Detection of Airborne Nanoparticles through Enhanced Light Scattering Images

Y. Yan Ye, Qisheng Ou, Weiqi Chen, Qingfeng Cao, Dongbin Kwak, Thomas H Kuehn, David H. Pui

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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 phe-nomenon 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.

Original languageEnglish (US)
Article number2038
Issue number5
StatePublished - Mar 1 2022

Bibliographical note

Funding Information:
Acknowledgments: We acknowledge the support of members of the Center for Filtration Research: 3M Corporation, Applied Materials, Inc., BASF Corporation, Boeing Company, Yancheng Environmental Protection Science and Technology Park, Cummins Filtration Inc., Donaldson Company, Inc., Entegris, Inc., Ford Motor Company, Guangxi Wat Yuan Filtration System Co., Ltd., LG Electronics Inc., MANN+HUMMEL GmbH, Midea Air-conditioning Equipment Co., Ltd., MSP Corporation, Parker Hannifin Company, Samsung Electronics Co., Ltd., Xinxiang Shengda Filtration Technology Co., Ltd., TSI Inc., W. L. Gore & Associates, Inc., Shigematsu Works Co., Ltd., and the affiliate member National Institute for Occupational Safety and Health (NIOSH).

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.


  • Aerosol
  • Airborne nanoparticles
  • Image processing
  • Laser particle detector
  • Light scattering
  • Light scattering image

PubMed: MeSH publication types

  • Journal Article


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