Microfluidic ultrafine particle dosimeter using an electrical detection method with a machine-learning-aided algorithm for real-time monitoring of particle density and size distribution.

Growing concerns related to the adverse health effects of airborne ultrafine particles (UFPs; particles smaller than 300 nm) have highlighted the need for field-portable, cost-efficient, real-time UFP dosimeters to monitor individual exposure. These dosimeters must measure both the particle density and size distribution as these parameters are essential to the determination of where and how many UFPs will be deposited in human lungs. However, though various kinds of laboratory-grade instruments and hand-held monitors have been developed, they are expensive and only capable of measuring particle size distribution. A microfluidic UFP dosimeter is proposed in this study to address these limitations. The proposed sensor, based on an electrical detection method with a machine-learning-aided algorithm, can simultaneously measure the size distribution (number concentration, mean mobility diameter, geometric standard deviation) and particle density, and is compact owing to the microelectromechanical systems (MEMS) technology. In a comparison test using physically synthesised Ag and di-ethyl-hexyl sebacate (DEHS) aerosols, the mean measurement errors of the proposed sensor compared to the reference system were 6.1%, 4.5%, and 7.3% for number concentration, mean mobility diameter, and particle density, respectively. Moreover, when the machine-learning aided algorithm was operated, the geometric standard deviation could be deduced with a 7.6% difference. These results indicate that the proposed device can be successfully used as a field-portable UFP sensor to assess individual exposure, an on-site monitor for ambient air pollution, an analysis tool in toxicological studies of inhaled particles, for quality assurance of nanomaterials engineered via aerosol synthesis, etc.

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

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.

Microfluidic condensation nanoparticle counter using water as the condensing liquid for assessing individual exposure to airborne nanoparticles.

We present a compact and inexpensive detection system that can accurately measure the number concentration of nanoparticles (NPs; particles smaller than 100 nm) in real-time for assessing individual exposure to airborne NPs in various environments. Our system is based on the condensation nucleation light scattering technique and uses water as the condensing liquid, which solves the self-contamination issues that affect most portable NP detection systems. Our system comprises two units: a microfluidic condensation chip for growing NPs into water droplets and a miniature optical detector for singly counting grown droplets. To effectively minimize the size and cost of our system, droplets are grown on a single chip according to the semiconductor manufacturing process. To use water as the condensing liquid, a super-hydrophilic wick (i.e., Cu micropillar array coated with CuO nanowires) is monolithically integrated into the chip. Simulations were performed to verify the method of generating supersaturated water vapor. Quantitative experiments using NaCl and Ag NPs revealed that our system grew NPs larger than 9.3 nm into 2.25 µm diameter water droplets and could count individual droplets over an extremely wide concentration range (0.021-105 N cm-3) with high accuracy. This outstanding performance allowed our system to resolve the daily pattern of the NP concentration along a metropolitan commuting street with strong agreement compared to the reference instrument. Because our system uses water, it can accurately monitor individual exposure to NPs in various kinds of environments, including multiuse facilities such as elementary schools and hospitals.

MEMS-based condensation particle growth chip for optically measuring the airborne nanoparticle concentration.

To monitor airborne nanoparticles at a particular point of interest sensitively and accurately, we developed a compact and inexpensive but highly-precise nanoparticle detection system. The proposed system, based on nucleation light-scattering, consists of two components: a microelectromechanical system (MEMS)-based particle growth chip that grows nanoparticles to micro-sized droplets through condensation and a miniaturized optical particle counter (mini-OPC) that detects individual grown droplets using a light-scattering method. To minimize the dimensions and cost of this system, all elements of the particle growth chip were integrated onto a glass slide through simple photolithography and 3D printing. Moreover, a passive cooling technique was adopted, which eliminated the need for an active cooling system. Thus, our system was much more compact, inexpensive, and power-efficient than conventional nanoparticle detection instruments. Through quantitative experiments using Ag nanoparticles in the size range of 5 to 70 nm, it was found that our system could count extremely small nanoparticles (12.4 nm) by growing them to micrometer-sized droplets. Furthermore, our system could provide an accurate number concentration of nanoparticles (the maximum difference was within 15% compared to the reference instrument), regardless of high (3500 N cm-3) and low (0.05 N cm-3) concentration environments. These results indicate that our system can be applied successfully to the monitoring of nanoparticles in various kinds of fields including not only indoor and outdoor environments but also high-tech industries utilizing cleanrooms, air filtration systems, etc.

Particle size spectrometer using inertial classification and electrical measurement techniques for real-time monitoring of particle size distribution.

To achieve real-time monitoring of aerodynamic submicron particle size distributions at a point-of-interest, we developed a high-performance particle size spectrometer that is compact, low-cost, and portable. The present system consists of four key components: a unipolar mini-discharger for electrically charging particles, an inertial size-separator for classifying charged particles into five size fractions in terms of their aerodynamic sizes, a portable multi-channel electrometer for detecting femto-ampere currents carried by charged particles at each stage, and a retrieval algorithm for converting the current data into a smooth particle size distribution. The unipolar mini-discharger and inertial size separator were quantitatively characterised by using standard polystyrene latex (PSL) particles. The experimentally determined cut-off diameters at each stage in the inertial size separator were 1.17, 0.94, 0.71, 0.54, and 0.23 µm, respectively. Then, the system was compared with a commercial reference aerodynamic particle sizer (APS) in the environment where the number concentration and the average size of TiO2 particles were changing. The present system resolved peak size and geometric standard deviation of particles to within 11.2%, and 6.3%, respectively, indicating that the system can be used to accurately monitor submicron particle size distributions in real time.