In the present work, we report the development of models for the prediction of two fuel properties: flash points (FPs) and cetane numbers (CNs), using quantitative structure property relationship (QSPR) approaches. Compounds inside the scope of the QSPR models are those likely to be found in alternative jet and diesel fuels, i.e., hydrocarbons, alcohols, and esters. A database containing FPs and CNs for these types of molecules has been built using experimental data available in the literature. Various approaches have been used, ranging from those leading to linear models, such as genetic function approximation and partial least squares, to those leading to nonlinear models, such as feed-forward artificial neural networks, general regression neural networks, support vector machines, and graph machines. Except for the case of the graph machine method, for which the only inputs are the simplified molecular input line entry specification (SMILES) formulas, previously listed approaches working on molecular descriptors and functional group count descriptors were used to build specific models for FPs and CNs. For each property, the predictive models return slightly different responses for each molecular structure. Thus, final models labeled as "consensus models" were built by averaging the predicted values of selected individual models. Predicted results were compared with respect to experimental data and predictions of existing models in the literature. Models were used to predict FPs and CNs of molecules for which to the best of our knowledge there is no experimental data in the literature. Using information in the database, evolutions of properties when increasing the number of carbon atoms in families of compounds were studied.

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Résumé -Potentiel de l'éthanol en tant que carburant pour un moteur dédié -Un des défis majeurs de l'industrie automobile est de réduire les émissions de gaz à effet de serre et, en particulier, celles du CO 2 . Plusieurs programmes de recherche sont en cours sur ce sujet, visant la réduction de la consommation des véhicules, mais aussi l'optimisation de la composition des carburants. Il est en effet essentiel de prendre en compte l'ensemble du processus, de la production des carburants aux émissions des véhicules, et un bilan "du puits à la roue" doit être effectué pour chaque technologie.L'éthanol possède des atouts importants pour satisfaire ces nouvelles contraintes : étant extrait de la biomasse, son bilan d'émission du CO 2 "du puits à la roue" est favorable. De plus, ses propriétés, en particulier en termes d'indice d'octane et de chaleur latente de vaporisation, permettent une optimisation du fonctionnement du moteur.La présente étude a pour but d'évaluer la voie éthanol. Les moyens de production sont considérés, en particulier leur bilan énergétique. Les principaux avantages et inconvénients de l'utilisation d'un tel carburant sont résumés. Enfin, nous présentons un exemple des gains qui peuvent être réalisés en optimisant un moteur pour l'utilisation de l'éthanol pur. Un moteur suralimenté de petite cylindrée a en effet été optimisé afin de bénéficier du potentiel de l'éthanol, notamment en termes de réduction du cliquetis. Les performances de ce moteur sont comparées à celles du moteur initial à essence, démontrant que des gains importants peuvent être obtenus avec une telle technologie. Abstract -Potentiality of Ethanol as a Fuel for Dedicated Engine

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Because of the recent changes in the formulation and handling of middle-distillate fuels, oxidation stability is becoming an increasingly important issue. However, liquid-phase oxidation kinetics of middle-distillate fuels remains poorly understood. The purpose of this study was to gain an in-depth understanding of the impact of fatty acid methyl ester (FAME) addition on autoxidation kinetics. A detailed kinetic mechanism for the autoxidation of a n-dodecane/methyl oleate (MO) surrogate mixture was generated and validated against original well-controlled accelerated oxidation experiments. Results emphasize the nonlinear oxidation promoting effect of MO on n-dodecane autoxidation. Pathway analyses reveal that HO 2 and OH propagation steps as well as the duration of initiation and propagation phases strongly affected sensitivity analysis by MO addition. On the basis of these analyses and the detailed mechanism, an analytical model was derived and validated against experiments on binary surrogate mixtures as well as blends of conventional commercial fuels and FAME. These results open up the use of bottom-up liquid-phase oxidation modeling strategies for the in silico formulation of alternative fuels and the design of innovative injection fuel systems.