Helical and Nonhelical Structures of Vinylene- and Azomethine-Linked Heterocyclic Oligomers: A Computational Study of Conformation-Dependent Optoelectronic Properties

A systematic computational investigation has been carried out at the density functional level of theory to characterize various conformational isomers of furan, pyrrole, and thiophene based oligomers and consequently study their stabilities and electronic properties, especially in the cases of long oligomers. In these oligomers, adjacent heterocyclic rings are connected by either vinylene or azomethine linkages. B3LYP and B3LYP-D3 functionals are used to observe the effect of dispersion energy. Our results show that a combination of the B3LYP-D3 functional and the 6-31G­(d,p) basis set is suitable for ground-state studies of these systems. For long vinylene-linked oligomers, folding isomers are comparatively more stable than their respective linearly conjugated isomers, due to intramolecular noncovalent interactions. In the case of azomethine-linked oligomers, geometries and stabilities of conformers depend on the type of heterocyclic ring in the repeating unit. For vinylene-linked heterocyclic oligomers, first optically allowed electronic transitions of linearly conjugated oligomers have the largest oscillator strengths, and these absorption bands are dominated by HOMO to LUMO transitions. In the case of a few linear azomethine-linked oligomers, two major electronic transitions, S₀ → S₁ and S₀ →S₂, are noticed. However, transitions from S₀ to higher electronic states are the most prominent transitions in cases of foldamers, except azomethine-linked thiophene foldamers. Major absorption bands of these helical oligomers are dominated by transitions from HOMO–<i>N</i> to LUMO+<i>N</i> orbitals. All the helical conformers are found to be circular dichroism active

Informatics-Driven Design of Superhard B–C–O Compounds

Materials containing B, C, and O, due to the advantages of forming strong covalent bonds, may lead to materials that are superhard, i.e., those with a Vicker’s hardness larger than 40 GPa. However, the exploration of this vast chemical, compositional, and configurational space is nontrivial. Here, we leverage a combination of machine learning (ML) and first-principles calculations to enable and accelerate such a targeted search. The ML models first screen for potentially superhard B–C–O compositions from a large hypothetical B–C–O candidate space. Atomic-level structure search using density functional theory (DFT) within those identified compositions, followed by further detailed analyses, unravels on four potentially superhard B–C–O phases exhibiting thermodynamic, mechanical, and dynamic stability