DFT analysis: Fe4 cluster and Fe(110) surface interaction studies with pyrrole,furan, thiophene,and selenophene molecules

DFT studies of both the Fe₄ cluster and the Fe(110) surface interaction with pyrrole, furan, thiophene, and selenophene showed that selenophene forms a stabler adsorbate iron complex than the other heterocyclic molecules; this is consistent with the binding energy data that were calculated between the Fe cluster and the Fe(110) surface with the heterocycles. Furthermore, when the adsorption of the compounds with the iron cluster was analyzed by molecular orbital studies, the orbitals of selenophene overlapped more strongly with the Fe atom than that of the other molecules. In TD-DFT, the π → π* peak observed for the molecules disappeared when they formed complexes, and there appeared a charge transfer band (ligand to metal), thus confirming the coordination of these molecules with the cluster. The data suggest that the chemisorption is an exothermic process.     

Large‐volume sample stacking with polarity switching for analysis of azo dyes in water samples by capillary electrophoresis

ABSTRACT

A simple, fast and efficient on-line pre-concentration method (large-volume sample stacking) by capillary electrophoresis was proposed for determination of azo dyes residues (allura red [AR], sunset yellow [SY] and tartrazine [TAR]) in water samples. Pre-concentration variables involved in the system were optimised using of a Box–Bhenken design. Under the optimal conditions: injection time 150.0 s, pre-concentration time 120.0 s and reverse potential ?8.0 kV, the proposed methodology improved the analytical sensibility achieving limits of detection of 21.0–41.4 µg L^?1 with enrichment factors of 82.1–210.8 fold. The large-volume sample stacking-capillary electrophoresis method was validated and applied to determine azo dyes residues in 20 water samples (bottled, spring and tap water). Two samples were positive for sunset yellow and tartrazine with a concentration of 25.3 and 30.2 µg L^?1 and % RSD less than 10.0% in all cases.     

Nonconventional C–H···Cu Interaction Between Copper Cun Clusters (n = 3–20) and Aromatic Compounds

The present study examines bonding patterns between copper Cu_n clusters (n?=?3–20) and aromatic compounds (benzene, phenol, and benzaldehyde) using a density-functional theory (DFT) approach. Hirshfeld population, natural bond orbital (NBO), molecular orbitals, and quantum theory of atoms in molecules (QTAIM) analyses suggested the formation of two types of interactions Cu–arene and C–H···Cu, in the complexation of copper clusters by an aromatic compound.