This article reports on a project in which rate constants of highly volatile compounds were experimentally determined and used to extend the kinetic model to predict evaporation.
In the authors’ previous project, a kinetic model was developed to predict evaporation of compounds as a function of gas chromatographic retention index (IT). To define the initial model, evaporation rate constants were experimentally determined for compounds in the range IT = 800–1400 at temperatures from 5 to 35 °C. Although the predictive accuracy was demonstrated, broader application of the model requires extension of the IT range to include more volatile compounds; however, such extension requires experimental determination of rate constants, which is challenging due to the explosive hazard and rapid evaporation of volatile compounds. In the current project, prior to experimental evaporations, theoretical calculations were performed to optimize experimental parameters and to ensure that the vapor generated remained below the lower flammability limit for each compound. Compounds were then experimentally evaporated at three different temperatures (10, 20, and 30 °C) and analyzed by gas chromatography-mass spectrometry. The evaporation rate constants for each compound, corrected for condensation, were determined by regression to a first-order rate equation. These rate constants were combined with previously collected data to extend the kinetic model at each temperature. Comparison of predicted and experimentally determined chromatograms of an evaporated validation mixture indicated good model performance, with correlation coefficients ranging from 0.955 to 0.997 and mean absolute percent errors in predicting abundance ranging from 3 to 26 percent. (publisher abstract modified)
Downloads
Similar Publications
- A Study on the Asymmetry of the Human Left and Right Pubic Symphyseal Surfaces Using High-Definition Data Capture and Computational Shape Methods
- Research Brief: Pediatrics and Preventive Care – Establishing a Foundation of Trust
- Using automated vehicle locator data to classify discretionary police patrol across space