Literature DB >> 33404228

Monitoring the Effective Density of Airborne Nanoparticles in Real Time Using a Microfluidic Nanoparticle Analysis Chip.

Hong-Beom Kwon1, Woo-Young Song1, Tae-Hoon Lee1, Seung-Soo Lee1, Yong-Jun Kim1.   

Abstract

Determining the effective density of airborne nanoparticles (NPs; particles smaller than 100 nm in diameter) at a point of interest is essential for toxicology and environmental studies, but it currently requires complex analysis systems comprising several high-precision instruments as well as a specially trained operator. To address these limitations, a field-portable and cost-efficient microfluidic NP analysis device is presented, which provides quantitative information on the effective density and size distribution of NPs in real time. Unlike conventional analysis systems, the device can operate in a standalone mode because of the chip operating principle based on the electrostatic/inertial classification and electrical detection methods. Moreover, the device is both compact (16.0 × 10.9 × 8.6 cm3) and light (950 g) owing to the hardware strip down enabled by integrating the essential functions for effective density analysis on a single chip. Quantitative experiments performed to simulate real-life applications utilizing effective density (i.e., effective density-based morphology analysis on engineered NPs and multi-parametric NP monitoring in ambient air) demonstrate that the developed device can be used as an analysis tool in toxicological studies as an on-site sensor for the monitoring of individual NP exposure and environments, for quality monitoring of engineered NPs via aerosol synthesis, and other applications.

Keywords:  airborne nanoparticles; effective density; microfluidics; real-time measurements; size distribution

Mesh:

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Year:  2021        PMID: 33404228     DOI: 10.1021/acssensors.0c01986

Source DB:  PubMed          Journal:  ACS Sens        ISSN: 2379-3694            Impact factor:   7.711


  1 in total

1.  A Simple Optical Aerosol Sensing Method of Sauter Mean Diameter for Particulate Matter Monitoring.

Authors:  Liangbo Li; Ang Chen; Tian Deng; Jin Zeng; Feifan Xu; Shu Yan; Shu Wang; Wenqing Cheng; Ming Zhu; Wenbo Xu
Journal:  Biosensors (Basel)       Date:  2022-06-21
  1 in total

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