Lifetime assessment of organic light emitting diodes by compact model incorporated with deep learning technique
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Il-Hoo | - |
dc.contributor.author | Lee, Song Eun | - |
dc.contributor.author | Kim, Yunjeong | - |
dc.contributor.author | You, Seung Yeol | - |
dc.contributor.author | Kim, Young Kwan | - |
dc.contributor.author | Kim, Gyu-Tae | - |
dc.date.accessioned | 2022-02-10T18:40:24Z | - |
dc.date.available | 2022-02-10T18:40:24Z | - |
dc.date.created | 2022-01-20 | - |
dc.date.issued | 2022-02 | - |
dc.identifier.issn | 1566-1199 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/135245 | - |
dc.description.abstract | Simple and efficient lifetime modeling of organic light emitting diodes (OLED) are suggested by in-situ successive AC/DC measurements with reinforcement assessments of machine learning. AC/DC device parameters of phosphorescent OLED devices with multiple transport layers are monitored and analyzed by third-order parallel R//C circuit model with deep learning algorithm. The prediction efficiency of the lifetime assessment is enhanced by combining in-situ AC/DC device parameters, reducing the assessment time compared to conventional constant-stress test methods. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER | - |
dc.subject | DEGRADATION MECHANISM | - |
dc.subject | PHOSPHORESCENT | - |
dc.subject | HOLE | - |
dc.title | Lifetime assessment of organic light emitting diodes by compact model incorporated with deep learning technique | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Gyu-Tae | - |
dc.identifier.doi | 10.1016/j.orgel.2021.106404 | - |
dc.identifier.scopusid | 2-s2.0-85120621668 | - |
dc.identifier.wosid | 000729283400004 | - |
dc.identifier.bibliographicCitation | ORGANIC ELECTRONICS, v.101 | - |
dc.relation.isPartOf | ORGANIC ELECTRONICS | - |
dc.citation.title | ORGANIC ELECTRONICS | - |
dc.citation.volume | 101 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Materials Science | - |
dc.relation.journalResearchArea | Physics | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
dc.subject.keywordPlus | DEGRADATION MECHANISM | - |
dc.subject.keywordPlus | PHOSPHORESCENT | - |
dc.subject.keywordPlus | HOLE | - |
dc.subject.keywordAuthor | OLEDs | - |
dc.subject.keywordAuthor | Compact modeling | - |
dc.subject.keywordAuthor | Deep learning | - |
dc.subject.keywordAuthor | Lifetime assessment | - |
dc.subject.keywordAuthor | Automatic successive measurements | - |
dc.subject.keywordAuthor | 4,4 &apos | - |
dc.subject.keywordAuthor | -N,N &apos | - |
dc.subject.keywordAuthor | -dicarbazole-biphenyl (CBP) | - |
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