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Morphology control and optical properties of ZnO nanostructures grown by ultrasonic synthesis
Morales-Flores, N.,Galeazzi, R.,Rosendo, E.,Diaz1d, T.,Velumani, S.,Pal, U. Techno-Press 2013 Advances in nano research Vol.1 No.1
ZnO nanostructures of rod-like, faceted bar, cup-end bars, and spindle shaped morphologies could be grown by a low power ultrasonic synthesis process. pH of the reaction mixture seems to plays an important role for defining the final morphology of ZnO nanostructures. While the solution pH as low as 7 produces long, uniform rod-like nanostructures of mixed phase (ZnO and $Zn(OH)_2$), higher pH of the reaction mixture produces ZnO nanostructures of different morphologies in pure hexagonal wurtzite phase. pH of the reaction as high as 10 produces bar shaped uniform nanostructures with lower specific surface area and lower surface and lattice defects, reducing the defect emissions of ZnO in the visible region of their photoluminescence spectra.
Diaz, Edgar A.,Chung, Yeonseung,Papapostolou, Vasileios,Lawrence, Joy,Long, Mark S.,Hatakeyama, Vivian,Gomes, Brenno,Calil, Yasser,Sato, Rodrigo,Koutrakis, Petros,Godleski, John J. Informa Healthcare 2012 Inhalation toxicology Vol.24 No.5
<P>The study presented here is a laboratory pilot study using diluted car exhaust from a single vehicle to assess differences in toxicological response between primary emissions and secondary products resulting from atmospheric photochemical reactions of gas phase compounds with O<SUB>3</SUB>, OH and other radicals. Sprague Dawley rats were exposed for 5 h to either filtered room air (sham) or one of two different atmospheres: (i) diluted car exhaust (P)+Mt. Saint Helens Ash (MSHA); (ii) P+MSHA+secondary organic aerosol (SOA, formed during simulated photochemical aging of diluted exhaust). Primary and secondary gases were removed using a nonselective diffusion denuder. Continuous respiratory data was collected during the exposure, and bronchoalveolar lavage (BAL) and complete blood counts (CBC) were performed 24 h after exposure. ANOVA models were used to assess the exposure effect and to compare those effects across different exposure types. Total average exposures were 363 ± 66 μg/m<SUP>3</SUP> P+MSHA and 212 ± 95 µg/m<SUP>3</SUP> P+MSHA+SOA. For both exposures, we observed decreases in breathing rate, tidal and minute volumes (TV, MV) and peak and median flows (PIF, PEF and EF50) along with increases in breathing cycle times (Ti, Te) compared to sham. These results indicate that the animals are changing their breathing pattern with these test atmospheres. Exposure to P+MSHA+SOA produced significant increases in total cells, macrophages and neutrophils in the BAL and <I>in vivo</I> chemiluminescence of the lung. There were no significant differences in CBC parameters. Our data suggest that simulated atmospheric photochemistry, producing SOA in the P+MSHA+SOA exposures, enhanced the toxicity of vehicular emissions.</P>
Invariant operators, orthogonal bases and correlators in general tensor models
Diaz, Pablo,Rey, Soo-Jong Elsevier 2018 Nuclear Physics, Section B Vol.932 No.-
<P><B>Abstract</B></P> <P>We study invariant operators in general tensor models. We show that representation theory provides an efficient framework to count and classify invariants in tensor models of (gauge) symmetry <SUB> G d </SUB> = U ( <SUB> N 1 </SUB> ) ⊗ ⋯ ⊗ U ( <SUB> N d </SUB> ) . As a continuation and completion of our earlier work, we present two natural ways of counting invariants, one for arbitrary <SUB> G d </SUB> and another valid for large rank of <SUB> G d </SUB> . We construct bases of invariant operators based on the counting, and compute correlators of their elements. The basis associated with finite rank of <SUB> G d </SUB> diagonalizes the two-point function of the free theory. It is analogous to the restricted Schur basis used in matrix models. We show that the constructions get almost identical as we swap the Littlewood–Richardson numbers in multi-matrix models with Kronecker coefficients in general tensor models. We explore the parallelism between matrix model and tensor model in depth from the perspective of representation theory and comment on several ideas for future investigation.</P>