Huber F, Daun KJ, Will S (2016)
Publication Status: Published
Publication Type: Journal article
Publication year: 2016
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Book Volume: 184
Pages Range: 27-39
DOI: 10.1016/j.jqsrt.2016.06.030
Inferring the size distribution of aerosolized fractal aggregates from the angular distribution of elastically scattered light is a mathematically ill-posed problem. This paper presents a procedure for analyzing Wide-Angle Light Scattering (WALS) data using Bayesian inference. The outcome is probability densities for the recovered size distribution and aggregate morphology parameters. This technique is applied to both synthetic data and experimental data collected on soot-laden aerosols, using a measurement equation derived from Rayleigh-Debye-Gans fractal aggregate (RDG-FA) theory. In the case of experimental data, the recovered aggregate size distribution parameters are generally consistent with TEM-derived values, but the accuracy is impaired by the well-known limited accuracy of RDG-FA theory. Finally, we show how this bias could potentially be avoided using the approximation error technique. (C) 2016 Elsevier Ltd. All rights reserved.
APA:
Huber, F., Daun, K.J., & Will, S. (2016). Sizing aerosolized fractal nanoparticle aggregates through Bayesian analysis of wide-angle light scattering (WALS) data. Journal of Quantitative Spectroscopy & Radiative Transfer, 184, 27-39. https://doi.org/10.1016/j.jqsrt.2016.06.030
MLA:
Huber, Franz, Kyle James Daun, and Stefan Will. "Sizing aerosolized fractal nanoparticle aggregates through Bayesian analysis of wide-angle light scattering (WALS) data." Journal of Quantitative Spectroscopy & Radiative Transfer 184 (2016): 27-39.
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