Computational Investigation of REST‐Based Fluorescent Detection of Explosives Using Super Yellow Polymer

The effective detection of explosive materials is essential for military, security, mining, and various civilian applications. In this study, two major processes involved in explosive detection, sample collection and detection mechanisms, were investigated separately due to their distinct characteristics. Computational chemistry methods were employed to minimize human involvement by facilitating the detection of landmines in hazardous mine‐contaminated areas. The aim of these calculations was to investigate the detection mechanisms of explosives at the molecular scale and to examine the affinity of explosives toward newly developed polymeric materials in comparison with experimental findings, particularly for explosives that are difficult to detect because of their low vapor pressures or similar absorption spectra. A variety of molecular complexes consisting of ten different nitroaromatic, nitro and nitramine explosive molecules with the preconcentrator (molecular magnet) Aflas polymer and the photoluminescent super yellow polymer were modeled using density functional theory (DFT). The detection mechanism was analyzed at the molecular level by evaluating intermolecular interaction energies and changes in the fluorescence spectra of probe–analyte complexes. The results reveal qualitative trends in molecular recognition and probe–analyte affinity that may influence sensing behavior.