Artificial Neural Network Based Group Contribution Method for Estimating Cetane and Octane Numbers of Hydrocarbons and Oxygenated Organic Compounds-Reference-Cited by-同舟云学术

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

Published:2017-10-10 Issue:42 Volume:56 Page:12236-12245
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Kubic William L.¹^ORCID,Jenkins Rhodri W.¹,Moore Cameron M.¹,Semelsberger Troy A.¹,Sutton Andrew D.¹

Affiliation:

1. Applied Engineering and Technology Division, ‡Chemistry Division, and §Material Physics Applications Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States

Funder

Los Alamos National Laboratory

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.7b02753

Reference41 articles.

1. Process Development

2. BioCompoundML: A General Biofuel Property Screening Tool for Biological Molecules Using Random Forest Classifiers

3. Quantitative Correlation of Physical and Chemical Properties with Chemical Structure: Utility for Prediction

4. Detailed Composition-Based Model for Predicting the Cetane Number of Diesel Fuels

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