Coarse-Graining Organic Semiconductors: The Path to Multiscale Design

Area of Science:

• Physical Chemistry
• Materials Science
• Computational Chemistry

Background:

• Molecular theory has advanced organic semiconductor understanding for decades, focusing on single-molecule or dimer electronic structures.
• Emerging noncrystalline molecular and polymeric semiconductors require mesoscale modeling for morphology and electronic structure prediction.

Purpose of the Study:

• To highlight advances in coarse-grained methodologies for multiscale characterization of noncrystalline organic semiconductors.
• To emphasize modeling approaches that predict both structural and electronic properties at the mesoscale.

Main Methods:

• Developing and applying coarse-grained modeling techniques.
• Integrating methods from soft matter physics, coarse-graining, and machine learning.
• Focusing on multiscale characterization without all-atom representations.

Main Results:

• Recent advances in coarse-grained methodologies for noncrystalline organic semiconductors are presented.
• Demonstrated capability of coarse-grained models for predicting mesoscale morphology and electronic structure.
• Bridging the gap between molecular electronic structure and macroscopic semiconductor performance.

Conclusions:

• Coarse-grained modeling is crucial for understanding noncrystalline organic semiconductors.
• These advanced computational tools enable prediction of structure-property relationships.
• This work facilitates the design and optimization of high-performance organic electronic devices.