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首页> 外文期刊>Chemical engineering journal >Mechanistic aspects in the formation of nano- and submicron particles in a batch and a continuous microfluidic reactor: Experiment, modeling and simulation
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Mechanistic aspects in the formation of nano- and submicron particles in a batch and a continuous microfluidic reactor: Experiment, modeling and simulation

机译:在分批和连续微流体反应器中形成纳米和亚微血管颗粒的机械方面:实验,建模和仿真

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To investigate mechanistic contrasts in particle formation between a batch and a continuous microreactor, a coupled computational fluid dynamics (CFD)-population balance equation (PBE) based model is proposed; incorporating mixing, reaction, nucleation, diffusion-growth, Brownian-coagulation, shear-induced coagulation and Ostwald ripening (OR), occurring simultaneously. This enables prediction of nanoparticle size over a wide range of temperatures, flow-fields and solvents. This has been possible for the first time, since we included: (i) effect of evaporative-loss of solvent at a high synthesis temperature in our batch reactor experiments, along with (ii) turbulent-shear coagulation of nanoparticles in this reactor, due to the imposed strong forced convection; while accounting for, in contrast, (iii) laminar-shear coagulation in the microreactor [Gutierrez et al. (Chem. Eng. J., 2011, 674-683)], due to prevailing low Reynolds number flow-synthesis in their experiments. We find that, evaporation significantly reduces particle size by reducing critical radius for OR. Consequently, without it, a strikingly high over-prediction error (about 40% with respect to our experimental particle size) is seen for synthesis of SiO2 particles in ethanol itself, with a more pronounced effect in methanol, a more volatile solvent. Furthermore, in contrasting flow fields of the two reactors, inclusion of the correct function, either turbulentshear or laminar-shear based coagulation, for batch or microreactor, respectively, enables us to predict temporal particle size evolution accurately. For batch reactor, prediction is completely a priori, while for microreactor, coagulation efficiency as a single adjustable parameter achieves that; without these, existing models suffer about 20% and 15% under-prediction in particles size, respectively, compared to experimental data.
机译:为了研究批次和连续微反应器之间的颗粒形成中的机械造影,提出了一种耦合的计算流体动力学(CFD) - 基于模型的模型;掺入混合,反应,成核,扩散生长,褐色凝固,剪切诱导的凝血和Ostwald成熟(或),同时发生。这使得能够在各种温度,流场和溶剂的范围内预测纳米粒子尺寸。这是第一次可能的,因为我们包括:(i)在我们的批量反应器实验中的高合成温度下蒸发 - 溶剂损失,以及该反应器中纳米颗粒的湍流剪切凝结,因此强迫强迫对流;虽然占据了相比之下的(iii)微反应器中的层状剪切凝结[Gutierrez等。 (化学。ENG。J.,2011,674-683),由于在实验中占上风低雷诺数流量。我们发现,蒸发通过降低临界半径来显着降低粒度或。因此,没有它,在乙醇本身中合成SiO 2颗粒,可以在乙醇本身中合成SiO 2颗粒,在乙醇中的效果更加明显,溶于溶于乙醇本身的比例高预测误差(约40%)。此外,在两个反应器的流动场中,分别包含正确的功能,湍流,湍流或基于层状剪切的凝血,使我们能够精确地预测时间粒度尺寸的进化。对于批量反应器,预测完全是先验的,而对于微反应器,凝固效率作为单个可调参数实现;没有这些,与实验数据相比,现有模型分别在粒子尺寸下遭受大约20%和15%的预测。

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