Detection of Airborne Nanoparticles through Enhanced Light Scattering Images

A new method is proposed in this paper to detect airborne nanoparticles, detecting the light scattering caused by both the particle and the surrounding molecules, which can surpass the limitations of conventional laser optical methods while maintaining simplicity and cost-effectiveness. This method is derived from a mathematical analysis that describes the particle light scattering phenomenon more exactly by including the influence of light scattered from surrounding gas molecules. The analysis shows that it is often too much of a simplification to consider only light scattering from the detected nanoparticle, because light scattering from the surrounding gas molecules, whether visible or invisible to the sensor, is important for nanoparticle detection. An image detection approach utilizing the light scattering from surrounding air molecules is described for the detection of airborne nanoparticles. Tests using monodisperse nanoparticles confirm that airborne particles of around 50 nm in size can even be detected using a low-cost testing device. This shows further that even when using a simple image processing code, captured particle light scattering images can be converted digitally into instantaneous particle counts or concentrations. The factors limiting conventional pulse detection are further discussed. This new method utilizes a simple static light scattering (SLS) approach to enable the development of new devices with better detection capabilities, paving the way for the further development of nanoparticle detection technology.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:22

Enthalten in:

Sensors (Basel, Switzerland) - 22(2022), 5 vom: 05. März

Sprache:

Englisch

Beteiligte Personen:

Ye, Yan [VerfasserIn]
Ou, Qisheng [VerfasserIn]
Chen, Weiqi [VerfasserIn]
Cao, Qingfeng [VerfasserIn]
Kwak, Dong-Bin [VerfasserIn]
Kuehn, Thomas [VerfasserIn]
Pui, David Y H [VerfasserIn]

Links:

Volltext

Themen:

Aerosol
Airborne nanoparticles
Image processing
Journal Article
Laser particle detector
Light scattering
Light scattering image

Anmerkungen:

Date Completed 14.03.2022

Date Revised 17.03.2022

published: Electronic

Citation Status MEDLINE

doi:

10.3390/s22052038

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM338020330