Abstract

This work demonstrates an active learning (AL) workflow for identifying promising material candidates for organic lightemitting diodes (OLEDs) based on multiple optoelectronic parameters while minimizing the number of physics‐based computations to explore an extensive library. This work paves the way for efficient computational materials screening before laborious synthesis, and device fabrication.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.