Description of original award (Fiscal Year 2023, $262,678)
Identification of evaporated liquids in fire debris samples is critical in determining an intentional fire. To assist with identification, reference libraries typically contain chromatograms of liquids experimentally evaporated to different levels. However, this is a time- and resource-intensive effort. To overcome practical limitations associated with experimental evaporations, the evaporation process can be modeled. While several kinetic and thermodynamic models have been proposed, these models tend to require that the identity of the liquid is known, which limits application in fire debris analysis. Further, it is not possible or feasible to compare these various models as they are based on different foundations, have different input requirements, and have different outputs.
Our group previously developed a kinetic model to predict evaporation rate constants as a function of retention index, which negates the need to know the chemical identity of the liquid. Early work demonstrated successful application to predict chromatograms corresponding to evaporated ignitable liquids, including gasoline. We recently (December 2022) completed a National Institute of Justice grant (Award No: 2018-DU-BX-0225), in which we further refined the kinetic model and developed a unified kinetic and thermodynamic approach to predict evaporation.
The proposed work seeks to address areas of future work highlighted in our previous NIJ award. As such, the focus is to validate the unified kinetic and thermodynamic approach to predict evaporation. This approach serves as the first step toward comprehensive evaluation of kinetic and thermodynamic models as both are defined on the same foundational basis. A comprehensive evaluation of the current unified approach will be conducted, which will include evaluating the performance of each model to predict evaporations conducted at high temperatures. The unified approach will then be extended to include oxygenated compounds, which are not currently represented in our modeling approach. The development of these models will ensure we have the capacity to predict evaporation of liquids representing any class defined in ASTM E1618. Finally, the models developed using the unified approach will be used to generate extensive reference collections of predicted chromatograms corresponding to liquids from different classes, evaporated to different extents, and at different temperatures. Application of these reference collections to identify evaporated liquids in submitted samples will then be demonstrated. At the end of this work, the most appropriate approach (kinetic or thermodynamic) to predict liquid evaporation will be determined and tools will be developed to assist with practical implementation in forensic laboratories. CA/NCF
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