通过在线超光谱成像和机器学习对聚烯中三水合物阻燃剂的量化,以安全分类
Georgiana Amariei1, Martin Lahn Henriksen1, Pernille Klarskov2
1Plastic and Polymer Engineering, Department of Biological and Chemical Engineering, Aarhus University, Aabogade 40, DK-8200 Aarhus N., Denmark.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
|February 6, 2024
概括
精确识别塑料废弃物中的三水合物 (ATH) 阻燃剂对于回收至关重要. 一个工业短波红外 (SWIR) 超光谱成像系统与主要组件分析 (PCA) 有效地检测和量化塑料中的ATH.
科学领域:
- 材料科学 材料科学 材料科学
- 聚合物化学 聚合物化学
- 分析化学 分析化学
背景情况:
- 在塑料中广泛使用三水合物 (ATH) 阻燃剂在塑料废物回收利用中提出了重大挑战.
- 准确识别和量化ATH对于有效和安全的塑料回收过程至关重要.
研究的目的:
- 为了证明工业直线短波红外 (SWIR) 超光谱成像系统与主要组件分析 (PCA) 结合用于检测和量化塑料垃圾中的ATH的有效性.
- 在低密度聚乙烯 (LDPE) 和聚烯 (PP) 中开发ATH度的定量估计模型.
主要方法:
- 使用工业内线SWIR高光谱成像系统进行样本分析.
- 使用主要成分分析 (PCA) 和SWIR频段面积比率用于定量估计ATH度.
- 使用元素分析,ATR-FTIR,DSC和TGA进行特征样本.
主要成果:
- 与SWIR频段面积比率模型相比,PCA模型显示出更高的性能.
- 在LDPE (R2=0.95) 和PP (R2=0.94) 中ATH度的高预测准确度分别达到22.91.6重%和24.02.5重%.
- 验证了不同ATH度的定量估计模型.
结论:
- 开发的SWIR高光谱成像系统与PCA是实时检测和量化塑料回收中的ATH的有效工具.
- 这种在线控制工具对回收行业具有重要意义,用于立即评估阻燃剂添加剂.
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