Mixture‐Quantitative Structure–Property Relationship Approaches for Jet Fuel‐Component Blends: A Review
Abstract
Jet fuels (JFs) and sustainable aviation fuels (SAFs) are complex hydrocarbon mixtures whose properties must meet strict international specifications to ensure consistent quality. Their increasing variability, driven by environmental and process constraints, raises multiple questions regarding the relationship between fuel composition, safety, and performance. In this context, predictive models can help support fuel formulation while reducing experimental effort. Quantitative structure–property relationship (QSPR) methods have been applied to fuel components such as hydrocarbons to predict various properties, showing promising results but often with limited accuracy and applicability. Several studies have also investigated mixture‐QSPR (M‐QSPR) approaches for hydrocarbon systems involving constituents also present in fuels; however, very few studies directly address real fuel mixtures. This is because M‐QSPR remains particularly challenging due to mixture interactions, data scarcity, representation difficulties, and validation issues. This review evaluates past M‐QSPR studies on fuels, fuel‐component mixtures, and general M‐QSPR methodologies to identify current advances, limitations, and gaps and to outline strategies for developing M‐QSPR models for JFs.
Related
- Synthesis and Structure–Photophysical Property Relationship of CF₂CF₂-Containing Tetracyclic Isoquinoline Derivative
- Two-Dimensional C60 Fullerene Networks (Graphullerene): Structure–Property Relations, Quantitative Benchmarking and Future Directions
- First hyperpolarizability of dithienylethene-based photoswitches: a structure-property relationship study.
- Studying the structure–property relationship in Zr-BDI MOF for noble-metal-free selective photocatalytic CO2 conversion to CO
- Insights into the Structural-Transport Property Relationship of the Size-Dependent Organic Molecules on Metal Surfaces
BibTeX
@article{yeghyan2026mixturequantitative,
title = {{Mixture‐Quantitative Structure–Property Relationship Approaches for Jet Fuel‐Component Blends: A Review}},
author = {Erik Yeghyan and Benoit Creton and Mickaël Matrat and Gilles Marcou},
journal = {Molecular Informatics},
year = {2026},
month = aug,
doi = {10.1002/minf.70050},
url = {https://ifp.hal.science/hal-05773658v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Mixture‐Quantitative Structure–Property Relationship Approaches for Jet Fuel‐Component Blends: A Review
AU - Erik Yeghyan
AU - Benoit Creton
AU - Mickaël Matrat
AU - Gilles Marcou
PY - 2026
DA - 2026/08/26
JO - Molecular Informatics
DO - 10.1002/minf.70050
UR - https://ifp.hal.science/hal-05773658v1
AB - Jet fuels (JFs) and sustainable aviation fuels (SAFs) are complex hydrocarbon mixtures whose properties must meet strict international specifications to ensure consistent quality. Their increasing variability, driven by environmental and process constraints, raises multiple questions regarding the relationship between fuel composition, safety, and performance. In this context, predictive models can help support fuel formulation while reducing experimental effort. Quantitative structure–property relationship (QSPR) methods have been applied to fuel components such as hydrocarbons to predict various properties, showing promising results but often with limited accuracy and applicability. Several studies have also investigated mixture‐QSPR (M‐QSPR) approaches for hydrocarbon systems involving constituents also present in fuels; however, very few studies directly address real fuel mixtures. This is because M‐QSPR remains particularly challenging due to mixture interactions, data scarcity, representation difficulties, and validation issues. This review evaluates past M‐QSPR studies on fuels, fuel‐component mixtures, and general M‐QSPR methodologies to identify current advances, limitations, and gaps and to outline strategies for developing M‐QSPR models for JFs.
SN - 1868-1743
SN - 1868-1751
ER -