2019
DOI: 10.1038/s41467-019-09066-4
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In-situ aerosol nanoparticle characterization by small angle X-ray scattering at ultra-low volume fraction

Abstract: State-of-the-art aerosol nanoparticle techniques all have one feature in common: for analysis they remove the nanoparticles from their original environment. Therefore, physical and chemical properties of the particles might be changed or cannot be measured correctly. To overcome these shortcomings, we apply synchrotron based small angle X-ray scattering (SAXS) as an in-situ measurement technique. Contrasting other aerosol studies using SAXS, we focus on particle concentrations which allow direct comparison to … Show more

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Cited by 28 publications
(9 citation statements)
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References 43 publications
(40 reference statements)
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“…Indeed, SAXS experiments allow the direct measurement of the mass‐fractal dimension of aggregates, which, corresponds to the slope of the spectra between the Guiner (low‐ q ) and the Porod (high‐ q ) regions. [ 30,37 ] SAXS analysis shows that decreasing the media porosity from 95% to 93% results in relatively close fractal dimensions ( D f ) of 1.85 and 1.83, respectively, in line with other reports that were measuring D f of semiconductor oxides in the diffusion limited aggregation regime. [ 26,30 ] These fractal dimensions were additionally confirmed by analysis of SEM images with a box‐counting algorithm (see the Supporting Information and Figure S7 therein).…”
Section: Figuresupporting
confidence: 86%
“…Indeed, SAXS experiments allow the direct measurement of the mass‐fractal dimension of aggregates, which, corresponds to the slope of the spectra between the Guiner (low‐ q ) and the Porod (high‐ q ) regions. [ 30,37 ] SAXS analysis shows that decreasing the media porosity from 95% to 93% results in relatively close fractal dimensions ( D f ) of 1.85 and 1.83, respectively, in line with other reports that were measuring D f of semiconductor oxides in the diffusion limited aggregation regime. [ 26,30 ] These fractal dimensions were additionally confirmed by analysis of SEM images with a box‐counting algorithm (see the Supporting Information and Figure S7 therein).…”
Section: Figuresupporting
confidence: 86%
“…Cluster aggregation is expected to produce a peak in S(q) whose position corresponds to the characteristic size of the clusters, so a broad peak in the low q region indicates a heterogeneous distribution of cluster sizes. 73,74 A broad peak at low q (starting at q ≤ 0.03 Å -1 ) was observed after 2 days, shifting to lower q over time consistent with formation of larger clusters and, ultimately, percolated networks spanning the entire macroscopic sample and inhibiting flow. The magnitude of S(q) at the lowest measured q increases over time, stabilizing by 4 weeks at a value comparable to previously reported for colloidal gels.…”
Section: Ligandmentioning
confidence: 92%
“…The inherent apparent randomness of such disordered structures hinders the engineering and optimization of well‐defined scalable architectures with self‐similar properties over various orders of magnitude. [ 29 ] Particularly, in colloidal and aerosol science, it is crucial to have precisely control the synthesis parameters, as the final agglomerate morphology depends on the self‐assembly of the constituent nanoparticles. [ 30 ] Furthermore, it is mandatory to tailor the necessary opto‐electro‐mechanical properties via assembling the nanoparticles—possibly spontaneously—into agglomerates and clusters of powders or onto substrates with film structures, depending on the application.…”
Section: Introductionmentioning
confidence: 99%