Theoretical model for quantitative determination of volatile compounds in polymers by dynamic headspace sampling

Abstract

A theoretical model was derived for dynamic headspace sampling of volatiles in solid samples, such as polymers, and In which process parameters as well as component parameters were Included. The model assumes that the mass transfer from the polymer to the surrounding gas phase is accomplished by two rate constants, one within the polymer and one In the boundary gas layer at the polymer interface. By use of the model the recovery can be determined, which simplifies the quantification. The calculated and the experimental results show very good correlation under different types of conditions. The effects of variation of some process parameters (e.g. temperature and flow rate) on the recovery were also studied. Under the studied temperature range, as high a temperature as possible, but lower than the melt index for the polymer, gives the best possibility to achieve highest recovery for less volatile compounds. However, the best solution for all types of compounds is to have a small film thickness and as high a contact area as possible. A decisive parameter is the thickness of the boundary layer, which should be minimized as far as possible to achieve rapid transport In the gas phase. The mass transfer through this layer is often the rate-determining factor for the extraction efficiency. The flow rate optimum is determined by the geometry of the headspace sampler, type of extraction gas, and the cold trap efficiency.

Quantitative determination of volatiles in polyolefins by dynamic headspace/capillary gas chromatography/mass spectrometry

“…To achieve quantitative performance of dynamic headspace analysis of polymers, it is important to understand the factors that influence the migration, such as desorption temperature, time, flow rate, and shape and size of the sample [9].…”

“…The number of extraction steps can be restricted to one or two by use of a theoretical model [9]. An internal standard system based upon continuous generation of gas standard mixtures will also be described.…”

“…These steps were repeated as many times as was necessary to achieve almost complete extraction of the component of interest. The recovery of the volatiles is dependent on several factors, such as sample size, temperature, flow rate of the purge gas, type of purge gas, sampler geometry, trappingand desorption efficiency [9,11,12]. Furthermore, the volatility, solubility and affinity of the compounds and their diffusion rates in the polymer as well as the properties of the polymer itself (e. g. crystallinity, chain-branching, density) also strongly influence the quantitative yield [9].…”

“…The parameters can be optimized by use of a multivariate optimizing program, e. g. simplex [15] or by use of a theoretical model [9,12]. However, the sampling condition is not always optimal for all volatiles and to get a better reproducibility of the results for the studied compounds, it is preferable to use multiple dynamic headspace extraction (MDHE).…”

“…Moreover, if the above mentioned parameters are known, the recovery can be determined and theoretically the extraction steps can be reduced to only one. The derivation and evaluation of the model will be published elsewhere [9].…”