Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, 11/12 Gabriela Narutowicza Street, 80-233 Gdańsk, Poland.
Department of Process Engineering and Chemical Technology, Faculty of Chemistry, Gdańsk University of Technology, 11/12 Gabriela Narutowicza Street, 80-233 Gdańsk, Poland.
Sensors (Basel). 2020 Sep 27;20(19):5531. doi: 10.3390/s20195531.
We describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular the concentration of carcinogenic benzene, were then used as reference values for assessing the applicability of an array of low-cost electrochemical sensors in monitoring the exposure of the users of consumer-grade fused deposition modelling 3D printers to potentially harmful volatiles. Using multivariate statistical analysis and machine learning, it was possible to determine whether a set threshold limit value for the concentration of BTEX was exceeded with a 0.96 classification accuracy and within a timeframe of 5 min based on the responses of the chemical sensors.
我们描述了一项概念研究,在该研究中,使用质子转移反应质谱仪和电子鼻实时监测了使用不同丙烯腈丁二烯苯乙烯 (ABS) 长丝进行打印时 3D 打印机外壳内苯、甲苯、乙苯和二甲苯 (BTEX) 化合物以及苯乙烯浓度的变化。然后,BTEX 化合物浓度的定量数据,特别是致癌苯的浓度,被用作评估一系列低成本电化学传感器在监测消费级熔丝制造 3D 打印机用户接触潜在有害挥发物的适用性的参考值。使用多元统计分析和机器学习,可以根据化学传感器的响应,以 0.96 的分类准确率和 5 分钟的时间范围内,确定 BTEX 浓度是否超过设定的阈值限制。