应。使用Plackett-Burman筛选设计，我们在12个实验中分析了6个合成参数的影响，随后对三个最重要的因素进行了全析因分析，以确定每个成功合成的关键参数。在此基础上，我们提供了一个有用的模板，产生输入数据的自动合成的基础上DOE对其他合成程序。在我们的POM测试案例中，在所研究的四个系统中的三个系统中发现氧化还原剂化学计量是pH和温度的重要因素，这也被发现是普遍重要的。从该分析中获得的见解被应用于设计优化的合成程序，并将产物的产率从最高文献报道的产率平均提高>33%。因此，这里概述的DOE方法显示，即使对于复杂的多变量合成程序，也可以通过简便的实验设计和分析快速地洞察反应优化。
Design of experiments (DOE) is a key method for optimizing physical processes by altering multiple variables at once to assess their effect. In chemistry, DOE explores a wider parameter space than the dominant "One Factor at a Time" (OFAT) method providing greater opportunity to explore the factors that can be used to optimize yield, purity, and to explore chemical space for new compounds. One area of chemistry that suffers from low yields and poor reproducibility but is full of hard to predict and interesting materials is polyoxometalate cluster science. Herein, we developed a DOE analysis methodology to explore the parameter space of polyoxometalate cluster formation to explore the subtle input effects that are known to have an impact on the product discovery, purity, and stability under the preparation conditions. Using a Plackett-Burman screening design, we analyzed the effect of six synthetic parameters in only 12 experiments, following up with a full factorial analysis of the three most significant factors to identify the key parameters in the successful synthesis of each. Based on this, we provide a useful template that produces the input data for automated synthesis based on DOE on other synthetic procedures. In our POM test cases, redox agent stoichiometry was found in three of the four systems studied to be significant factors with pH and temperature, which also found to be commonly important. The insights derived from this analysis were applied to design optimized synthetic procedures and improve the yield of the product by on average >33% from the highest reported literature yield. Thus, the DOE methodology outlined here is shown to yield insights into reaction optimization rapidly with facile experimental design and analysis even for complex multivariate synthetic procedures.