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December 8, 2025Energies4 citationsOpen Access

Evaluating Fuel Properties of SAF Blends: From Component-Based Estimation to Molecular Dynamics

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FBFozia BatoolVVVladislav VasilyevJWJames Wang

Key Points

  • Thermophysical properties of sustainable aviation fuels are critical for reducing aviation's carbon footprint, and effective evaluation methods are essential.
  • Key metrics include density, viscosity, and thermal stability, with molecular dynamics simulations offering high accuracy in modeling these properties.
  • Approaches combining molecular dynamics and machine learning enhance predictions of fuel properties, optimizing the design of sustainable aviation fuels.
  • Future research focuses on integrating reactive frameworks for pyrolysis and oxidation studies, indicating the potential for improved fuel formulations.

Abstract

The transition to sustainable aviation fuel (SAF) is critical for reducing the carbon footprint of the aviation sector while ensuring compatibility with current engines and infrastructure. Regulatory constraints, such as ASTM D7566, currently limit SAF blending to 50% in commercial flights, emphasizing the need for accurate evaluation of SAF properties to enable broader adoption. This review presents an updated overview of fuel studies evaluating key thermophysical and transport properties of hydrocarbon-based SAFs—including density, viscosity, specific energy, flash point, and thermal stability—with particular emphasis on molecular dynamics (MD) simulations. Among the MD simulations, the OPLS-AA force field demonstrates high accuracy in modeling liquid-phase hydrocarbons and shows strong agreement with experimental data. Coupled with MD engines like LAMMPS and GROMACS, it enables scalable and efficient simulations of SAF blends. Emerging research trends highlight integrative approaches that combine classical MD and machine learning (ML) in fuel property prediction, and force-field optimization to improve predictive capability. Future research in fuel is moving toward multi-force-field coupling using reactive frameworks such as ReaxFF for studying pyrolysis and oxidation, and data-driven experiments with in situ simulation feedback loops to accelerate SAF design and facilitate wider implementation in aviation.

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Cite This Study

Batool et al. (2025) studied this question.

synapsesocial.com/papers/694020e82d562116f28fac83https://doi.org/10.3390/en18246401
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