Optical and structural properties of self-assembled ZnO QD chains by L-MBE

ZnO complex 3D nano-structures have been self-organized on Al2O3 (0 0 0 1) substrate by laser molecular beam epitaxy (L-MBE). It is shown by AFM morphology that the structure is composed of ID quantum dot chains (QDCs) and larger nano-islands at the nodes of QDCs. The formation mechanism of the nano-structure is also investigated. XRD results indicate that the nano-structure is highly c-axis oriented, with the aligned in-plane oriented domains. Time-integrated photoluminescence (TIPL) of the sample shows obvious blue-shift and broadening of the near band-edge (NBE) emission at room temperature, which are related to the quantum confinement effects. Time-resolved PL (TRPL) result shows bi-exponential decay behavior of ZnO QDCs, with a fast decay time of 38.21 ps and a low decay time of 138.19ps, respectively, which is considered to be originated from the interdot coupling made by coherent emission and reabsorption of the photons in QDCs. (C) 2007 Elsevier B.V. All rights reserved.

The mean value concept in mono-linear regression of multi-variables and its application to trace studies in geosciences

IEECAS SKLLQG

Alpha decay half-lives of heavy nuclei within a generalized liquid drop model

Theoretical alpha-decay half-lives of the heaviest nuclei are calculated using the experimental Q value. The barriers in the quasi-molecular shape path is determined within a Generalized Liquid Drop Model (GLDM) and the WKB approximation is used. The results are compared with calculations using the Density-Dependent, M3Y (DDM3Y) effective interaction and the Viola-Seaborg-Sobiczewski (VSS) formulae. The calculations provide consistent estimates for the half-lives of the a decay chains of these superheavy elements. The experimental data stand between the GLDM calculations and VSS ones in the most time.

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.

bridge the gap between software test process and business value: a case study

Chinese Academy of Sciences (ISCAS)

value-based multiple software projects scheduling with genetic algorithm

Chinese Acad Sci, ISCAS Lab Internet Software Technologies

Phosphonate-Functionalized Polyfluorene as a Highly Water-Soluble Iron(III) Chemosensor

An anionic, phosphonate-functionalized polyfluorene, i.e., poly(9,9-bis(3'-phosphatepropyl)fluorene-alt-1,4-phenylene) sodium salt (PFPNa), has been synthesized by copolymerization of phosphonic acid-substituted 2,7-dibromofluorene and phenyldiboronic ester via direct Suzuki polycondensation reaction in DMF/water. Polymer PFPNa is highly soluble and emissive in water with a solubility of 60 mg/mL and a photoluminescence quantum yield of 75%. The absorption and fluorescence spectra of PFPNa are strongly dependent on pH value owing to the partial protonation of phosphate groups and the aggregation of the polymer chains.

A copper/p-sulfonatocalix[6]arene/phenanthroline supramolecular compound with 1D [Cu-2-calixarene](n) coordination chains

A supramolecular complex [Cu(phen)(2)H2O]{[Cu(phen)(H2O)](2)[C6AS]}center dot 2.5H(2)O (phen = 1,10'-phenanthroline and C6AS = p-sulfonatocalix[6]arene) has been synthesized under hydrothermal condition, and characterized by IR spectroscopy, TG analysis and single crystal X-ray diffraction. In the structure, unprecedented 1D ({[Cu(phen)(H2O)](2)[C(6)AS]}(2-))(n) coordination chains (exactly being belts) are stacked into some 2D layers by the pi center dot center dot center dot pi stacking interactions, which are further interconnected into a 3D extended structure by hydrogen bonding.