Inverse design workflow discovers hole-transport materials tailored for perovskite solar cells

Area of Science:

• Materials Science
• Organic Electronics
• Renewable Energy

Background:

• Designing organic molecules for optoelectronic devices is complex and often requires large datasets not readily available for specialized fields.
• Existing models for molecular design struggle with data scarcity in niche research areas.

Purpose of the Study:

• To demonstrate a closed-loop workflow for the inverse design of tailored organic semiconductors.
• To discover novel hole-transporting materials with optimized properties for solar cell applications.

Main Methods:

• Implemented a workflow combining high-throughput synthesis of organic semiconductors to generate large datasets.
• Utilized Bayesian optimization to efficiently search for materials with desired characteristics.
• Employed molecular descriptors to establish structure-property relationships for predictive modeling.

Main Results:

• Successfully created large datasets of organic semiconductors through high-throughput synthesis.
• Identified high-performance hole-transporting molecules using Bayesian optimization with minimal initial suggestions.
• Achieved power conversion efficiencies up to 26.2% (certified 25.9%) in perovskite solar cells using the discovered materials.

Conclusions:

• The developed closed-loop workflow enables efficient inverse design of organic semiconductors.
• This approach overcomes data limitations in specialized research fields.
• The discovered materials significantly advance the performance of perovskite solar cells.