Evolutionary chemical space exploration for functional materials: computational organic semiconductor discovery.

Area of Science:

• Materials Science
• Computational Chemistry
• Organic Electronics

Background:

• Accelerating materials discovery through computational methods like crystal structure and property prediction is crucial.
• Identifying promising molecules from vast chemical spaces remains a bottleneck in discovering new functional molecular materials.

Purpose of the Study:

• To develop and demonstrate an evolutionary computational method for exploring chemical space and identifying novel organic semiconductors.
• To find small molecule organic semiconductors with high charge carrier mobilities, specifically exploring aza-substituted pentacenes.

Main Methods:

• An evolutionary method was employed to explore a user-defined chemical space for promising molecules.
• Promising molecules were subsequently evaluated using crystal structure prediction.
• The method was applied to the exploration of aza-substituted pentacenes.

Main Results:

• The evolutionary method efficiently explored large chemical spaces, requiring calculations on only ~1% of molecules.
• Two promising structural motifs were identified: aza-substituted naphtho[1,2-a]anthracenes and pyridazine-based molecules.
• These motifs exhibited low reorganisation energies comparable to pentacene and high electron affinities.

Conclusions:

• The developed evolutionary method significantly accelerates the discovery of functional molecular materials by efficiently navigating vast chemical spaces.
• The identified aza-substituted naphthoanthracenes and pyridazine-based molecules show potential for high-performance organic semiconductor applications.