Enhanced fission track resolution using aerogel spacers for automated nuclear forensic analysis and fissile isotope differentiation

Nuclear forensics depends on accurate identification of fissile isotopes for security and nonproliferation purposes. However, traditional fission track analysis (FTA) is largely manual, operator-dependent, and incapable of distinguishing isotopes based on track features. This research aims to modernize FTA by developing a physics-informed, automated framework that combines Monte Carlo simulations (GEANT4), synthetic data generation, and image-processing algorithms for isotope differentiation. Simulations were performed for ²³³U, ²³⁵U, and ²²⁹Th using a LEXAN® polycarbonate solid-state nuclear track detector (SSNTD) with Aerogel spacers of various densities to improve track resolution. Synthetic datasets were analyzed through the newly developed FTA-Finder application. Results indicate that a 50 μm aerogel spacer enhances the separation of light and heavy fission fragment clusters. Image-processing algorithms successfully differentiated isotopes in synthetic data by reconstructing isotope-specific track-length distributions and angular spreads. These findings demonstrate that morphology-based parameters can serve as isotopic fingerprints, paving the way for automated, reproducible, and high-accuracy nuclear forensic analysis. The framework's integration into practical safeguards investigations could improve the reliability and speed of fissile material identification worldwide.