Advanced Centre of Research in High Energy Materials, University of Hyderabad, Prof C R Rao Road, Central University Campus PO, Gachibowli, Hyderabad, Telangana 500046, India.
Waste Manag. 2020 Nov;117:48-57. doi: 10.1016/j.wasman.2020.07.046. Epub 2020 Aug 14.
We present, rapid and efficient identification of ten different types of post-consumer plastics obtained from a local recycling unit by deploying a low cost, compact CCD spectrometer in laser-induced breakdown spectroscopy (LIBS) technique. For this investigation, spectral emissions were collected by an Echelle spectrograph equipped with an intensified charge-coupled device (ES-ICCD) as well as a non-gated Czerny Turner CCD spectrometer (NCT-CCD). The performance is evaluated by interrogating the samples in a single-shot as well as accumulation mode (ten consecutive laser shots). The results from principal component analysis (PCA) have shown excellent discrimination. Further, the artificial neural network (ANN) analysis has demonstrated that individual identification accuracies/rates up to ~99 % can be achieved. The data acquired with ES-ICCD in the accumulation of ten shots have shown average identification accuracies ~97 %. Nevertheless, similar performance is achieved with the NCT-CCD spectrometer even in a single shot acquisition which reduces the overall analysis time by a factor of ~15 times compared to the ES-ICCD. Furthermore, the detector/collection system size, weight, and cost also can be reduced by ~10 times by employing a NCT-CCD spectrometer. The results have the potential in realizing a compact and low-cost LIBS system for the rapid identification of plastics with higher accuracies for the real-time application.
我们通过在激光诱导击穿光谱（LIBS）技术中部署低成本、紧凑型 CCD 光谱仪，快速有效地识别了来自当地回收单位的十种不同类型的消费后塑料。在这项研究中，通过配备增强型电荷耦合器件（ES-ICCD）的阶梯光谱仪和非门控 Czerny Turner CCD 光谱仪（NCT-CCD）收集光谱发射。通过单次和累积模式（连续十次激光射击）询问样品来评估性能。主成分分析（PCA）的结果表明具有出色的辨别能力。此外，人工神经网络（ANN）分析表明，个别识别准确率/率高达约 99%。在累积十次射击中使用 ES-ICCD 获得的数据显示平均识别准确率约为 97%。然而，即使在单次采集时，NCT-CCD 光谱仪也能实现类似的性能，与 ES-ICCD 相比，整体分析时间缩短了约 15 倍。此外，通过采用 NCT-CCD 光谱仪，还可以将探测器/收集系统的尺寸、重量和成本降低约 10 倍。这些结果有望实现紧凑且低成本的 LIBS 系统，用于快速识别塑料，具有更高的准确率，适用于实时应用。
