Evaluating Fuel Properties of Strained Polycycloalkanes for High-Performance Sustainable Aviation Fuels

Dilip Rijal, Vladislav Vasilyev, Yunxia Yang and Feng Wang ()
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Dilip Rijal: School of Science, Computing and Emerging Technologies, Swinburne University of Technology, Melbourne, VIC 3122, Australia
Vladislav Vasilyev: National Computational Infrastructure, Australian National University, Canberra, ACT 0200, Australia
Yunxia Yang: CSIRO Energy, Melbourne, VIC 3168, Australia
Feng Wang: School of Science, Computing and Emerging Technologies, Swinburne University of Technology, Melbourne, VIC 3122, Australia

Energies, 2025, vol. 18, issue 19, 1-18

Abstract: Sustainable aviation fuel (SAF) is a drop-in alternative to conventional jet fuels, designed to reduce greenhouse gas (GHG) emissions while requiring minimal infrastructure changes and certification under the American Society for Testing and Materials (ASTM) D7566 standard. This study assesses recently identified high-energy-density (HED) strained polycycloalkanes as SAF candidates. Strain energy (E se ) was calculated using density functional theory (DFT), while operational properties such as boiling point (BP) and flash point (FP) were predicted using support vector regression (SVR) models. The models demonstrated strong predictive performance (R 2 > 0.96) with mean absolute errors of 6.92 K for BP and 9.58 K for FP, with robustness sensitivity analysis. It is found that approximately 65% of these studied polycycloalkanes fall within the Jet A fuel property boundaries. The polycycloalkanes (C 9 –C 15 ) with strain energies below approximately 60 kcal/mol achieve an balance between energy density and ignition safety, aligning with the specifications of Jet A. The majority of structures were dominated by five-membered rings, with a few three- or four-membered rings enhancing favorable trade-offs among BP, FP, and HED. This early pre-screening indicates that moderately strained polycycloalkanes are safe, energy-dense candidates for next-generation sustainable jet fuels and provide a framework for designing high-performance SAFs.

Keywords: boiling point; flash point; machine learning; strained polycycloalkanes; sustainable aviation fuel (SAF) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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