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Linear Four-Chalcogen Interactions in Radical Cationic and Dicationic Dimers of 1,5-(Dichalcogena)canes: Nature of the Interactions Elucidated by QTAIM Dual Functional Analysis with QC Calculations.

Satoko HayashiKengo NagataShota OtsukiWaro Nakanishi
Published in: The journal of physical chemistry. A (2017)
The dynamic and static nature of extended hypervalent interactions of the BE···AE···AE···BE type are elucidated for four center-seven electron interactions (4c-7e) in the radical cationic dimers (1·+) and 4c-6e in the dicationic dimers (12+) of 1,5-(dichalcogena)canes (2: AE(CH2CH2CH2)2BE: AE, BE = S, Se, Te, and O). The quantum theory of atoms-in-molecules dual functional analysis (QTAIM-DFA) is applied for the analysis. Total electron energy densities Hb(rc) are plotted versus Hb(rc) - Vb(rc)/2 [= (ℏ2/8m)∇2ρb(rc)] at bond critical points (BCPs) of the interactions, where Vb(rc) values show potential energy densities at BCPs. Data from the fully optimized structures correspond to the static nature of the interactions. Those from the perturbed structures around the fully optimized ones are also plotted, in addition to those of the fully optimized ones, which represent the dynamic nature of interactions. The BE···AE-AE···BE interactions in 12+ are stronger than the corresponding ones in 1·+, respectively. On the one hand, for 12+ with AE, BE = S, Se, and Te, AE···AE are all classified by the shared shell interactions and predicted to have the weak covalent nature, except for those in 1a2+ (AE = BE = S) and 1d2+ (AE = BE = Se), which have the nature of regular closed shell (r-CS)/trigonal bipyramidal adduct formation through charge transfer (CT-TBP). On the other hand, AE···BE are predicted to have the nature of r-CS/molecular complex formation through charge transfer for 1a2+, 1b2+ (AE = Se; BE = S), and 1d2+ or r-CS/CT-TBP for 1c2+ (AE = Te; BE = S), 1e2+ (AE = Te; BE = Se), and 1f2+ (AE = BE = Te). The BE···AE-AE···BE interactions in 1·+ and 12+ are well-analyzed by applying QTAIM-DFA.
Keyphrases
  • computed tomography
  • magnetic resonance imaging
  • mass spectrometry
  • machine learning
  • molecular dynamics simulations
  • positron emission tomography
  • density functional theory
  • pet ct
  • neural network
  • dual energy