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dc.contributor.authorPaterson, Leanne
dc.contributor.authorMay, Falk
dc.contributor.authorAndrienko, Denis
dc.date.accessioned2021-02-16T12:33:59Z
dc.date.available2021-02-16T12:33:59Z
dc.date.issued2020-10-28
dc.identifier.citationPaterson, L., May, F., & Andrienko, D. (2020). Computer aided design of stable and efficient OLEDs. Journal of Applied Physics, 128(16), 160901. doi:10.1063/5.0022870
dc.identifier.issn0021-8979
dc.identifier.issn1089-7550
dc.identifier.doi10.1063/5.0022870
dc.identifier.urihttp://hdl.handle.net/10754/667460
dc.description.abstractOrganic light emitting diodes (OLEDs) offer a unique alternative to traditional display technologies. Tailored device architecture can offer properties such as flexibility and transparency, presenting unparalleled application possibilities. Commercial advancement of OLEDs is highly anticipated, and continued research is vital for improving device efficiency and lifetime. The performance of an OLED relies on an intricate balance between stability, efficiency, operational driving voltage, and color coordinates, with the aim of optimizing these parameters by employing an appropriate material design. Multiscale simulation techniques can aid with the rational design of these materials, in order to overcome existing shortcomings. For example, extensive research has focused on the emissive layer and the obstacles surrounding blue OLEDs, in particular, the trade-off between stability and efficiency, while preserving blue emission. More generally, due to the vast number of contending organic materials and with experimental pre-screening being notoriously time-consuming, a complementary in silico approach can be considerably beneficial. The ultimate goal of simulations is the prediction of device properties from chemical composition, prior to synthesis. However, various challenges must be overcome to bring this to a realization, some of which are discussed in this Perspective. Computer aided design is becoming an essential component for future OLED developments, and with the field shifting toward machine learning based approaches, in silico pre-screening is the future of material design.
dc.description.sponsorshipD.A. acknowledges the BMBF Grant InterPhase (No. FKZ 13N13661) and the European Union Horizon 2020 Research and Innovation Programme 'Widening Materials Models' under Grant Agreement No. 646259 (MOSTOPHOS). This research has been supported by the King Abdullah University of Science and Technology (KAUST), via the Competitive Research Grants (CRG) Program. D.A. acknowledges KAUST for hosting his sabbatical.
dc.publisherAIP Publishing
dc.relation.urlhttp://aip.scitation.org/doi/10.1063/5.0022870
dc.rightsThis article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. The following article appeared in Journal of Applied Physics and may be found at http://doi.org/10.1063/5.0022870.
dc.titleComputer aided design of stable and efficient OLEDs
dc.typeArticle
dc.identifier.journalJournal of Applied Physics
dc.rights.embargodate2021-10-28
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionMax Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany
dc.contributor.institutionMerck KGaA, 64293 Darmstadt, Germany
dc.identifier.volume128
dc.identifier.issue16
dc.identifier.pages160901
kaust.grant.numberCRG
dc.identifier.eid2-s2.0-85094649340
kaust.acknowledged.supportUnitCompetitive Research


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