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尘埃对 Ir(0)纳米颗粒成核和生长动力学及粒度分布的影响:通过基于机理的颗粒群平衡模型分析及所得认识。

Dust Effects on Ir(0) Nanoparticle Formation Nucleation and Growth Kinetics and Particle Size-Distributions: Analysis by and Insights from Mechanism-Enabled Population Balance Modeling.

机构信息

Department of Mathematics , Colorado State University , Fort Collins , Colorado 80523-1874 , United States.

Department of Chemistry , Middle East Technical University , 06800 Ankara , Turkey.

出版信息

Langmuir. 2020 Feb 18;36(6):1496-1506. doi: 10.1021/acs.langmuir.9b03193. Epub 2020 Feb 3.

DOI:10.1021/acs.langmuir.9b03193
PMID:32011887
Abstract

The effects of microfiltration removal of filterable dust on nanoparticle formation kinetics and particle-size distribution, in a polyoxometalate polyanion (PWNbO)-stabilized Ir(0) nanoparticle formation system, are analyzed by the newly developed method of Mechanism-Enabled Population Balance Modeling (ME-PBM). The [(BuN)Na(1,5-COD)Ir·PWNbO] precatalyst system produces on average Ir(0) nanoparticles of 1.74 ± 0.33 nm and hence a particle-size distribution (PSD) of ±19% dispersion when the precatalyst is reduced under H in propylene carbonate solvent. But if the precatalyst is reduced in solvent and microfiltered reagent solutions (where the filtered solvent is then also used to rinse dust from the glassware), then larger Ir(0) 1.96 ± 0.16 nm nanoparticles are produced with a remarkable, 2.4-fold lowered ±8% dispersion. The results and effects of the microfiltration reduction of dust are analyzed by the newly developed method of ME-PBM. More specifically, the studies reported herein address eight outstanding questions that are listed in the Introduction. Those questions include: how easy or difficult it is to fit PSD data? What is the ability of the recently discovered alternative termolecular nucleation and two size-dependent growth steps mechanism to account for the effects of dust on the PSD? What types and amount of PSD kinetics data are needed to deconvolute the PSD into the parameters of the ME-PBM? What is the reliability of the resulting rate constants? Additional questions addressed include: if the ME-PBM results offer insights into the remarkable 2.4-fold narrowing of the PSD post simple microfiltration lowering of the dust, and if the results are likely to be more general? The Summary and Conclusions section lists nine specific insights that include comments on needed future studies.

摘要

采用新开发的基于机理的颗粒群平衡模型(ME-PBM)分析了微滤去除可过滤粉尘对多金属氧酸盐聚阴离子(PWNbO)稳定的 Ir(0)纳米颗粒形成体系中纳米颗粒形成动力学和粒径分布的影响。[(BuN)Na(1,5-COD)Ir·PWNbO]前催化剂体系在丙烯碳酸酯溶剂中 H 还原下,平均生成 1.74 ± 0.33nm 的 Ir(0)纳米颗粒,因此粒径分布(PSD)为±19%的分散度。但是,如果前催化剂在 溶剂中并经过微滤试剂溶液还原(过滤后的溶剂随后也用于冲洗玻璃器皿上的粉尘),则会生成粒径较大的 Ir(0)1.96 ± 0.16nm 纳米颗粒,且显著降低了 2.4 倍的±8%分散度。采用新开发的 ME-PBM 方法分析了微滤减少粉尘的效果和结果。更具体地说,本文研究报告解决了引言中列出的八个突出问题。这些问题包括:拟合 PSD 数据的难易程度如何?最近发现的替代三分子成核和两个尺寸相关生长步骤机理对粉尘对 PSD 的影响的解释能力如何?需要多少类型和数量的 PSD 动力学数据来将 PSD 反卷积为 ME-PBM 的参数?所得速率常数的可靠性如何?解决的其他问题包括:ME-PBM 结果是否提供了有关通过简单微滤降低粉尘后 PSD 显著变窄 2.4 倍的见解,以及结果是否可能更具普遍性?总结和结论部分列出了九个具体的见解,包括对未来研究的评论。

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