Linking Consistency in Experimental Results to Surface Morphology: A Novel Hypothesis on Laser-Ignited Combustion in Random Particle Packings

Laser-ignited particle combustion is critical to energy, aerospace, and defense applications, yet understanding its physicochemical mechanisms is hindered by poor reproducibility in combustion data from randomly packed samples. While classical theory attributes data inconsistency to variations in packing density, we propose instead that consistency of the surface layer morphology—given the nanoscale laser penetration depth—is the dominant factor. A two-dimensional Discrete Element Model showed that increasing particle layers markedly reduces surface topography conformity, while gravitational settling maintains packing density near its theoretical maximum. An innovative constrained droplet method was developed for sample preparation, integrating multi-stage sieving, equal-circle packing in a circle theory, alongside droplet deposition to build multilayer samples mirroring computational models. In-situ laser ignition diagnostics revealed that key combustion metrics—spectral profiles, temporal evolution, ignition delay, and combustion duration—exhibit a rapid decline in consistency with increasing layers, closely matching the simulated decay in surface morphology conformity. Contrary to long-held assumptions, this work robustly shows that surface morphology governs laser-ignition experimental reproducibility. This paradigm-shifting finding redefines the controlling mechanism in laser-ignited combustion of random particle packings, thereby provides a method for refining sample preparation and enables the accurate determination of key parameters that remain elusive with conventional approaches.