Journal
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
Volume 56, Issue 42, Pages 12236-12245Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.iecr.7b02753
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Funding
- Los Alamos National Laboratory LDRD program [LDRD20160095ER]
- National Nuclear Security Administration of the U.S. Department of Energy [DE-AC5206NA25396]
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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.
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