目次
ポスター発表
- 第1日 6月22日(水) P会場(501,502,503)
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1P-23 PDF
PyGC-高分解能TOFMSとKMD解析を組み合わせたポリオレフィン中に含まれる微量成分のデータマイニング
A combination of PyGC-high resolution TOFMS and Kendrick mass defect (KMD) analysis was applied for an efficient data mining of targeted trace components among numerous polyolefin pyrolysates in PyGC-TOFMS analysis. KMD plot efficiently highlighted oxidative antioxidants containing in a PET bottle cap made of polyethylene. Remainder of Kendrick mass (RKM) plot was applied to comprehensively detect oxidative products of polypropylene. Based on the intensities of extracted peaks, the degree of oxidation was able to be assessed with high sensitivity.