Opportunities for Next-Generation Luminescent Materials through Artificial Intelligence

Luminescent materials are continually sought for application in solid-state LED-based lighting and display applications. This has traditionally required extensive experimental effort. More recently, the employment of data-driven approaches in materials science has provided an alternative avenue to accelerate the discovery and development of luminescent materials. In this Perspective, we give an overview of luminescent materials used for lighting and display applications with a specific focus on inorganic phosphors, quantum dots, and organic light-emitting diodes. We discuss recent progress using data-driven approaches to discover new compounds, predict optical properties, and optimize synthesis, among other topics for each type of material. We then highlight future research directions focusing on using artificial intelligence (AI) to advance these fields and address some crosscutting challenges limiting the current application of AI techniques in luminescence-related research.

Automated summary

The search for luminescent materials for LED lighting and display applications has traditionally involved extensive experimental effort, but data-driven approaches in materials science are now providing an alternative pathway for discovery and development. This Perspective provides an overview of luminescent materials such as inorganic phosphors, quantum dots, and organic LEDs, with a focus on recent progress in using data-driven approaches to discover new compounds and optimize synthesis. Future research directions include utilizing artificial intelligence to further advance these fields and address challenges limiting the current application of AI techniques in luminescence-related research.