RESUMEN
The through-space charge transfer thermally activated delayed fluorescence (TSCT-TADF) properties of a series of molecules were characterized and tested theoretically by density functional theory and time-dependent density functional theory. By analyzing the weak interaction of the molecules at the ground state and calculating the transition contribution ratio of the donor, acceptor, and bridge in the excited state, we verified the through-space charge transfer characteristic of these molecules. We designed new molecules on the basis of the reported molecules (non-TADF molecule 1 and TADF molecule 2) to improve the performance. Smaller singlet-triplet energy gaps and larger spin-orbit coupling were obtained in the designed molecules, which is beneficial to obtain higher intersystem crossing and reverse intersystem crossing rates (kRISC). In addition, we calculated the radiation rate and the singlet-triplet reorganization energy, which is used to characterize the nonradiation rate. The comprehensive evaluation of both radiative and nonradiative processes shows that molecules 4 and 6 have the potential to be highly efficient TSCT-TADF materials.
RESUMEN
Doublet-emission is mainly discovered in stable radicals, lanthanide-metal complexes with an f1 electron configuration and transition-metal complexes with a low-spin d5 electron configuration, and has a distinct radiation mechanism from closed-shell luminescent molecules and thus technology opportunities. There exists an unpaired electron in the frontier molecular orbitals which enables efficient nanosecond-scale luminescence in these materials due to the spin-allowed transitions between doublet-spin states. In this review, we summarize recent advances in these materials and their application in organic light emitting diodes (OLEDs). The photoluminescence and electroluminescence mechanisms of different doublet-emissive molecular systems are discussed, in addition to the photophysical phenomena arising from doublet states. We also outline the current challenges faced by each molecular system, and the potential outlook on the future research trends in this field.
RESUMEN
TV show captioning aims to generate a linguistic sentence based on the video and its associated subtitle. Compared to purely video-based captioning, the subtitle can provide the captioning model with useful semantic clues such as actors' sentiments and intentions. However, the effective use of subtitle is also very challenging, because it is the pieces of scrappy information and has semantic gap with visual modality. To organize the scrappy information together and yield a powerful omni-representation for all the modalities, an efficient captioning model requires understanding video contents, subtitle semantics, and the relations in between. In this paper, we propose an Intra- and Inter-relation Embedding Transformer (I2Transformer), consisting of an Intra-relation Embedding Block (IAE) and an Inter-relation Embedding Block (IEE) under the framework of a Transformer. First, the IAE captures the intra-relation in each modality via constructing the learnable graphs. Then, IEE learns the cross attention gates, and selects useful information from each modality based on their inter-relations, so as to derive the omni-representation as the input to the Transformer. Experimental results on the public dataset show that the I2Transformer achieves the state-of-the-art performance. We also evaluate the effectiveness of the IAE and IEE on two other relevant tasks of video with text inputs, i.e., TV show retrieval and video-guided machine translation. The encouraging performance further validates that the IAE and IEE blocks have a good generalization ability. The code is available at https://github.com/tuyunbin/I2Transformer.
