Descriptors-based machine-learning prediction of cetane number using quantitative structure–property relationship-Reference-Cited by-同舟云学术

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Descriptors-based machine-learning prediction of cetane number using quantitative structure–property relationship

Published:2024-09 Issue: Volume:17 Page:100385
ISSN:2666-5468
Container-title:Energy and AI
language:en
Short-container-title:Energy and AI

Author:

Freitas Rodolfo S.M.^ORCID,Jiang Xi

Funder

Engineering and Physical Sciences Research Council

Publisher

Elsevier BV

Reference72 articles.

1. Global CO2 emissions from transport by sub-sector in the Net Zero Scenario;IEA,2000

2. Sustainable synthetic carbon based fuels for transport: Policy briefing;Hutchings,2019

3. Literature review on life cycle assessment of transportation alternative fuels;Liu;Environ Technol Innov,2023

4. Synthetic fuels based on dimethyl ether as a future non-fossil fuel for road transport from sustainable feedstocks;Styring;Front Energy Res,2021

5. An overview of major synthetic fuels;Ram;Energies,2023

Cited by 1 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. Numerical Approaches to Determine Cetane Number of Hydrocarbons and Oxygenated Compounds, Mixtures, and their Blends;Energy & Fuels;2024-08-05

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