Organic 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.
|Original language||English (US)|
|Journal||Journal of Applied Physics|
|State||Published - Oct 28 2020|
Bibliographical noteKAUST Repository Item: Exported on 2021-02-17
Acknowledged KAUST grant number(s): CRG
Acknowledgements: D.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.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.