Mr. Camden Boyle Profile

Camden Boyle

at Univ of Missouri

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Proceedings Article | 15 June 2023 Presentation + Paper

Towards automatic characterization of nano-energetic material response to directed energy

Timothy Gaines, Camden Boyle, J. Alex Hurt, Matthew Maschmann, James Keller, Grant Scott, Stanton Price

Proceedings Volume 12513, 1251304 (2023) https://doi.org/10.1117/12.2663877

KEYWORDS: Sintering, Performance modeling, Random forests, Particles, Feature extraction, Image processing, Nanoparticles, Aluminum, Image classification

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Nanoenergetic materials offer high-density energy storage that may be reacted to produce heat and release gaseous products. However, the fundamental reaction mechanisms of isolated nanoenergetic fuel particles (typically aluminum - AL) remain poorly understood. In this study, the structure-property relationships of photothermally heated AL nanoparticles are explored using an optical microscope setup and laser-based photothermal heating. Our research explores optical imaging and computer vision techniques to measure distinctive features from images captured before and after directed energy excitation of nanoenergetic particles. These features are used to describe the reactions in the pursuit of creating an automated nanoenergetic material reaction characterization model. Specifically, optical imagery of nano-aluminum particle clusters is taken before and after the reaction is initiated via laser irradiation. Through image preprocessing and registration, we remove untargeted nanoparticle clusters and align the images. We then classify particle reactions into three classes, Spallation, Sintering, or a Combination of both, through an examination of various features derived from our preprocessed imagery. These techniques serve as tools to aid researchers in quantitatively measuring reaction properties, such as loss of mass, and accelerating the search for optimized reaction parameters.

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