Multiple Headspace Extraction for the Quantitative Determination of Residual Monomer and Solvents in Polystyrene Pellets
Polystyrene is one of the most useful plastics used in various common consumer products as food containers,drinking cups,cutlery and toys.Residual styrene can migrate from the product and therefore come in contact with the user.The acute toxicity of styrene has been well studied.It is a skin and mucous membranes irritant and also has narcotic properties.The presence of styrene monomer in the polystyrene must be as low as possible.The analysis of residual impurities and monomers in solid polymers is always challenging.Traditionally,the sample is dissolved in a suitable solvent and injected directly into a gas chromatograph.However,the biggest problem with the direct injection of a polymer solution is the need of frequent maintenance including changing the column and replacing the inlet liner to ensure a clean analytical system.Also,there is a potential risk of decomposition of the sample in the injection port at high temperature.An easy alternate method is to use a headspace technique to do an analysis of the gas phase over the solid sample at a fixed temperature and equilibration time.This method will require compensation for the sample matrix,as calibration standards cannot be created with the same matrix interaction.Multiple headspace extraction (MHE) is a technique to exhaustively extract a sample and calculated the amount of analyte by comparison to an external standard.Herein,a multiple headspace extraction (MHE)method using the Agilent 7697A Headspace Sampler coupled with a 7890A Gas Chromatograph has been developed for quantitative determination of residual monomers and solvents in polystyrene pellets.The polystyrene pellets were freeze-ground before analysis by the MHE procedure.The optimization of headspace temperature and time for sample equilibration are discussed in detail..The repeatability was generally better than 2% RSD for each analyte in the same sample batch and the reproducibility was better than 5.6% RSD for different sample batches.
Wenwen Shen Chunxiao Wang Roger Firor
Agilent Technologies Co., Ltd., 412 Ying Lun Road, Waigaoqiao Free Trade Zone, Shanghai 200131, Chin Agilent Technologies, Inc., 2850 Centerville Road, Wilmington DE 19808, USA
国内会议
北京
英文
104-104
2012-10-01（万方平台首次上网日期，不代表论文的发表时间）