Optimal high-throughput virtual screening pipeline for efficient selection of redox-active organic materials

Area of Science:

• Materials Science
• Computational Chemistry
• Renewable Energy Storage

Background:

• Growing demand for renewable energy necessitates advanced energy storage solutions beyond current lithium-ion batteries.
• Organic electrode materials offer a promising alternative but require precise control over their redox potential (RP) for optimal performance.
• Identifying suitable organic materials with targeted RPs is a significant bottleneck in developing next-generation batteries.

Purpose of the Study:

• To propose and validate a computational framework for designing and operating a high-throughput virtual screening (HTVS) pipeline.
• To enable rapid identification of organic materials with specific redox potentials for energy storage applications.
• To enhance the efficiency and throughput of screening potential organic electrode materials.

Main Methods:

• Development of a high-fidelity model for accurate redox potential estimation.
• Design of a set of surrogate models with varying accuracy and complexity.
• Integration of these models into a high-throughput virtual screening (HTVS) pipeline for efficient material evaluation.

Main Results:

• Successful construction of a highly accurate and efficient HTVS pipeline.
• Demonstration that the proposed pipeline construction and operation strategies significantly increase screening throughput.
• Validation of the computational framework for accelerating the discovery of organic energy storage materials.

Conclusions:

• The developed computational framework and HTVS pipeline effectively address the challenge of finding organic materials with targeted redox potentials.
• This approach substantially enhances the speed and efficiency of discovering novel organic electrode materials for advanced energy storage.
• The study provides a scalable strategy for accelerating research and development in organic-based renewable energy storage.