Threshold Sooting Index of Sustainable Aviation Fuel Candidates From Composition Input Alone: Progress Toward Uncertainty Quantification

13-C-AJFF-UD-026, 027This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as: Energy Fuels 2022, 36, 4, 1916\u20131928 Publication Date: January 31, 2022 https://doi.org/10.1021/acs.energyfuels.1c03794 Copyright \ua9 2022 The Authors. Published by American Chemical SocietyA quantitative structure\u2013property relationship model has been developed to predict the threshold sooting index (TSI) of arbitrary mixtures of aliphatic and aromatic hydrocarbons of known composition. The model employs contributions from eight molecular fragments plus a global shift and a penalty factor for naphthenic compounds. For each coefficient, the contributions were determined by a constrained regression to data from five different experimental campaigns, which were stitched together by setting the TSI of methylcyclohexane to 5 and the TSI of 1-methylnaphthalene to 100. Unique to this study; the TSI of 1,3,5-trimethylbenzene was restricted to the range of 54.7 and 63.1, which significantly constrains uncertainty. Within the composite training dataset, which contained 65 molecules and 124 data points, including simple mixtures, the model was found to match 95% of the data within 8.9 TSI. Validation of the model against n-butylcyclohexane, dimethylcyclooctane, and a six-component surrogate jet fuel shows prediction to be well within the 95-percentile confidence band of the experiment. This model is the first to integrate the linear blending rule for the TSI with a linear quantitative structure\u2013property relationship model for the TSI, and the first time that referee controls have been applied to ensure that all datasets, experimental and modeled, are normalized to the same scale