An Advanced Gas Chromatography–Mass Spectrometry Workflow for High-Confidence Non-Targeted Screening of Non-Intentionally Added Substances in Recycled Plastics
Hengyu Lin (8892140), Conner Stultz (22521971), James Griffith (30490), Junho Jeon (1911442), Julibeth M. Martinez De La Hoz (22012471), Peilin Yang (5992781)
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
As circularity grows in the global economy, recycling has become more relevant in the plastic materials industry. Recycled plastics, sourced from various origins, can contain numerous non-intentionally added substances such as organic contaminants, polymer degradation products, and consumer residues. The confident identification of contaminants has become an important step in the quality assessment of the recycled material and the evaluation of cleaning processes. However, traditional one-dimensional gas chromatography often encounters challenges in reporting accurate results for these complex samples. In this work, we combine a cryogen-free comprehensive two-dimensional gas chromatographic separation coupled with high-resolution mass spectrometry and a new confidence-level-based data reporting workflow to achieve more rigorous and higher-confidence identification of nontargeted species in recycled plastics. We propose four confidence levels, and seven confidence descriptor classifications based on mass spectral matching, retention index matching, and mass accuracy from high-resolution mass spectral data. The workflow was applied to postconsumer recycled plastics before and after the cleaning process. Higher than 70% of identifications are made with medium-to-high confidence. About 50% more peaks are separated and identified by the workflow compared to traditional one-dimensional separation without significant increase in data collection and analysis time. The workflow was validated by recycled plastics spiked with 26 known compounds of environmental relevance covering a broad range of chemical structures.
逐年被引趋势
暂无年度引用数据
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
化学Analytical Chemistry and Chromatography
Metabolomics and Mass Spectrometry Studies · Spectroscopy and Chemometric Analyses