化学
卟啉
锌
X射线光电子能谱
自由基
电化学
光谱学
光化学
结晶学
物理化学
有机化学
电极
核磁共振
量子力学
物理
盐(化学)
作者
James G. Goll,K. T. Moore,Abhik Ghosh,Michael J. Therien
摘要
The synthesis, optical spectroscopy, photophysical properties, electrochemistry, and X-ray photoelectron spectroscopy of a series of [5,10,15,20-tetrakis(perfluoroalkyl)porphinato]zinc(II) complexes and their free base analogs are reported. The title compounds were prepared by a condensation methodology that utilizes perfluoro-1-(2‘-pyrrolyl)-1-alkanol precursors and employs continuous water removal throughout the course of the reaction to yield the meso perfluorocarbon-substituted porphyrins. The nature of the porphyrin-pendant meso-perfluoroalkyl group exerts considerable influence over the macrocycle's solubility properties. The structure of the monopyridyl adduct of [5,10,15,20-tetrakis(heptafluoropropyl)porphinato]zinc(II) features an S4-distorted porphyrin core; X-ray data are as follows: P1̄ with a = 15.1330(5) Å, b = 19.2780(6) Å, c = 14.6030(4) Å, α = 110.220(2)°, β = 103.920(2)°, γ = 85.666(2)°, V= 3880.1(2) Å3, dcalc = 1.887 g cm-3, and Z = 4. Electrochemical studies carried out on these porphyrin and (porphinato)zinc(II) complexes indicate that meso-perfluoroalkylporphyrins are among the most electron-deficient porphyrinic species known. X-ray photoelectron spectroscopy experiments corroborate the electron poor nature of these systems and evince extreme stabilization of the nitrogen 1s orbitals, consonant with particularly effective removal of electron density from the macrocycle by the meso-perfluoroalkyl moieties that is modulated by σ-symmetry orbitals. The photophysical properties of these compounds differ from all other previously reported highly electron deficient porphyrin macrocycles in that they possess long-lived, fluorescent excited states; hence their optoelectronic features are consistent with a variety of excited-state electron-transfer quenching schemes in which both 1ZnP* and 1H2P* can be utilized as potent photooxidants.
科研通智能强力驱动
Strongly Powered by AbleSci AI