CAJ | 학술논문

定性定量分析复杂组分中未知混合次要成分是非常困难的。常用的色谱质谱联用分析方法，对于其中的次要成分混合物峰，由于分开它们耗时耗力，所以较少进行深入研究。本文利用熵最小算法，以一个合成航空煤油的 GC-MS 谱图为例，对其中的某个混合物峰，利用熵最小算法，对其中含有的各个组分进行快速定性定量分析。结果显示，利用熵最小算法，不但能定性未知物，对未知物的定量也非常有用。利用熵最小算法帮助分离混合物谱图，能大大减少现行化学分析中组分分离的繁琐步骤。
정성정량분석복잡조분중미지혼합차요성분시비상곤난적。상용적색보질보련용분석방법，대우기중적차요성분혼합물봉，유우분개타문모시모력，소이교소진행심입연구。본문이용적최소산법，이일개합성항공매유적 GC-MS 보도위례，대기중적모개혼합물봉，이용적최소산법，대기중함유적각개조분진행쾌속정성정량분석。결과현시，이용적최소산법，불단능정성미지물，대미지물적정량야비상유용。이용적최소산법방조분리혼합물보도，능대대감소현행화학분석중조분분리적번쇄보취。
It is a very difficult task to do qualification and quantification analysis on unknown minor components inside complex mixture. Currently chromatography separation techniques has difficult in separation minor components out from mixture spectra, since tremendous time and cost will raise, therefore most minor components in mixture spectra always be ignored. In this work, entropy minimization algorithms have been used to reconstruct minor unknown compounds out from mixture, and do qualification and quantification analysis of these unknown compounds as well. A GC-MS mixture spectrum from a synthesized jet fuel was used to do demonstrated here. The results show that entropy minimization algorithm is a great help in separation minor components inside complex mixtures, and save great time and cost for analyzers.