title: Revealing intuitively assessable chemical bonding patterns in organic aromatic molecules via adaptive natural density partitioning.
abstract: The newly developed adaptive natural density partitioning (AdNDP) method has been applied to a series of organic aromatic mono- and polycyclic molecules, including cyclopropenyl cation, cyclopentadienyl anion, benzene, naphthalene, anthracene, phenanthrene, triphenylene, and coronene. The patterns of chemical bonding obtained by AdNDP are consistent with chemical intuition and lead to unique, compact, graphic formulas. The resulting bonding patterns avoid resonant description and are always consistent with the point symmetry of the molecule. The AdNDP representation of aromatic systems seamlessly incorporates localized and delocalized bonding elements.
authors.affiliation: Department of Chemistry and Biochemistry, Utah State University, 0300 Old Main Hill, Logan, Utah 84322, USA.
authors.forename: Dmitry Yu
authors.initials: DY
authors.lastname: Zubarev
authors.forename: Alexander I
authors.initials: AI
authors.lastname: Boldyrev