Quantitative determination of hazardous substances in aerosols by light scattering and machine learning with the example of Cr(VI) in electroplating processes

Andreas Peckhaus; Arne Walter; Marian Kraus; Florian Gebert; Frank Duschek

doi:10.1364/AIS.2021.JTu5A.25

OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES)
OSA Technical Digest (Optica Publishing Group, 2021),
paper JTu5A.25
•https://doi.org/10.1364/AIS.2021.JTu5A.25

Quantitative determination of hazardous substances in aerosols by light scattering and machine learning with the example of Cr(VI) in electroplating processes

Andreas Peckhaus, Arne Walter, Marian Kraus, Florian Gebert, and Frank Duschek

Hyperspectral Imaging and Sounding of the Environment 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-90-3

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Joint Poster Session I (JTu5A)

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A. Peckhaus, A. Walter, M. Kraus, F. Gebert, and F. Duschek, "Quantitative determination of hazardous substances in aerosols by light scattering and machine learning with the example of Cr(VI) in electroplating processes," in OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES), S. Buckley, F. Vanier, S. Shi, K. Walker, I. Coddington, S. Paine, K. Lok Chan, W. Moses, S. Qian, P. Pellegrino, F. Vollmer, G. , J. Jágerská, R. Menzies, L. Emmenegger, and J. Westberg, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper JTu5A.25.

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Abstract

Regulations of safety usage of hazardous substances impose companies to monitor their emissions. A novel approach determines the mass concentration of Cr(VI) in exhaust airflow based on angular light scattering combined with machine learning algorithms.

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