Effect of the surface-plasmon-exciton coupling and charge transfer process on the photoluminescence of metal-semiconductor nanostructures

National Basic Research Program of China [2012CB619302, 2010CB923204, 2009CB930704]; National Natural Science Foundation of China [61106118]; Natural Science Foundation of Fujian Province of China [2011J01362]; Fundamental Research Funds for the Central Universities [2011121026]The effect of direct metal coating on the photoluminescence (PL) properties of ZnO nanorods (NRs) has been investigated in detail in this work. The direct coating of Ag nanoparticles (NPs) induces remarkable enhancement of the surface exciton (SX) emissions from the ZnO NRs. Meanwhile, the charge transfer process between ZnO and Ag also leads to notable increment of blue and violet emissions from Zn interstitial defects. A thin SiO2 blocking layer inserted between the ZnO and Ag has been demonstrated to be able to efficiently suppress the defect emission enhancement caused by the direct contact of metal-semiconductor, without weakening the surface-plasmon-exciton coupling effect. A theoretical model considering the type of contacts formed between metals, ZnO and blocking layer is proposed to interpret the change of the PL spectra

Measurement of Neutrino-Electron Scattering Cross-Section with a CsI(Tl) Scintillating Crystal Array at the Kuo-Sheng Nuclear Power Reactor

The $\bar{\nu}_{e}-e^{-}$ elastic scattering cross-section was measured with a CsI(Tl) scintillating crystal array having a total mass of 187kg. The detector was exposed to an average reactor $\bar{\nu}_{e}$ flux of $\rm{6.4\times 10^{12} ~ cm^{-2}s^{-1}}$ at the Kuo-Sheng Nuclear Power Station. The experimental design, conceptual merits, detector hardware, data analysis and background understanding of the experiment are presented. Using 29882/7369 kg-days of Reactor ON/OFF data, the Standard Model(SM) electroweak interaction was probed at the squared 4-momentum transfer range of $\rm{Q^2 \sim 3 \times 10^{-6} ~ GeV^2}$. The ratio of experimental to SM cross-sections of $\xi =[ 1.08 \pm 0.21(stat)\pm 0.16(sys)]$ was measured. Constraints on the electroweak parameters $(g_V , g_A)$ were placed, corresponding to a weak mixing angle measurement of \s2tw = 0.251 \pm 0.031({\it stat}) \pm 0.024({\it sys}) . Destructive interference in the SM \nuebar -e process was verified. Bounds on anomalous neutrino electromagnetic properties were placed: neutrino magnetic moment at \mu_{\nuebar}< 2.2 \times 10^{-10} \mu_{\rm B} and the neutrino charge radius at -2.1 \times 10^{-32} ~{\rm cm^{2}} < \nuchrad < 3.3 \times 10^{-32} ~{\rm cm^{2}}, both at 90% confidence level.Comment: 18 Figures, 7 Tables; published version as V2 with minor revision from V

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis