High-throughput virtual screening for organic electronics: a comparative study of alternative strategies

Area of Science:

• Materials Science
• Computational Chemistry
• Organic Electronics

Background:

• High-throughput virtual screening (HTVS) is crucial for accelerating the discovery of novel organic electronics materials.
• The effectiveness of HTVS protocols depends heavily on a series of methodological choices.
• Optimizing these choices is essential for improving the efficiency and applicability of virtual screening in materials science.

Purpose of the Study:

• To review the field of HTVS for organic electronics materials.
• To systematically analyze the methodological choices influencing HTVS protocols.
• To discuss strategies for optimizing HTVS workflows and enhancing their predictive power.

Main Methods:

• Comprehensive review of existing literature on HTVS methodologies for organic electronics.
• Analysis of property computation methods and their accuracy validation against experimental data.
• Evaluation of diverse candidate generation approaches and their respective advantages and limitations.

Main Results:

• Identified key decision points in designing HTVS protocols, from property prediction to candidate selection.
• Demonstrated the impact of dataset quality and size on the accuracy of computed material properties.
• Highlighted the importance of analyzing screening results beyond top candidate identification, focusing on emergent patterns and structure-property relationships.

Conclusions:

• Systematic optimization of methodological choices in HTVS leads to more robust and applicable workflows for organic electronics materials discovery.
• The field of HTVS is rapidly evolving, driven by new applications, methodologies, and data availability.
• Understanding structure-property relationships derived from HTVS is a significant outcome, guiding future materials design.