Predicting the size of silver nanoparticles synthesised in flow reactors: Coupling population balance models with fluid dynamic simulations
Predicting the size of silver nanoparticles synthesised in flow reactors: Coupling population balance models with fluid dynamic simulations
复制标题
DOI：
10.1016/j.cej.2023.147684
复制
发表时间：
2023-12-03
影响因子：
15.1
通讯作者：
Torrente-Murciano，Laura
中科院分区：
文献类型：
--
作者：
Casado，Cintia;Pinho，Bruno;Torrente-Murciano，Laura
实现纳米材料合成过程中的尺寸控制是至关重要的部署在许多应用中，由于其强大的尺寸性能的关系。然而，由于纳米颗粒合成的多步机制，这仍然是该领域的一个挑战。在本文中，我们提出了一个实验验证的模型，能够预测的颗粒尺寸和分布的银纳米粒子在流动反应器中合成的耦合时间分辨流体动力学模拟与人口平衡。该模型揭示了反应器的设计和相应的纳米粒子的大小之间的基本相关性。其显示增加混合速率增加纳米粒子形成的总速率，其中纳米粒子合成在整个反应体积中均匀地发生。相反，当在反应物流之间存在可区分的界面（即低混合速率）时，成核和生长发生在入口物流之间的界面中的小部分反应体积中。快速混合和高平均成核速率的组合可导致转化为小尺寸和窄尺寸分布的成核爆发。这项工作提出了一种新的方法，使用计算指导设计的反应器合成纳米材料，使该领域远离目前的试错策略。
Achieving size control during nanomaterial synthesis is critical for their deployment in numerous applications due to their strong size-properties relationships. However, it remains a challenge in the field due to multi-step mechanisms in nanoparticle synthesis. In this paper, we present an experimentally-validated model able to predict the particle size and distribution of silver nanoparticles synthesised in flow reactors by coupling time-resolved fluid dynamic simulations with population balance. The model reveals fundamental correlations between reactor design and the corresponding size of the nanoparticles. It shows that increasing mixing rate, increases the overall rate of nanoparticle formation, where nanoparticle synthesis takes place homogeneously in the whole of the reaction volume. In contrast, when there is a distinguishable interface between reactant streams (i.e. low mixing rate), nucleation and growth take place in a small fraction of the reaction volume in the interface between the inlet streams. The combination of fast mixing and high average nucleation rate can lead to a burst of nuclei formation translated in small size and narrow size distribution. This work presents a new approach for the use of computational-guided design of reactors for the synthesis of nanomaterials to move the field away from current trial-and-error strategies.