首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Automation and optimization of liquid-phase microextraction by gas chromatography
Authors:Ouyang Gangfeng  Zhao Wennan  Pawliszyn Janusz
Institution:School of Chemistry and Chemical Engineering, Sun Yat-sen University, Guangzhou 510275, China. cesoygf@sysu.edu.cn
Abstract:Several fully automated liquid-phase microextraction (LPME) techniques, including static headspace LPME (HS-LPME) (a drop of solvent is suspended at the tip of a microsyringe needle and exposed to the headspace of the sample solution), exposed dynamic HS-LPME (the solvent is exposed in the headspace of sample vial for different time, and then withdrawn into the barrel of the syringe. This procedure is repeated a number of times), unexposed dynamic HS-LPME (the solvent is moved inside the needle and the barrel of a syringe, and the gaseous sample is withdrawn into the barrel and then ejected), static direct-immersed LPME (DI-LPME) (a drop of solvent is suspended at the tip of a microsyringe needle and directly immersed into the sample solution), dynamic DI-LPME (the solvent is moved inside the needle and the barrel of a syringe, and the sample solution is withdrawn and ejected), and two phase hollow fiber-protected LPME (HF-LPME) (a hollow fiber is used to stabilize and protect the solvent), auto-performed with a commercial CTC CombiPal autosampler, are described in this paper. Critical experimental factors, including temperature, choice of extraction solvent, solvent volume, plunger movement rate, and extraction time were investigated. Among the three HS-LPME techniques that were evaluated, the exposed dynamic HS-LPME technique provided the best performance, compared to the unexposed dynamic HS-LPME and static HS-LPME approaches. For DI-LPME, the dynamic process can enhance the extraction efficiency and the achieved method precision is comparable with the static DI-LPME technique. The precision of the fully automated HF-LPME is quite acceptable (RSD values below 6.8%), and the concentration enrichment factors are better than the DI-LPME approaches. The fully automated LPME techniques are more accurate and more convenient, and the reproducibility achieved eliminates the need for an internal standard to improve the method precision.
Keywords:
本文献已被 ScienceDirect PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号