Grupo de Análise Instrumental Aplicada (GAIA), Departamento de Química (DQ), Universidade Federal de São Carlos (UFSCar), PO Box 676, Zip Code 13565-905, São Carlos, SP, Brazil.
Laboratório de Polímeros, Departamento de Química (DQ), Universidade Federal de São Carlos (UFSCar), PO Box 676, Zip Code 13565-905, São Carlos, SP, Brazil.
Waste Manag. 2017 Dec;70:212-221. doi: 10.1016/j.wasman.2017.09.027. Epub 2017 Sep 28.
Due to the continual increase in waste generated from electronic devices, the management of plastics, which represents between 10 and 30% by weight of waste electrical and electronic equipment (WEEE or e-waste), becomes indispensable in terms of environmental and economic impacts. Considering the importance of acrylonitrile-butadiene-styrene (ABS), polycarbonate (PC), and their blends in the electronics and other industries, this study presents a new application of laser-induced breakdown spectroscopy (LIBS) for the fast and direct determination of PC and ABS concentrations in blends of these plastics obtained from samples of e-waste. From the LIBS spectra acquired for the PC/ABS blend, multivariate calibration models were built using partial least squares (PLS) regression. In general, it was possible to infer that the relative errors between the theoretical or reference and predicted values for the spiked samples were lower than 10%.
由于电子设备产生的废物不断增加，管理塑料废物（占电子电气设备废物（WEEE 或电子废物）重量的 10%至 30%）在环境和经济影响方面变得不可或缺。鉴于丙烯腈-丁二烯-苯乙烯（ABS）、聚碳酸酯（PC）及其混合物在电子和其他行业中的重要性，本研究提出了激光诱导击穿光谱（LIBS）的新应用，用于快速直接测定从电子废物样品中获得的这些塑料混合物中 PC 和 ABS 的浓度。从 PC/ABS 共混物的 LIBS 光谱中，使用偏最小二乘法（PLS）回归建立了多元校准模型。一般来说，可以推断出加标样品的理论值或参考值与预测值之间的相对误差低于 10%。
