A complete model for the quantitative simulation of electrical and optical characteristics for organic light-emitting devices with fluorescent dopant in the host is presented. This simulation model consists of three parts: charged carrier transport model, exciton model, and emission and optical model. In the first part, we include not only charge carrier trapping but also direct carrier recombination phenomena on the fluorescent dopant. In the second part, Förster [Discuss. Faraday Soc. 27, 7 (1959)] energy transfer from the host molecule to the dopant molecule is included in exciton model. In addition, the quenching phenomena related to dopant concentration and electrode are also considered in this study. In the optical model, the thin-film optics is applied to calculate the interference effect of the device. Results for several multilayer devices with different fluorescent dopant concentrations are presented. On the basis of the experimental data of a typical doped device, we have found good agreement between the simulation results and the experimental data.

Simultaneous sensing of multiple gases by a single fluorescent-based gas sensor is of utmost importance for practical applications. Such sensing is strongly hindered by cross-sensitivity effects. In this study, we propose a novel analysis method to ameliorate such hindrance. The trial sensor used here was fabricated by coating platinum(II) meso-tetrakis(pentafluorophenyl)porphyrin (PtTFPP) and eosin-Y dye molecules on both sides of a filter paper for sensing O₂ and NH₃ gases simultaneously. The fluorescent peak intensities of the dyes can be quenched by the analytes and this phenomenon is used to identify the gas concentrations. Ideally, each dye is only sensitive to one gas species. However, the fluorescent peak related to O₂ sensing is also quenched by NH₃ and vice versa. Such cross-sensitivity strongly hinders gas concentration detection. Therefore, we have studied this cross-sensitivity effect systematically and thus proposed a new analysis method for accurate estimation of gas concentration. Comparing with a traditional method (neglecting cross-sensitivity), this analysis improves O₂-detection error from −11.4% ± 34.3% to 2.0% ± 10.2% in a mixed background of NH₃ and N₂.