Modeling Particle Emissions from Three-Dimensional Printing with Acrylonitrile-Butadiene-Styrene Polymer Filament.

An eddy diffusion model using data from a desktop three-dimensioanl (3D) printer was developed under laboratory conditions and then coupled with Monte Carlo analysis to estimate the potential range of particulate concentrations in and around various industrial-size 3D printers, in this case large additive manufacturing processes using acrylonitrile-butadiene-styrene polymer feedstock. The model employed mass emission estimates determined from thermal gravimetric analysis and printer enclosure particle loss rates. Other model inputs included ranging terms for extrusion rate, temperature, print time, source-to-receiver distance, printer positions, particle size fraction, and environmental diffusivity estimates based on air changes per hour. Monte Carlo analysis bracketed measured environmental particulate concentrations associated with large-scale additive manufacturing processes (3D printing). Statistically, there was no difference between the average near-field particle concentrations measured and that of the model-derived average. However, the model began to vary more statistically, if not practically, from air-monitoring results in the far field. Diffusivity and extrusion rate emerged as the two most important variables in predicting environmental concentrations. This model can be used to estimate air concentrations over a range of varying conditions, such as one might employ in a "what if" type of evaluation to estimate employee exposure, for example, as a compliance effort with OSHA standard 29 CFR Part 1910.132, requiring a formal hazard assessment for work environments as a "before exposure" effort to determine if respiratory protection is needed.

Direct Reading Particle Counters: Calibration Verification and Multiple Instrument Agreement via Bump Testing.

The calibration records of two direct reading instruments designated as condensation particle counters were examined to determine the number of times they were found to be out of tolerance at annual manufacturer's recalibration. Both instruments were found to be out of tolerance more times than within tolerance. And, it was concluded that annual calibration alone was insufficient to provide operational confidence in an instrument's response. Therefore, a method based on subsequent agreement with data gathered from a newly calibrated instrument was developed to confirm operational readiness between annual calibrations, hereafter referred to as bump testing. The method consists of measuring source particles produced by a gas grille spark igniter in a gallon-size jar. Sampling from this chamber with a newly calibrated instrument to determine the calibrated response over the particle concentration range of interest serves as a reference. Agreement between this reference response and subsequent responses at later dates implies that the instrument is performing as it was at the time of calibration. Side-by-side sampling allows the level of agreement between two or more instruments to be determined. This is useful when simultaneously collected data are compared for differences, i.e., background with process aerosol concentrations. A reference set of data was obtained using the spark igniter. The generation system was found to be reproducible and suitable to form the basis of calibration verification. The bump test is simple enough to be performed periodically throughout the calibration year or prior to field monitoring.

Ambient air sampling during quantum-dot spray deposition.

Ambient air sampling for nanosize particle emissions was performed during spot spray coating with a Sono-Tek ExactaCoat Benchtop system (ECB). Cadmium selenide quantum dots (QDs) and gold QDs, nominally 3.3 and 5 nm in diameter respectively, were applied during the evaluation. Median spray drop size was in the 20 to 60 micrometer size range. Industrial hygiene monitoring and evaluation of controls were revised when a scanning mobility particle sizer indicated a significant increase in the ambient air concentration upon early enclosure door-opening. A time delay sufficient to provide 10 enclosure air changes (a concentration reduction of more than 99.99%) before door-opening prevented the release of aerosol particles in any measurable size. As part of the evaluation, aerosol characterization in reference to background was made using condensation particle counters, atomic force and electron microscopy, and chemical analysis.

Characterizing aerosolized particulate as part of a nanoprocess exposure assessment.

Characterizing a process aerosol in the nanoscale beyond numeric concentration can assist in hazard assessment and in separating aerosolized process material from background aerosol. Size and size distribution, chemical composition, solubility, shape, and surface area may become important categorization parameters of exclusion/inclusion for purposes of exposure control. Various particle parameters are presented using examples from a process simulation. The process aerosol was composed of insoluble carbon particles plus environmental background constituents at an average air concentration of 2.76E+5 particles/cubic centimeter (p/cm3). Greater than 70% of the carbon particulate was blade-like in shape, 50% of which had a height dimension < or =100 nm. The equivalent spherical mobility diameter of 0.8% of the particulate was < or =100 nm in size. The carbon blades had a root-mean-square roughness of 75 nm and an average fractal dimension of 2.25. Obtaining these measures characterizes the aerosol and identifies parameters that may be important toxicologically.

Particle loss in a scanning mobility particle analyzer sampling extension tube.

Deposition of particles in sampling lines may occur due to various physical forces. Particles in the nanoscale are not highly susceptible to inertial or sedimentary deposition, and electrical losses are reportedly controlled by using conductive tubing. Particle losses from diffusion affect size distribution and number concentration. Selectively removing the smallest particles has the effect of increasing the statistical measure of particle size-the geometric mean-while decreasing number concentration and geometric standard deviation. Quantification of losses is necessary to interpret or correct the data. Sample loss from a rigid graphitic or flexible Tygon tube attached to a scanning mobility particle sizer inlet was investigated during sampling at the Center for Nanophase Materials Sciences. Mean concentrations and particle size parameters determined from samples collected with and without sample inlet extensions were compared. Number concentration decreased and mean particle size increased for both tubing types at lengths of approximately 0.7 m.

Preferred sampler inlet configurations for collection of aerosolized nano-scale materials.

BACKGROUND: Due to the lack of standard industrial hygiene sampling protocols for collection of nano-scale materials, sampling inlet device selection is left to individual researchers and professionals. OBJECTIVE: The objective of this study was to compare nano-scale aspiration efficiency for common inlet configurations with that of an open-ended sampler tube that is a commonly used inlet for direct reading instruments such as a condensation particle counter. METHODS: A polydisperse aerosol was generated using an electric motor as the aerosol source. Typical aerosols generated by this method produced particles with geometric mean mobility diameters of approximately 30 nm with geometric standard deviations of approximately 2. Comparison of raw particle counts in size ranges measured with a scanning mobility particle analyzer was made by determining the fractional difference between the selected inlet and that of the open-ended tube. RESULTS: Particle size distributions were nearly identical for all inlet types. The same held true for numbers of particles collected with the exception that the needle inlet was highly variable. CONCLUSIONS: When completing air monitoring for nano-scale materials, inlets on most collection devices (filters, tubing) do not impact aspiration efficiency. This means that it is not necessary to match inlet configurations when using multiple methods to collect and analyze nano-scale materials.