Laser-Promoted Generation of Cluster Ions at the Surfaces of Black Phosphorus Nanosheets and Black Phosphorus–Gold Nanocomposites

The lack of structural information on cluster ions generated from nanomaterials under laser irradiation limits our understanding of their behavior in laser desorption/ionization mass spectrometry (LDI-MS). To address this, the integration of nanomaterials as nanomatrices has significantly advanced LDI-MS, with density functional theory (DFT) serving as a powerful tool to uncover their electronic and structural characteristics. Recently, plasmonic black phosphorus nanosheets (BPNs)-gold nanocomposites (BP@Au) have emerged as promising nanomatrices for the sensitive detection of anticancer drugs in blood serum. Motivated by this, we investigated the electronic structures and cluster ion formation behaviors of BPNs and BP@Au under laser irradiation. Using the PBE functional, we identified stable ground-state geometries and local minima for selected clusters. The most thermodynamically stable isomers of P 3 + and P 5 + were identified with binding energies of −0.07 eV and −7.26 eV, respectively. For the gold–phosphide clusters (P n Au + ), the computed binding energies were 6.40 eV for PAu +, −1.96 eV for P 3 Au +, −19.48 eV for P 8 Au +, and −29.81 eV for P 11 Au + . Furthermore, vertical dissociation energies (E d ), Gibbs free energy (ΔG), and enthalpy changes (ΔH) were systematically evaluated for all possible dissociation pathways to identify the most favorable fragmentation channels of P n Au + clusters. Additionally, HOMO–LUMO (H-L) gap analyses were conducted to further evaluate and compare the relative electronic stability of these clusters. The structural features of these clusters may partially reflect the layered configuration of BPNs and BP@Au nanocomposites; however, this was not directly verified experimentally. This structural correspondence may contribute to improved ionization efficiency and reduced spectral background associated with monoisotopic signals. These theoretical insights provide a foundation for rational nanomatrix design and deepen our understanding of cluster behavior in LDI-MS.