Preparation of gold nanoparticles (GNP) aqueous suspensions by a new method involving Tiron

A new method is proposed to produce gold nanoparticles (GNP) by in situ reduction of a gold salt dissolved in water. The reducing agent used is Tiron instead of the citrate anion most often mentioned in literature. The influence of various parameters has been investigated, such as the content of Tiron with respect to that of the precursor of gold HAuCl₄, or the initial pH of the solution after mixing of reactants. It is shown that Tiron also exerts a positive influence as a dispersant, which impedes agglomeration of gold nanoparticles. The typical average size of GNP synthesized in the present work is close to 7 nm.     

Development of polyurethane elastomer composite materials by addition of milled fiberglass with coupling agent

Polyurethane elastomer composites were developed using milled fiberglass and their mechanical properties were studied. In particular, the organically chemical treatment of the milled fiberglass was investigated in detail. It was demonstrated that both strength and toughness of the resulting elastomer composites were improved considerably with the addition content of fiberglass. Furthermore, it was indicated that the optimal properties can be achieved by the proper addition of milled fiberglass that was chemically treated using coupling agent.     

Host/guest complex of Me-β-CD/2,2-dimethoxy-2-phenyl acetophenone for initiation of aqueous photopolymerization: Kinetics and mechanism

Methylated-β-cyclodextrin (Me-β-CD) was used to complex the photoinitiator, 2,2-dimethoxy-2-phenyl acetophenone (DMPA), yielding a water-soluble host/guest complex. The comparative studies demonstrated that the Me-β-CD complexed DMPA exhibited a high photoreactivity identical to the uncomplexed DMPA, while the CD complex obviously influenced the products of primary photolysis of DMPA and the photopolymerization kinetics due to the steric effect of CD on the subsequent initiation reactions. The photopolymerization rate of acrylamide can be described by the equation: R_p=K[2a]^0.62[M]^1.37[I]^0.5[Me-β-CD]⁰. The mechanism of polymerization was also discussed.     

近期国内天然橡胶市场动态

本周（10月20～24日）亚洲天胶市场天胶价格小幅震荡，现货市场成交有限。期货沪胶在13000元震荡较为明显，市场商家仍多处于观望状态，对橡胶后市信心不足。本周CIF中国主港11月船期报价：泰国烟片胶RSS3外盘报价1640美元-1675美元／吨，泰国标准胶STR20外盘报价1550美元～1605美元／吨，印尼标准胶SIR20外盘报价1560美元～1580美元／吨，马来西亚标准胶SMR20外盘报价1670美元～1705美元／吨，越南标准胶SVR3L外盘报价1670美元-1705美元／吨，泰国乳胶外盘报价1340美元～1390美元／吨。本周国内天胶两大产区均未有成交，本周标准胶SCR5近期跟随期货市场价格波动，国内大部分销区市场主流报价在14700元～16000元／吨左右，下跌幅度高达1000元／吨左右。     

Effects of compressive and tensile stress on the growth mode of epitaxial oxide films

Oxide films were deposited on different substrates by laser molecular beam epitaxy. Reflection high-energy electron diffraction was performed to in situ investigate the change of growth mode and the lattice relaxation during the growth. An asymmetrical phenomenon was found in the two kinds of strain states, compressive stress and tensile stress of heterostructures with different lattice mismatch. In the case of BaTiO₃/SrTiO₃ (2.2%), 2D layer-by-layer growth mode without lattice relaxation can be maintained for a longer period for BTO films on STO with compressive stress, comparing to STO films on BTO with tensile stress. When MgO films were deposited on SrTiO₃ with a large mismatch of 7.8%, compressive stress leads to rapid lattice relaxation with a very thin wet layer, and 3D strained island were observed. As a comparison, SrTiO₃ films on MgO with tensile stress were configured. No RHEED patterns can be observed duo to a large tensile stress.     

Integration of prior knowledge of measurement noise in kernel density classification

Samples can be measured with different precisions and reliabilities in different experiments, or even within the same experiment. These varying levels of measurement noise may deteriorate the performance of a pattern recognition system, if not treated with care. Here we seek to investigate the benefit of incorporating prior knowledge about measurement noise into system construction. We propose a kernel density classifier which integrates such prior knowledge. Instead of using an identical kernel for each sample, we transform the prior knowledge into a distinct kernel for each sample. The integration procedure is straightforward and easy to interpret. In addition, we show how to estimate the diverse measurement noise levels in a real world dataset. Compared to the basic methods, the new kernel density classifier can give a significantly better classification performance. As expected, this improvement is more obvious for small sample size datasets and large number of features.