📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Liquid synthetic fuels design guided by chemical structure: A machine learning perspective (2024)

First Author: Freitas R

Attributed to: Utilisation of Synthetic Fuels for "Difficult-to-Decarbonise" Propulsion funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.46855/energy-proceedings-10921

Publication URI: http://dx.doi.org/10.46855/energy-proceedings-10921

Type: Preprint

ISSN: 20042965