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
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Energy Sciences
INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
Organic Chemistry
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container_end_page 12245
container_issue 42
container_start_page 12236
container_title Industrial & engineering chemistry research
container_volume 56
creator Kubic, William L
Jenkins, Rhodri W
Moore, Cameron M
Semelsberger, Troy A
Sutton, Andrew D
description 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.
doi_str_mv 10.1021/acs.iecr.7b02753
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subjects Energy Sciences
INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
Organic Chemistry
title Artificial Neural Network Based Group Contribution Method for Estimating Cetane and Octane Numbers of Hydrocarbons and Oxygenated Organic Compounds
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