Theory of interfacial charge-transfer complex photophysics in π\pi-conjugated polymer-fullerene blends

We present a theory of the electronic structure and photophysics of 1:1 blends of derivatives of polyparaphenylenevinylene and fullerenes. Within the same Coulomb-correlated Hamiltonian applied previously to interacting chains of single-component $\pi$-conjugated polymers, we find an exciplex state that occurs below the polymer's optical exciton. Weak absorption from the ground state occurs to the exciplex. We explain transient photoinduced absorptions in the blend, observed for both above-gap and below-gap photoexcitations, within our theory. Photoinduced absorptions for above-gap photoexcitation are from the optical exciton as well as the exciplex, while for below-gap photoexcitation induced absorptions are from the exciplex alone. In neither case are free polarons generated in the time scale of the experiment. Importantly, the photophysics of films of single-component $\pi$-conjugated polymers and blends can both be understood by extending Mulliken's theory of ground-state charge transfer to the case of excited-state charge transfer.Comment: 9 pages, 8 figure

Controlling quantum transport through a single molecule

We investigate multi-terminal quantum transport through single monocyclic aromatic annulene molecules, and their derivatives, using the nonequilibrium Green function approach in the self-consistent Hartree-Fock approximation. A new device concept, the Quantum Interference Effect Transistor (QuIET) is proposed, exploiting perfect destructive interference stemming from molecular symmetry, and controlling current flow by introducing decoherence and/or elastic scattering that break the symmetry. This approach overcomes the fundamental problems of power dissipation and environmental sensitivity that beset many nanoscale device proposals.Comment: 4 pages, 5 figure

The ubiquitous 1100 charge ordering in organic charge-transfer solids

Charge and spin-orderings in the 1/4-filled organic CT solids are of strong interest, especially in view of their possible relations to organic superconductivity. We show that the charge order (CO) in both 1D and 2D CT solids is of the ...1100... type, in contradiction to mean field prediction of >...1010... CO. We present detailed computations for metal-insulator and magnetic insulator-insulator transitions in the theta-ET materials. Complete agreement with experiments in several theta systems is found. Similar comparisons between theory and experiments in TCNQ, TMTTF, TMTSF, and ET materials prove the ubiquity of this phenomenon.Comment: 3 pages, 4 eps figures; ICSM 200

Correlated-electron description of the photophysics of thin films of π\pi-conjugated polymers

We extend Mulliken's theory of ground state charge transfer in a donor-acceptor complex to excited state charge transfer between pairs of identical $\pi$-conjugated oligomers, one of which is in the optically excited state and the other in the ground state, leading to the formation of a charge-transfer exciton. Within our theory, optical absorptions from the charge-transfer exciton should include a low energy intermolecular charge-transfer excitation, as well as distinct intramolecular excitations from both the neutral delocalized exciton component and the Coulombically bound polaron-pair component of the charge-transfer exciton. We report high order configuration-interaction calculations for pairs of oligomers of poly-paraphenylenevinylene (PPV) that go beyond our previous single configuration-interaction calculation and find all five excited state absorptions predicted using heuristic arguments based on the Mulliken concept. Our calculated excited state absorption spectrum exhibits strong qualitative agreement with the complete wavelength-dependent ultrafast photoinduced absorption in films of PPV derivatives, suggesting that a significant fraction of the photoinduced absorption here is from the charge-transfer exciton. We make detailed comparisons to experiments, and a testable experimental prediction

Density matrix renormalization group study of conjugated polymers with transverse pi-conjugation

We report accurate numerical studies of excited state orderings in long hypothetical pi-conjugated oligomers in which the hydrogen atoms of trans-polyacetylene are replaced with conjugated sidegroups, within modified Hubbard models. There exists a range of the bare Coulomb repulsion for which the excited state ordering is conducive to photoluminescence in the substituted systems, even as this ordering is opposite in the unsubstituted polyenes of the same lengths. Our work provides motivation to study real pi-conjugated polymers with transverse conjugation and small optical gaps.Comment: 5 pages, 4 fig

Towards Scalable Visual Exploration of Very Large RDF Graphs

In this paper, we outline our work on developing a disk-based infrastructure for efficient visualization and graph exploration operations over very large graphs. The proposed platform, called graphVizdb, is based on a novel technique for indexing and storing the graph. Particularly, the graph layout is indexed with a spatial data structure, i.e., an R-tree, and stored in a database. In runtime, user operations are translated into efficient spatial operations (i.e., window queries) in the backend.Comment: 12th Extended Semantic Web Conference (ESWC 2015

A novel application of deep learning with image cropping: a smart city use case for flood monitoring

© 2020, The Author(s). Event monitoring is an essential application of Smart City platforms. Real-time monitoring of gully and drainage blockage is an important part of flood monitoring applications. Building viable IoT sensors for detecting blockage is a complex task due to the limitations of deploying such sensors in situ. Image classification with deep learning is a potential alternative solution. However, there are no image datasets of gullies and drainages. We were faced with such challenges as part of developing a flood monitoring application in a European Union-funded project. To address these issues, we propose a novel image classification approach based on deep learning with an IoT-enabled camera to monitor gullies and drainages. This approach utilises deep learning to develop an effective image classification model to classify blockage images into different class labels based on the severity. In order to handle the complexity of video-based images, and subsequent poor classification accuracy of the model, we have carried out experiments with the removal of image edges by applying image cropping. The process of cropping in our proposed experimentation is aimed to concentrate only on the regions of interest within images, hence leaving out some proportion of image edges. An image dataset from crowd-sourced publicly accessible images has been curated to train and test the proposed model. For validation, model accuracies were compared considering model with and without image cropping. The cropping-based image classification showed improvement in the classification accuracy. This paper outlines the lessons from our experimentation that have a wider impact on many similar use cases involving IoT-based cameras as part of smart city event monitoring platforms