Artificial Neural Network Based Group Contribution Method for Estimating Cetane and Octane Numbers of Hydrocarbons and Oxygenated Organic Compounds

Artificial Neural Network Based Group Contribution Method for Estimating Cetane and Octane Numbers of Hydrocarbons and Oxygenated Organic Compounds

Chemical pathways for converting biomass into fuels produce compounds for which key physical and chemical property data are unavailable. We developed an artificial neural network based group contribution method for estimating cetane and octane numbers that captures the complex dependence of fuel pro...

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Veröffentlicht in:Industrial & engineering chemistry research 2017-10, Vol.56 (42), p.12236-12245
Hauptverfasser: Kubic, William L, Jenkins, Rhodri W, Moore, Cameron M, Semelsberger, Troy A, Sutton, Andrew D
Format: Artikel
Sprache:eng
Schlagworte:
Energy Sciences
INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
Organic Chemistry
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Zusammenfassung:Chemical pathways for converting biomass into fuels produce compounds for which key physical and chemical property data are unavailable. We developed an artificial neural network based group contribution method for estimating cetane and octane numbers that captures the complex dependence of fuel properties of pure compounds on chemical structure and is statistically superior to current methods.
ISSN:0888-5885
1520-5045
DOI:10.1021/acs.iecr.7b02753