研究目的
Investigating the capabilities of laser induced breakdown spectroscopy (LIBS) combined with multivariate statistical approaches for spatially resolved polymer classification.
研究成果
LIBS combined with multivariate statistics is effective for spatially resolved polymer classification, including 2D structured samples and depth profiling of multilayer systems. The method provides simultaneous elemental analysis, enhancing information accessibility.
研究不足
Uneven ablation and defocusing effects may affect depth profiling results. Translucency of polymers at certain thicknesses can lead to combined ablation of multiple layers.
1:Experimental Design and Method Selection:
LIBS was used for spatially resolved polymer classification. Multivariate statistical approaches (PCA and k-means clustering) were applied for data evaluation.
2:Sample Selection and Data Sources:
Two structured synthetic polymer samples (2D structured and multilayer system) were analyzed.
3:List of Experimental Equipment and Materials:
LIBS J200 system, Nd:YAG laser, Czerny-Turner spectrometer, Si wafer, various polymers (ABS, PLA, PE, PAK, PVC).
4:Experimental Procedures and Operational Workflow:
LIBS parameters were optimized for each sample. Line-scan patterns were used for lateral resolution. Depth profiling was performed layer by layer.
5:Data Analysis Methods:
PCA and k-means clustering were used for polymer classification. Data was standardized and emission signals were integrated for analysis.
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