Medinger Joelle, Nedyalkova Miroslava, Lattuada Marco
Department of Chemistry, University of Fribourg, Chemin du Musée 9, 1700 Fribourg, Switzerland.
Nanomaterials (Basel). 2021 Feb 1;11(2):360. doi: 10.3390/nano11020360.
Magnetite nanocrystal clusters are being investigated for their potential applications in catalysis, magnetic separation, and drug delivery. Controlling their size and size distribution is of paramount importance and often requires tedious trial-and-error experimentation to determine the optimal conditions necessary to synthesize clusters with the desired properties. In this work, magnetite nanocrystal clusters were prepared via a one-pot solvothermal reaction, starting from an available protocol. In order to optimize the experimental factors controlling their synthesis, response surface methodology (RSM) was used. The size of nanocrystal clusters can be varied by changing the amount of stabilizer (tribasic sodium citrate) and the solvent ratio (diethylene glycol/ethylene glycol). Tuning the experimental conditions during the optimization process is often limited to changing one factor at a time, while the experimental design allows for variation of the factors' levels simultaneously. The efficiency of the design to achieve maximum refinement for the independent variables (stabilizer amount, diethylene glycol/ethylene glycol (DEG/EG) ratio) towards the best conditions for spherical magnetite nanocrystal clusters with desirable size (measured by scanning electron microscopy and dynamic light scattering) and narrow size distribution as responses were proven and tested. The optimization procedure based on the RSM was then used in reverse mode to determine the factors from the knowledge of the response to predict the optimal synthesis conditions required to obtain a good size and size distribution. The RSM model was validated using a plethora of statistical methods. The design can facilitate the optimization procedure by overcoming the trial-and-error process with a systematic model-guided approach.
磁铁矿纳米晶体簇因其在催化、磁分离和药物递送方面的潜在应用而受到研究。控制它们的尺寸和尺寸分布至关重要，通常需要进行繁琐的反复试验来确定合成具有所需特性的簇所需的最佳条件。在这项工作中，从现有的方案出发，通过一锅溶剂热反应制备了磁铁矿纳米晶体簇。为了优化控制其合成的实验因素，使用了响应面方法（RSM）。纳米晶体簇的尺寸可以通过改变稳定剂（柠檬酸三钠）的用量和溶剂比例（二甘醇/乙二醇）来改变。在优化过程中调整实验条件通常一次只能改变一个因素，而实验设计允许同时改变因素的水平。该设计在实现独立变量（稳定剂用量、二甘醇/乙二醇（DEG/EG）比例）朝着具有理想尺寸（通过扫描电子显微镜和动态光散射测量）和窄尺寸分布的球形磁铁矿纳米晶体簇的最佳条件的最大细化方面的效率得到了验证和测试。然后，基于RSM的优化程序以反向模式使用，根据响应的知识确定因素，以预测获得良好尺寸和尺寸分布所需的最佳合成条件。使用大量统计方法对RSM模型进行了验证。该设计可以通过系统的模型引导方法克服反复试验过程，从而促进优化程序。
