Investigating particle emissions and aerosol dynamics from a consumer fused deposition modeling 3D printer with a lognormal moment aerosol model

Abstract

Particle emissions from consumer-fused deposition modeling 3D printers have been reported previously; however, the complex processes leading to observed aerosols have not been investigated. We measured particle concentrations and size distributions between 7 nm and 25 mm emitted from a 3D printer under different conditions in an emission test chamber. The experimental data was combined with a moment lognormal aerosol dynamic model to better understand particle formation and subsequent evolution mechanisms. The model was based on particles being formed from nucleation of unknown semivolatile compounds emitted from the heated filament during printing, which evolve due to condensation of emitted vapors and coagulation, all within a small volume near the printer extruder nozzle. The model captured observed steady state particle number size distribution parameters (total number, geometric mean diameter and geometric standard deviation) with errors nominally within 20%. Model solutions provided a range of vapor generation rates, saturation vapor pressures and vapor condensation factors consistent with measured steady state particle concentrations and size distributions. Vapor generation rate was a crucial factor that was linked to printer extruder temperature and largely accounted for differences between filament material and brands. For the unknown condensing vapor species, saturation vapor pressures were in the range of 10 ¡3 to 10 ¡1 Pa. The model suggests particles could be removed by design of collection surfaces near the extruder tip.

3D Printing - Evaluating Particle Emissions of a 3D Printing Pen

“…Printing ABS resulted in a higher particle concentration and larger particles compared to PLA. The temperature increase during printing of PLA resulted in higher particle number concentrations but had no significant effect on the geometric mean diameter (GMD).This is in agreement with a previous study28 .…”

“…The different particle concentrations might be related to the use of additives. Zhang et al 28 have stated that particles might be formed by some additives as for example pigments, however not by the bulk material. Thus, the use of different pigments for different colors might influence the number of particles released.…”

Comparison of discrete, discrete-sectional, modal and moment models for aerosol dynamics simulations

“…The discrete and discrete-sectional models are verified in the work of Biswas et al (1997), Chadha et al (2017), and Gao et al (2017). The moment and modal models are verified in the work of Sharma, Wang, et al (2019) and Zhang et al (2018), and Wang et al (2017), respectively.…”

“…In this section, first different mathematical approaches to solving the general dynamics equation are illustrated. This is followed by the description of different Geng, Park, and Sajo 2013;Harrington and Kreidenweis 1998;Kommu, Khomami, and Biswas 2004;Pirjola et al 1999;Seigneur et al 1986;Talukdar and Swihart 2004;Tsantilis, Kammler, and Pratsinis 2002;Zhang et al 1999) Discrete model PSD is divided into discrete sizes and the increment volume of the two neighboring discrete sizes is the volume of the monomer Most accurate; Computationally expensive (Frenklach and Harris 1987;Friedlander 2000;Gelbard and Seinfeld 1979;Landgrebe and Pratsinis 1989;Lehtinen and Kulmala 2003;Smith, Wells, and (Frenklach and Harris 1987;Harrington and Kreidenweis 1998;Lin, Sethi, and Biswas 1992;McGraw 1997;Pirjola et al 1999;Pratsinis 1988;Seigneur et al 1986;Suh, Zachariah, and Girshick 2001;Talukdar and Swihart 2004;Williams 1986;Yamamoto 2014;Zhang et al 1999Zhang et al , 2018 (Biswas et al 1997;Chadha et al 2017;Gao et al 2017;Kommu et al 2004;Landgrebe and Pratsinis 1990;Moniruzzaman and Park 2006;Wu and Biswas 1998;Wu and Flagan 1988) Modal model Assume monodisperse for each mode; 2n...…”

Simulation and Reproduction of a Manipulator According to Classical Arm Representation and Trajectory Planning

“…This is ASTESJ ISSN: 2415-6698 vital in a lightweight robot configuration. Its ease of use and fast time from design to manufacturing also makes FDM printers prevalent in small manufacturing enterprises, design offices, and private residential [6,7].…”