Two-Factor Authentication of Dynamic Disorder for Computational Screening of High-Mobility Organic Semiconductors

Area of Science:

• Materials Science
• Organic Electronics
• Computational Chemistry

Background:

• Efficient charge transport in organic semiconductors (OSCs) relies on suppressing dynamic disorder, specifically thermal fluctuations of intermolecular transfer integrals (J).
• Disorder amplitude (σJ) is determined by molecular coordinate fluctuations and the transfer integral gradient (∇J).

Purpose of the Study:

• To introduce a new family of disorder descriptors, TIGER, based on a physics-inspired two-factor model.
• To develop and validate a computational screening protocol using these descriptors for identifying high-mobility OSCs.

Main Methods:

• Developed the TIGER (Two-factor Insightful Gradient-based Engineering) descriptors.
• Implemented a computational screening protocol leveraging these descriptors.
• Calculated intrinsic mobilities for identified OSC structures.

Main Results:

• Demonstrated the transferability and effectiveness of the TIGER descriptors.
• Identified novel OSC structures with calculated intrinsic mobilities up to 60 cm² V⁻¹ s⁻¹.
• Successfully identified previously known high-mobility OSCs.

Conclusions:

• The TIGER descriptors and screening protocol offer a physics-based approach to materials discovery.
• This methodology provides efficient tools for identifying promising OSCs for advanced electronic applications.
• Accelerates the digital discovery of organic semiconductors with superior charge transport properties.