Adarsh U K, Bhoje Gowd E, Bankapur Aseefhali, Kartha V B, Chidangil Santhosh, Unnikrishnan V K
Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.
Material Sciences and Technology Division, CSIR-National Institute for Interdisciplinary Science and Technology (CSIR-NIIST), Thiruvananthapuram 695 019, Kerala, India.
Waste Manag. 2022 Aug 1;150:339-351. doi: 10.1016/j.wasman.2022.07.025. Epub 2022 Jul 27.
Ever-accumulating amounts of plastic waste raises alarming concern over environmental and public health. A practical solution for addressing this threat is recycling, and the success of an industry-oriented plastic recycling system relies greatly on the accuracy of the waste sorting technique adapted. We propose a multi-modal spectroscopic sensor which combines laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy in a single optical platform for characterizing plastics based on elemental and molecular information to assist the plastic identification-sorting process in recycling industries. The unique geometry of the system makes it compact and cost-effective for dual spectroscopy. The performance of the system in classifying industrially important plastic classes counting PP, PC, PLA, Nylon-1 1, and PMMA is evaluated, followed by the application of the same in real-world plastics comprising PET, HDPE, and PP in different chemical-physical conditions where the system consumes less than 30 ms for acquiring LIBS-Raman signals. The evaluation of the system in characterizing commuting samples shows promising results to be applied in industrial conditions in future. The study on effect of physical-chemical conditions of plastic wastes in characterizing them using the system shows the necessity for combining multiple techniques together. The proposal is not to determine the paramount methodology to characterize and sort plastics, but to demonstrate the advantages of dual-spectroscopy sensors in such applications. The outcomes of the study suggest that the system developed herein has the potential of emerging as an industrial-level plastic waste sorting sensor.
日益增多的塑料垃圾引发了对环境和公众健康的严重担忧。解决这一威胁的一个切实可行的办法是回收利用，而以行业为导向的塑料回收系统的成功很大程度上依赖于所采用的垃圾分类技术的准确性。我们提出了一种多模态光谱传感器，它将激光诱导击穿光谱（LIBS）和拉曼光谱结合在一个单一的光学平台上，用于基于元素和分子信息对塑料进行表征，以协助回收行业中的塑料识别分类过程。该系统独特的几何结构使其紧凑且具有成本效益，适用于双光谱分析。评估了该系统对包括聚丙烯（PP）、聚碳酸酯（PC）、聚乳酸（PLA）、尼龙-11和聚甲基丙烯酸甲酯（PMMA）在内的工业上重要的塑料类别进行分类的性能，随后将其应用于处于不同化学物理条件下的包括聚对苯二甲酸乙二酯（PET）、高密度聚乙烯（HDPE）和PP在内的实际塑料中，该系统获取LIBS-拉曼信号的时间不到30毫秒。该系统对通勤样本进行表征的评估显示出在未来工业条件下应用的良好前景。关于塑料废料的物理化学条件对使用该系统表征它们的影响的研究表明了将多种技术结合在一起的必要性。本文的提议并非要确定表征和分类塑料的首要方法，而是要展示双光谱传感器在这类应用中的优势。研究结果表明，本文开发的系统有潜力成为一种工业级的塑料垃圾分类传感器。
