Selecting Stable Metal Oxide Nanoparticle Additives for Hydrocarbon Fuels through a Predictive Thermal Stability Phase Map

High Resolution Image Download MS PowerPoint Slide Metal oxide nanoparticles are widely investigated as fuel additives in internal combustion engines, where they can enhance combustion efficiency and reduce emissions; however, their practical use is fundamentally constrained by the colloidal instability of the resulting nanofuels, triggered by the drastic reduction in base fluid viscosity at elevated temperatures. This study presents a predictive framework that delineates the thermophysical kinetic stability boundaries for ten different metal oxide nanoparticles in hydrocarbon media (iso-octane and n-dodecane, representing gasoline and diesel surrogates), independent of chemical stabilization. While the analytical model covers a broad range of oxides, the theoretical stability boundaries were experimentally corroborated as an idealized baseline through dynamic light scattering (DLS) measurements using three representative nanoparticles (CeO 2, Fe 2 O 3, SiO 2 ) selected to span the entire density spectrum. Analytical modeling based on a Lagrangian perspective, conducted within the 20–100 °C range, revealed that a temperature-induced viscosity loss of 55–65% suppresses the gain in thermal energy, driving the system into an advective sedimentation regime. Stability phase maps, constructed using the Peclet number and critical settling velocities, characterize safe operational domains as a function of particle density and temperature. The experimental results corroborated the theoretical limits, specifically showing that high-density CeO 2 undergoes catastrophic agglomeration (>600 nm) in iso-octane at 80 °C due to viscosity collapse. This study establishes a theoretical stability ceiling for nanofuel design and provides a transferable, transport-physics-based methodology for selecting a stable combination of nanoparticle type, base fuel, and operating temperature, transforming the conventional experimental trial-and-error process of nanofuel formulation into a rational design workflow.