Amplification of Dissymmetry Factors in π-Extended [7]- and [9]Helicenes

Abstract

π-Extended helicenes constitute an important class of polycyclic aromatic hydrocarbons with intrinsic chirality. Herein, we report the syntheses of π-extended [7]helicene 4 and π-extended [9]helicene 6 through regioselective cyclodehydrogenation in high yields, where a “prefusion” strategy plays a key role in preventing undesirable aryl rearrangements. The unique helical structures are unambiguously confirmed by X-ray crystal structure analysis. Compared to the parent pristine [7]helicene and [9]helicene, these novel π-extended helicenes display significantly improved photophysical properties, with a quantum yield of 0.41 for 6 . After optical resolution by chiral high-performance liquid chromatography, the chiroptical properties of enantiomers 4 - P / M and 6 - P / M are investigated, revealing that the small variation in helical length from [7] to [9] can cause an approximately 10-fold increase in the dissymmetry factors. The circularly polarized luminescence brightness of 6 reaches 12.6 M –1 cm –1 as one of the highest among carbohelicenes.

Pathways to increase the dissymmetry in the interaction of chiral light and chiral molecules

“…20 Extending the size of a chromophore is not limited to conventional covalent chemistry; supramolecular and dynamiccovalent assembly have proved to be particularly important strategies: using point chirality as a means to bias the assembled system into a helical structure of one dominant handedness. 21,22 In such situations, the assembly adopts a helical configuration, resulting in a chiral environment at the chromophores, which dominates the chiroptical response.…”

Stacked Ensemble Machine Learning for Range-Separation Parameters

“…4 and Table S8): many functionals that had significantly overestimated Finally, we benchmarked the performance of ML-ωPBE in µ fl and τ fl , which are key quantities to determine difficult-to-evaluate composite photodynamic properties like the fluorescence quantum yield 18,19 and the luminescence dissymmetry factor. 154,155 We selected only five RSH functionals in our comparison due to their successful descriptions of electronic density distributions (Fig. S4( functionals.…”

Stacked Ensemble Machine Learning for Range-Separation Parameters

“…Finally, we benchmarked the performance of ML-ωPBE in µ fl and τ fl , which are key quantities to determine difficult-to-evaluate composite photodynamic properties like the fluorescence quantum yield 18,19 and the luminescence dissymmetry factor. 153,154 We selected only five RSH functionals in our comparison due to their successful descriptions of electronic density distributions (Fig. S4 functionals.…”