Impact of isoelectronic substitution on the excited state processes in polycyclic aromatic hydrocarbons: a joint experimental and theoretical study of 4 a ,8 a -azaboranaphthalene.
Floriane SturmMichael BühlerChristoph StapperJohannes S SchneiderHolger HeltenIngo FischerMerle Insa Silja RöhrPublished in: Physical chemistry chemical physics : PCCP (2024)
Substituting CC with the isoelectronic BN units is a promising approach to modify the optoelectronic properties of polycyclic aromatic hydrocarbons. While computational studies have already addressed trends in the electronic structure of the various isosteres, experimental data are still scarce. Here, the excited state spectroscopy and dynamics of 4 a ,8 a -azaboranaphthalene were studied by picosecond time-resolved photoionization in a supersonic jet and analyzed with the aid of XMS-CASPT2 and time-dependent DFT calculations. A resonance-enhanced multiphoton ionization spectrum (REMPI) reveals the S 1 origin at = 33 830 ± 12 cm -1 . Several vibrational bands were resolved and assigned by comparison with the computations. A [1+1] photoelectron spectrum via the S 1 origin yielded an adiabatic ionization energy of 8.27 eV. Selected vibrational bands were subsequently investigated by pump-probe photoionization. While the origin as well as several low-lying vibronic states exhibit lifetimes in the ns-range, a monoexponential decay is observed at higher excitation energies, ranging from 400 ps at +1710 cm -1 to 13 ps at +3360 cm -1 . The deactivation is attributed to an internal conversion of the optically excited S 1 state via a barrier that gives access to a conical intersection (CI) to the S 0 state. The doping significantly changes the energetic ordering of CIs and lowers the corresponding energy barrier for the associated deactivation pathway, as revealed by nudged elastic band (NEB) calculations.
Keyphrases
- density functional theory
- energy transfer
- polycyclic aromatic hydrocarbons
- molecular dynamics
- molecular dynamics simulations
- quantum dots
- gas chromatography
- electronic health record
- high frequency
- big data
- magnetic resonance
- machine learning
- mass spectrometry
- living cells
- case control
- deep learning
- contrast enhanced