Hetero-polycyclic aromatic systems: A data-driven investigation of structure-property relationships

Area of Science:

• Chemistry
• Materials Science
• Computational Chemistry

Background:

• Polycyclic aromatic systems (PASs) are crucial in chemistry and materials science.
• Understanding PASs structure-property relationships is key for designing new functional molecules.
• Current understanding of these relationships is limited.

Purpose of the Study:

• To elucidate the structure-property relationships in polycyclic aromatic systems (PASs).
• To analyze the impact of molecular descriptors on electronic properties of PASs.
• To leverage a large dataset for data-driven insights into PASs.

Main Methods:

• Utilized the COMPAS-2 dataset (~500k molecules).
• Included 11 types of aromatic and antiaromatic rings, with sizes from one to ten rings.
• Performed a data-driven investigation of electronic molecular properties.

Main Results:

• Explored effects of electron count, geometry, atomic composition, and heterocyclic composition.
• Analyzed a wide range of electronic molecular properties.
• Identified key factors influencing PASs properties.

Conclusions:

• The study provides a detailed understanding of structure-property relationships in PASs.
• Findings can guide the rational design of novel functional materials.
• Data-driven approaches are effective for exploring complex chemical systems.