Inverting Singlet and Triplet Excited States using Strong Light-Matter Coupling

In organic microcavities, hybrid light-matter states can form with energies that differ from the bare molecular excitation energies by nearly 1 eV. A timely question, given recent advances in the development of thermally activated delayed fluorescence materials, is whether strong light-matter coupling can be used to invert the ordering of singlet and triplet states and, in addition, enhance reverse intersystem crossing (RISC) rates. Here, we demonstrate a complete inversion of the singlet lower polariton and triplet excited states. We also unambiguously measure the RISC rate in strongly-coupled organic microcavities and find that, regardless of the large energy level shifts, it is unchanged compared to films of the bare molecules. This observation is a consequence of slow RISC to the lower polariton due to the delocalized nature of the state across many molecules and an inability to compete with RISC to the dark exciton reservoir, which occurs at a rate comparable to that in bare molecules

Triplet harvesting in the polaritonic regime: a variational polaron approach

We explore the electroluminescence efficiency for a quantum mechanical model of a large number of molecular emitters embedded in an optical microcavity. We characterize the circumstances under which a microcavity enhances harvesting of triplet excitons via reverse intersystem-crossing (R-ISC) into singlet populations that can emit light. For that end, we develop a time-local master equation in a variationally optimized frame which allows for the exploration of the population dynamics of chemically relevant species in different regimes of emitter coupling to the condensed phase vibrational bath and to the microcavity photonic mode. For a vibrational bath that equilibrates faster than R-ISC (in emitters with weak singlet-triplet mixing), our results reveal that significant improvements in efficiencies with respect to the cavity-free counterpart can be obtained for strong coupling of the singlet exciton to a photonic mode, as long as the singlet to triplet exciton transition is within the inverted Marcus regime; under these circumstances, we show the possibility to overcome the detrimental delocalization of the polariton states across a macroscopic number of molecules. On the other hand, for a vibrational bath that equilibrates slower than R-ISC (i.e., emitters with strong singlet-triplet mixing), we find that while enhancemnents in photoluminiscence can be obtained via vibrational relaxation into polaritons, this only occurs for small number of emitters coupled to the photon mode, with delocalization of the polaritons across many emitters eventually being detrimental to electroluminescence efficiency. These findings provide insight on the tunability of optoelectronic processes in molecular materials due to weak and strong light-matter coupling

A CONSTRAINED MATCHING PURSUIT APPROACH TO AUDIO DECLIPPING

© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Audio Inpainting

(c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Published version: IEEE Transactions on Audio, Speech and Language Processing 20(3): 922-932, Mar 2012. DOI: 10.1090/TASL.2011.2168211

Summarizing First-Person Videos from Third Persons' Points of Views

Video highlight or summarization is among interesting topics in computer vision, which benefits a variety of applications like viewing, searching, or storage. However, most existing studies rely on training data of third-person videos, which cannot easily generalize to highlight the first-person ones. With the goal of deriving an effective model to summarize first-person videos, we propose a novel deep neural network architecture for describing and discriminating vital spatiotemporal information across videos with different points of view. Our proposed model is realized in a semi-supervised setting, in which fully annotated third-person videos, unlabeled first-person videos, and a small number of annotated first-person ones are presented during training. In our experiments, qualitative and quantitative evaluations on both benchmarks and our collected first-person video datasets are presented.Comment: 16+10 pages, ECCV 201