Octane Prediction from Infrared Spectroscopic Data-Reference-Cited by-同舟云学术

Octane Prediction from Infrared Spectroscopic Data

Published:2019-10-22 Issue:1 Volume:34 Page:817-826
ISSN:0887-0624
Container-title:Energy & Fuels
language:en
Short-container-title:Energy Fuels

Author:

Al Ibrahim Emad¹,Farooq Aamir¹^ORCID

Affiliation:

1. Clean Combustion Research Center (CCRC), Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia

Funder

King Abdullah University of Science and Technology

Publisher

American Chemical Society (ACS)

Subject

Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.energyfuels.9b02816

Reference55 articles.

1. Test Method for Research Octane Number of Spark-Ignition Engine Fuel

2. Test Method for Motor Octane Number of Spark-Ignition Engine Fuel

3. A Study of the Structure–Octane Number Relationship for Hydrocarbons

4. Models for the calculation and prediction of the octane and cetane numbers of individual hydrocarbons

5. A methodology to relate octane numbers of binary and ternary n-heptane, iso-octane and toluene mixtures with simulated ignition delay times

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview;Journal of Chemical Information and Modeling;2024-01-29

2. The blending behavior in infrared spectra of oxygenated fuel blends;AIAA SCITECH 2024 Forum;2024-01-04

3. Machine learning-driven screening of fuel additives for increased spark-ignition engine efficiency;Proceedings of the Combustion Institute;2024

4. Designing green chemicals by predicting vaporization properties using explainable graph attention networks;Green Chemistry;2024

5. Augmentations for selective multi-species quantification from infrared spectroscopic data;Chemometrics and Intelligent Laboratory Systems;2023-09