Optimization of organic light emitting diode structures

Abstract

In this work we present detailed analysis of the emitted radiation spectrum from tris(8-hydroxyquinoline) aluminum (Alq 3 ) based OLEDs as a function of: the choice of cathode, the thickness of organic layers, and the position of the hole transport layer/Alq 3 interface. The calculations fully take into account dispersion in glass substrate, indium tin oxide anode, and in the organic layers, as well as the dispersion in the metal cathode. Influence of the incoherent transparent substrate (1 mm glass substrate) is also fully accounted for. Four cathode structures have been considered: Mg/Ag, Ca/Ag, LiF/Al, and Ag. For the hole transport layer, N,N'-diphenyl-N,N'-(3-methylphenyl)-1,1'-biphenyl-4,4'-diamine (TPD) was considered. As expected, emitted radiation is strongly dependent on the position of the emissive layer inside the cavity and its distance from the metal cathode. Although our optical model for an OLED does not explicitly include exciton quenching in vicinity of the metal cathode, designs placing emissive layer near the cathode are excluded to avoid unrealistic results. Guidelines for designing devices with optimum emission efficiency are presented. Finally, the optimized devices were fabricated and characterized and experimental and calculated emission spectra were compared.

P‐252: Late‐News Poster: Deep Learning based Inverse Design Technology for White Organic Light‐emitting Diode Thin‐film Structure

“…We anticipate that the inverse design neural network can be further improved by training with bigger database and well-tuned training algorithm. Furthermore, it should be possible to achieve accurate prediction performance beyond the limitation of the inverse design artificial neural network by applying an optimization algorithms to neural networks [14][15][16][17]. By using our deep learning based inverse designing neural network, it is easily achieved to instantly predict WOLED thin-film structures that correspond to desired characteristics.…”

Electrical and Optical Simulation of Tris (8-hydroxyquinoline) Aluminium-Based Microcavity Organic Light Emitting Diode (MOLED)

“…In order to further improve and optimise this device for use in practical applications, device modeling of OLED characteristics is required to better understand the physical processes affecting the device performance. Continuing from our previous work, where detailed analysis of the optical radiation spectrum from microcavity-based OLED have been presented, the carrier transport analysis is included in this work to provide further insight into both optical and electrical behaviors of double layer OLED device [3].…”