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从体散射光谱估算粒度分布:单模态悬浮液的验证。

Estimation of Particle Size Distribution from Bulk Scattering Spectra: Validation on Monomodal Suspensions.

机构信息

Department of Biosystems , MeBioS, KU Leuven , Kasteelpark Arenberg 30 , 3001 Leuven , Belgium.

Department of Biosystems, Biosystems Technology Cluster , KU Leuven Campus Geel , Kleinhoefstraat 4 , 2440 Geel , Belgium.

出版信息

Anal Chem. 2019 Aug 6;91(15):10040-10048. doi: 10.1021/acs.analchem.9b01913. Epub 2019 Jul 18.

DOI:10.1021/acs.analchem.9b01913
PMID:31318541
Abstract

A particle size distribution (PSD) estimation method based on light-scattering properties was validated on experimental visible/near-infrared scattering spectra of polystyrene suspensions, with a nominal particle size ranging from 0.1 to 12 μm in diameter. On the basis of μ and spectra extracted from double integrating sphere measurements, good PSD estimates were obtained for particles ≥1 μm. The particle volume fraction estimates in the case of μ were close to the target concentrations, although influenced by small baseline fluctuations on the spectra. For submicrometer particles, on the other hand, the non-oscillating μ spectra lack discriminating power, resulting in erroneous PSD estimates. The reduced scattering coefficient spectra (μ') were found less useful for particle size estimation as they lack a characteristic shape, causing an over- or underestimation of the distribution width. In summary, the estimation routine proved to deliver PSD estimates in line with the reference measurements for micrometer-sized or larger particles based on their μ and scattering spectra. Additional validation on more polydisperse samples forms the next step before going to bimodal PSD estimates.

摘要

一种基于光散射特性的粒径分布(PSD)估计方法在聚苯乙烯悬浮液的实验可见/近红外散射光谱上得到了验证,其标称粒径范围为 0.1 至 12 μm。基于双积分球测量提取的 μ 和 光谱,对于粒径≥1 μm 的颗粒,得到了良好的 PSD 估计。在 μ 的情况下,颗粒体积分数的估计值接近目标浓度,尽管受到光谱上小的基线波动的影响。另一方面,对于亚微米颗粒,非振荡的 μ 光谱缺乏辨别力,导致 PSD 估计错误。由于缺少特征形状,减小的散射系数光谱(μ')对于粒径估计的用处不大,导致分布宽度的高估或低估。总之,对于基于 μ 和 散射光谱的微米级或更大粒径的颗粒,估计程序被证明能够提供与参考测量值一致的 PSD 估计值。在进行双峰 PSD 估计之前,下一步是对更多多分散性样品进行额外验证。

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