Accelerated diradical character assessment in large datasets of polybenzenoid hydrocarbons using xTB fractional occupation.

Polybenzenoid hydrocarbons (PBHs) have garnered significant attention in the field of organic electronics due to their unique electronic properties. To facilitate the design and discovery of new functional organic materials based on these compounds, it is necessary to assess their diradical character. However, this usually requires expensive multireference calculations.

COMPAS-3: a dataset of -condensed polybenzenoid hydrocarbons.

We introduce the third installment of the COMPAS Project - a COMputational database of Polycyclic Aromatic Systems, focused on -condensed polybenzenoid hydrocarbons. In this installment, we develop two datasets containing the optimized ground-state structures and a selection of molecular properties of ∼39k and ∼9k -condensed polybenzenoid hydrocarbons (at the GFN2-xTB and CAM-B3LYP-D3BJ/cc-pvdz//CAM-B3LYP-D3BJ/def2-SVP levels, respectively). The manuscript details the enumeration and data generation processes and describes the information available within the datasets.

Interpretable Deep-Learning Unveils Structure-Property Relationships in Polybenzenoid Hydrocarbons.

In this work, interpretable deep learning was used to identify structure-property relationships governing the HOMO-LUMO gap and the relative stability of polybenzenoid hydrocarbons (PBHs) using a ring-based graph representation. This representation was combined with a subunit-based perception of PBHs, allowing chemical insights to be presented in terms of intuitive and simple structural motifs. The resulting insights agree with conventional organic chemistry knowledge and electronic structure-based analyses and also reveal new behaviors and identify influential structural motifs.

The COMPAS Project: A Computational Database of Polycyclic Aromatic Systems. Phase 1: -Condensed Polybenzenoid Hydrocarbons.

Chemical databases are an essential tool for data-driven investigation of structure-property relationships and for the design of novel functional compounds. We introduce the first phase of the COMPAS Project─a COMputational database of Polycyclic Aromatic Systems. In this phase, we developed two data sets containing the optimized ground-state structures and a selection of molecular properties of ∼34k and ∼9k -condensed polybenzenoid hydrocarbons (at the GFN2-xTB and B3LYP-D3BJ/def2-SVP levels, respectively) and placed them in the public domain.