Mixture‐Quantitative Structure–Property Relationship Approaches for Jet Fuel‐Component Blends: A Review

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.

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Publication Details

Journal
Molecular Informatics
Published
2026-08-26
DOI
https://doi.org/10.1002/minf.70050
Primary Topic
Advanced Combustion Engine Technologies
Type
article
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article

Mixture‐Quantitative Structure–Property Relationship Approaches for Jet Fuel‐Component Blends: A Review

Benoît Creton, Gilles Marcou, Mickaël Matrat, Erik Yeghyan
Molecular Informatics
Advanced Combustion Engine Technologies
article

Mixture‐Quantitative Structure–Property Relationship Approaches for Jet Fuel‐Component Blends: A Review

Benoît Creton, Gilles Marcou, Mickaël Matrat, Erik Yeghyan
article en

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.

Molecular InformaticsVol. 45(9)
IFP Énergies nouvelles (FR), Université de Strasbourg (FR)
Industry, innovation and infrastructure
Openalex Percentile: Top 18%
Advanced Combustion Engine Technologies
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