4 Material und Umwelt
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Fused filament fabrication (FFF) is a material extrusion-based technique often used in desktop 3D printers. Polymeric filaments are melted and are extruded through a heated nozzle to form a 3D object in layers. The extruder temperature is therefore a key parameter for a successful print job but also one of the main emission driving factors as harmful pollutants (e.g., ultrafine particles) are formed by thermal polymer degradation. The awareness of potential health risks has increased the number of emission studies in the past years. However, studies usually refer their calculated emission data to the printer set extruder temperature for comparison purposes. In this study, we used a thermocouple and an infrared camera to measure the actual extruder temperature and found significant temperature deviations to the displayed set temperature among printer models. Our result shows that printing the same filament feedstocks with three different printer models and with identical printer set temperature resulted in a variation in particle emission of around two orders of magnitude. A temperature adjustment has reduced the variation to approx. one order of magnitude. Thus, it is necessary to refer the measured emission data to the actual extruder temperature as it poses a more accurate comparison parameter for evaluation of the indoor air quality in user scenarios or for health risk assessments.
The diversity of fused filament fabrication (FFF) filaments continues to grow rapidly as the popularity of FFF-3D desktop printers for the use as home fabrication devices has been greatly increased in the past decade. Potential harmful emissions and associated health risks when operating indoors have induced many emission studies. However, the lack of standardization of measurements impeded an objectifiable comparison of research findings. Therefore, we designed a chamber-based standard method, i.e., the strand printing method (SPM), which provides a standardized printing procedure and quantifies systematically the particle emission released from individual FFF-3D filaments under controlled conditions. Forty-four marketable filament products were tested. The total number of emitted particles (TP) varied by approximately four orders of magnitude (1E9 ≤ TP ≤ 1E13), indicating that origin of polymers, manufacturer-specific additives, and undeclared impurities have a strong influence. Our results suggest that TP characterizes an individual filament product and particle emissions cannot be categorized by the polymer type (e.g., PLA or ABS) alone. The user's choice of a filament product is therefore decisive for the exposure to released particles during operation. Thus, choosing a filament product awarded for low emissions seems to be an easily achievable preemptive measure to prevent health hazards.
In this work, we use a gas sensor system consisting of a commercially available gas sensor in temperature cycled operation. It is trained with an extensive gas profile for detection and quantification of hazardous volatile organic compounds (VOC) in the ppb range independent of a varying background of other, less harmful VOCs and inorganic interfering gases like humidity or hydrogen. This training was then validated using a different gas mixture generation apparatus at an independent lab providing analytical methods as reference. While the varying background impedes selective detection of benzene and naphthalene at the low concentrations supplied, both formaldehyde and total VOC can well be quantified, after calibration transfer, by models trained with data from one system and evaluated with data from the other system. The lowest achievable root mean squared errors of prediction were 49 ppb for formaldehyde (in a concentration range of 20–200 ppb) and 150 μg/m³ (in a concentration range of 25–450 μg/m³) for total VOC. The latter uncertainty improves to 13 μg/m³ with a more confined model range of 220–320 μg/m³. The data from the second lab indicate an interfering gas which cannot be detected analytically but strongly influences the sensor signal. This demonstrates the need to take into account all sensor relevant gases, like, e.g., hydrogen and carbon monoxide, in analytical reference measurements.