25‐3: Machine‐Learning‐Assisted Materials Discovery of Blue Emitter for More Efficient and Durable OLED Device. Issue 1 (28th June 2021)

• Record Type: Journal Article
• Authors: Kim, Sohae; Cho, Dahye; Kim, Seran; Kang, Sunwoo; Koh, Eunkyung; Kang, Iljoon; Kim, Hoilim; Mi Cho, Young; Kim, Yongjo
• Is Part Of: Digest of technical papers. Volume 52:Issue 1(2021)
• Page Start: 314
• Page End: 316
• Publication Date: 2021-06-28
• Subjects: Machine learning -- OLED -- emitting materials -- phosphors -- thermally activated delayed fluorescence -- and TADF; Information display systems -- Congresses; 621.3815422
• DOI: 10.1002/sdtp.14678
• Languages: English
• ISSNs: 0097-966X

Abstract

Abstract : While a more efficient and stable emitter with a deep blue color is essential for a better performance of organic light‐emitting diodes (OLED) devices, obtaining such materials is extremely challenging. In the current work, we have developed a tool to assist the discovery of blue OLED materials by applying a v‐HTS of materials based on the properties predicted using ML and a ML‐predictabiltiy scale. In this study, the materials of interest include both Pt (II) phosphor complexes [1−3] and thermally activated delayed fluorescence materials for blue dopants [4−6] . We have also developed a user‐friendly version that includes most of the algorithms used in this study, which is available on an internal web‐based simulation platform.