Dirac Fermion in Strongly-Bound Graphene Systems

It is highly desirable to integrate graphene into existing semiconductor technology, where the combined system is thermodynamically stable yet maintain a Dirac cone at the Fermi level. Firstprinciples calculations reveal that a certain transition metal (TM) intercalated graphene/SiC(0001), such as the strongly-bound graphene/intercalated-Mn/SiC, could be such a system. Different from free-standing graphene, the hybridization between graphene and Mn/SiC leads to the formation of a dispersive Dirac cone of primarily TM d characters. The corresponding Dirac spectrum is still isotropic, and the transport behavior is nearly identical to that of free-standing graphene for a bias as large as 0.6 V, except that the Fermi velocity is half that of graphene. A simple model Hamiltonian is developed to qualitatively account for the physics of the transfer of the Dirac cone from a dispersive system (e.g., graphene) to an originally non-dispersive system (e.g., TM).Comment: Apr 25th, 2012 submitte

PRIN: a predicted rice interactome network

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yeast two-hybrid system and affinity purification followed by mass spectrometry are widely used in model organisms, the progress of protein-protein interactions detection in plants is rather slow. With this motivation, our work presents a computational approach to predict protein-protein interactions in <it>Oryza sativa</it>.</p> <p>Results</p> <p>To better understand the interactions of proteins in <it>Oryza sativa</it>, we have developed PRIN, a Predicted Rice Interactome Network. Protein-protein interaction data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast (<it>Saccharomyces cerevisiae</it>), worm (<it>Caenorhabditis elegans</it>), fruit fly (<it>Drosophila melanogaster</it>), human (<it>Homo sapiens</it>), <it>Escherichia coli </it>K12 and <it>Arabidopsis thaliana</it>. With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. Further analysis showed that the topology properties of predicted rice protein interaction network are more similar to yeast than to the other 5 organisms. This may not be surprising as the interologs based on yeast contribute nearly 74% of total interactions. In addition, GO annotation, subcellular localization information and gene expression data are also mapped to our network for validation. Finally, a user-friendly web interface was developed to offer convenient database search and network visualization.</p> <p>Conclusions</p> <p>PRIN is the first well annotated protein interaction database for the important model plant <it>Oryza sativa</it>. It has greatly extended the current available protein-protein interaction data of rice with a computational approach, which will certainly provide further insights into rice functional genomics and systems biology.</p> <p>PRIN is available online at <url>http://bis.zju.edu.cn/prin/</url>.</p

Universal quasiparticle decoherence in hole- and electron-doped high-Tc cuprates

We use angle-resolved photoemission to unravel the quasiparticle decoherence process in the high-$T_c$ cuprates. The coherent band is highly renormalized, and the incoherent part manifests itself as a nearly vertical ``dive'' in the $E$-$k$ intensity plot that approaches the bare band bottom. We find that the coherence-incoherence crossover energies in the hole- and electron-doped cuprates are quite different, but scale to their corresponding bare bandwidth. This rules out antiferromagnetic fluctuations as the main source for decoherence. We also observe the coherent band bottom at the zone center, whose intensity is strongly suppressed by the decoherence process. Consequently, the coherent band dispersion for both hole- and electron-doped cuprates is obtained, and is qualitatively consistent with the framework of Gutzwiller projection.Comment: 4 pages, 4 figure

On-chip light-scattering enhancement enables high performance single-particle tracking under conventional bright-field microscope

Scattering-based single-particle tracking (S-SPT) has opened new avenues for highly sensitive label-free detection and characterization of nanoscopic objects, making it particularly attractive for various analytical applications. However, a long-standing issue hindering its widespread applicability is its high technical demands on optical systems. The most promising solution entails implementing on-chip light-scattering enhancement, but the existing field-enhancement technology fails as their highly localized field is insufficient to cover the three-dimensional trajectory of particles within the interrogation time. Here, we present a straightforward and robust on-chip microlens-based strategy for light-scattering enhancement, providing an enhancement range ten times greater than that of near-field optical techniques. These properties are attributed to the increased long-range optical fields and complex composite interactions between two closely spaced structures. Thanks to this strategy, we demonstrate that high-performance S-SPT can be achieved, for the first time, under a conventional bright-field microscope with illumination powers over 1,000 times lower than typically required. This significantly reduces the technical demands of S-SPT, representing a significant step forward in facilitating its practical application in biophotonics, biosensors, diagnostics, and other fields.Comment: 29 pages,4 figure

Localized photonic nanojet based sensing platform for highly efficient signal amplification and quantitative biosensing

Light-analyte interaction systems are key elements of novel near-field optics based sensing techniques used for highly-sensitive detection of various kinds of targets. However, it is still a great challenge to achieve quantitative analysis of the targets using these sensing techniques, since critical difficulties exist on how to efficiently and precisely introduce the analytes into the desired location of the near-field light focusing, and quantitatively measure the enhanced optical signal reliably. In this work, we present for the first time a localized photonic nanojet (L-PNJ) based sensing platform which provides a strategy to achieve quantitative biosensing via utilizing a unique light-analyte interaction system. We demonstrate that individual fluorescent microsphere of different sizes can be readily introduced to the light-analyte interaction system with loading efficiency more than 70%, and generates reproducible enhanced fluorescence signals with standard deviation less than 7.5%. We employ this sensing platform for fluorescent-bead-based biotin concentration analysis, achieving the improvement on the detection sensitivity and limit of detection, opening the door for highly sensitive and quantitative biosensing. This L-PNJ based sensing platform is promising for development of next-generation on-chip signal amplification and quantitative detection systems