Existence of an upper limit on the density of excitons in carbon nanotubes by diffusion-limited exciton-exciton annihilation: Experiment and theory

Through an investigation of photoemission properties of highly-photoexcited single-walled carbon nanotubes, we demonstrate that there is an upper limit on the achievable excitonic density. As the intensity of optical excitation increases, all photoluminescence emission peaks arising from different chirality single-walled carbon nanotubes showed clear saturation in intensity. Each peak exhibited a saturation value that was independent of the excitation wavelength, indicating that there is an upper limit on the excitonic density for each nanotube species. We propose that this saturation behavior is a result of efficient exciton-exciton annihilation through which excitons decay non-radiatively. In order to explain the experimental results and obtain excitonic densities in the saturation regime, we have developed a model, taking into account the generation, diffusion-limited exciton-exciton annihilation, and spontaneous decays of one-dimensional excitons. Using the model, we were able to reproduce the experimentally obtained saturation curves under certain approximations, from which the excitonic densities were estimated. The validity of the model was confirmed through comparison with Monte Carlo simulations. Finally, we show that the conventional rate equation for exciton-exciton annihilation without taking into account exciton diffusion fails to fit the experimentally observed saturation behavior, especially at high excitonic densities.Comment: 5 figures, 1 tabl

Homology-based prediction of interactions between proteins using Averaged One-Dependence Estimators

BACKGROUND: Identification of protein-protein interactions (PPIs) is essential for a better understanding of biological processes, pathways and functions. However, experimental identification of the complete set of PPIs in a cell/organism (“an interactome”) is still a difficult task. To circumvent limitations of current high-throughput experimental techniques, it is necessary to develop high-performance computational methods for predicting PPIs. RESULTS: In this article, we propose a new computational method to predict interaction between a given pair of protein sequences using features derived from known homologous PPIs. The proposed method is capable of predicting interaction between two proteins (of unknown structure) using Averaged One-Dependence Estimators (AODE) and three features calculated for the protein pair: (a) sequence similarities to a known interacting protein pair (F(Seq)), (b) statistical propensities of domain pairs observed in interacting proteins (F(Dom)) and (c) a sum of edge weights along the shortest path between homologous proteins in a PPI network (F(Net)). Feature vectors were defined to lie in a half-space of the symmetrical high-dimensional feature space to make them independent of the protein order. The predictability of the method was assessed by a 10-fold cross validation on a recently created human PPI dataset with randomly sampled negative data, and the best model achieved an Area Under the Curve of 0.79 (pAUC(0.5%) = 0.16). In addition, the AODE trained on all three features (named PSOPIA) showed better prediction performance on a separate independent data set than a recently reported homology-based method. CONCLUSIONS: Our results suggest that F(Net), a feature representing proximity in a known PPI network between two proteins that are homologous to a target protein pair, contributes to the prediction of whether the target proteins interact or not. PSOPIA will help identify novel PPIs and estimate complete PPI networks. The method proposed in this article is freely available on the web at http://mizuguchilab.org/PSOPIA

Aharonov-Bohm Exciton Absorption Splitting in Chiral Specific Single-Walled Carbon Nanotubes in Magnetic Fields of up to 78 T

The Ajiki-Ando (A-A) splitting of single-walled carbon nanotubes(SWNT) originating from the Aharanov-Bohm effect was observed in chiral specific SWNTs by the magneto-absorption measurements conducted at magnetic fields of up to 78 T. The absorption spectra from each chirality showed clear A-A splitting of the $E_{11}$ optical excitonic transitions. The parameters of both the dark-bright exciton energy splitting and the rate of A-A splitting in a magnetic field were determined for the first time from the well-resolved absorption spectra.Comment: 5 pages, 3 figure

eF-seek: prediction of the functional sites of proteins by searching for similar electrostatic potential and molecular surface shape

We have developed a method to predict ligand-binding sites in a new protein structure by searching for similar binding sites in the Protein Data Bank (PDB). The similarities are measured according to the shapes of the molecular surfaces and their electrostatic potentials. A new web server, eF-seek, provides an interface to our search method. It simply requires a coordinate file in the PDB format, and generates a prediction result as a virtual complex structure, with the putative ligands in a PDB format file as the output. In addition, the predicted interacting interface is displayed to facilitate the examination of the virtual complex structure on our own applet viewer with the web browser (URL: http://eF-site.hgc.jp/eF-seek)