Sustainable aviation fuel (SAF) remains the only near‑term decarbonisation pathway fully compatible with existing long‑haul aircraft and current fuel infrastructure. Power‑to‑Liquid (PtL) SAF, in particular, depends critically on large‑scale renewable hydrogen availability, positioning Australia—with its exceptional solar resources—as a strategic leader in future SAF production. Although decades of experimental fuel studies have generated valuable empirical knowledge, a significant gap persists in molecular‑level electronic‑structure understanding—precisely the insight required for the rational design of high‑energy‑density (HED) components for advanced PtL SAF formulations.
Within this context, we integrate machine learning (ML) with density functional theory (DFT) to screen and investigate strained multicyclic hydrocarbons at the molecular and electronic‑structure level. Our recent work examines JP‑10 (Jet Propellant‑10, C₁₀H₁₆, exo‑tetrahydrodicyclopentadiene), norbornadiene/quadricyclane (NBD/QC), and newly explored adamantane‑based fuels. For JP‑10, we reveal distinct electronic‑structure differences between the exo (fuel) and endo (solid) isomers and present new results on first ionization potentials (IR), radical reactivity patterns, and 13C NMR signatures. Complementary studies on adamantane and its methylated derivatives establish a rigorous structure–property framework linking orbital topology, molecular symmetry, phase behaviour, and liquid‑phase HED fuel performance. I will also briefly introduce several interconnected SAF research projects in my laboratory: ML pre-screening of strained HED hydrocarbons; ML‑assisted DFT analysis of strain‑energy‑driven reactivity; molecular‑dynamics prediction of fuel‑blend properties; techno‑economic analysis (TEA) and life‑cycle assessment (LCA) of SAF production pathways; TEA of plasma‑driven methanation systems; and DFT‑guided catalyst design for PtL synthesis. These molecular‑level investigations form a coordinated and unified electronic‑structure‑driven strategy for advancing next‑generation HED SAF components—from quantum‑chemical insight to systems‑level deployment.