155 research outputs found

    Study of Alpha-Sigma Phase Transformation in Mechanically Alloyed Fe-Cr-Sn Alloys

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    The solubility of tin is significantly extended by mechanical alloying in near equiatomic Fe-Cr alloys. The influences of Sn concentration and of grain size on the kinetics of formation of the sigma-phase have been studied using different techniques. The sigma-phase formation is much faster for as-milled alloys than it is for conventional alloys. The sigma-phase formation rate decreases with the increase of Sn concentration in alloys with nanometer-sized grains as it does in coarse-grained alloys. The mechanisms which are responsible for the slowing-down of the alpha-sigma transformation are different in both kinds of alloys

    Study of RFe12−xMox (R =Y, Ho) compounds by neutron powder diffraction, ac susceptibility and magnetization

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    Neutron powder diffraction, magnetization and ac susceptibility measurements were performed on compounds of the series RFe12−xMox (R D Y and Ho, x D 1, 2, 3). The influence of the Mo content on both structural and magnetic properties is discussed. Comparison with published data for different Mo concentrations is made. It is found that the effect of Mo substitution for Fe on structural and magnetic properties can be described by two regimes separated by a critical Mo content around x=2.Portuguese-French JNICT-CNRS collaboration

    Muoniated radical states in the organic semiconductor phthalocyanine

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    Phthalocyanine samples of ZnPc, H2Pc and CuPc were investigated by the muon spin rotation amp; 956;SR technique. In ZnPc and H2Pc, three muoniated radical states of paramagnetic origin were identified, two of which having hyperfine interactions in the range 110 150 MHz and correspondign to muonium addition at the outer benzene rings. The third state presents a smaller hyperfine interaction about 25 MHz , and is tentatively assigned to addition at bridging nitrogen atoms. CuPc has an unpaired electron from the Cu atom, which originates a diamagnetic like signal upon muonium addition. The signal exhibits two components with very different relaxation rates, corresponding to two different spatial couplings of the Cu electron with the muonium s electro

    Electrical and raman scattering studies of ZnO:P and ZnO:Sb thin films

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    A study on the structure, electrical and optical properties of ZnO thin films produced by r.f. magnetron sputtering and implanted either with phosphorous (P) or antimony (Sb) is reported in this work. Raman spectroscopy, X-ray diffraction, optical transmittance and Hall effect measurements have been employed to characterize the samples. X-ray diffraction and Raman scattering patterns confirm that, after a 500ºC annealing, the doped films keep a polycrystalline nature with (002) preferred orientation. These films are very transparent and Hall effect results show that all have p-type conduction, despite doping ion and dose. The electric resistivity reaches values of 0.012 (cm) and 0.042 (cm) for the P and Sb-doped samples, respectivel

    Muon diffusion and trapping in chalcopyrite semiconductors

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    The diffusion parameters of diamagnetic muons in chalcopyrites CuInSe2, CuInS2, CuInTe2, CuGaTe2 and (Ag0.25Cu0.75)InSe2 were obtained by [mu]SR methods. The variations among the different compositions were found to validate the anion-antibonding localization model. The application of a two-state model to the zero-field data revealed muon trapping by defects. The dipolar width at the trap and the number of jumps before trapping were determined. The Cu vacancy is identified as the trapping center in CuInSe2 and the energy depth of the trap has been determined.http://www.sciencedirect.com/science/article/B6TVH-47K37XD-1/1/c6039f1a6212b2c9af977ddf9c54886

    Room temperature paramagnetism of ZnO:Mn films grown by RF-sputtering

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    ZnO:Mn transparent thin films (thickness b1 μm) with the Mn contents ranging from 1.8 to 3.25 at.% were grown by RF magnetron co-sputtering. The films are nanocrystalline, with wurtzite-structure grains of a typical size of 20 nm and with a preferential orientation of the c-axis perpendicular to the surface. According to the Raman spectroscopy data, Mn mostly substitutes Zn in the lattice sites. In spite of these factors, the nanostructure and the Mn(Zn) substitution, that are considered favorable for ferromagnetism in this material, both magnetic resonance and Faraday effect measurements show paramagnetic behavior of the ZnO:Mn films and the absence of ferromagnetic order at room temperature.FCT throughproject PTDC/FIS/72843/200

    Muonium in nano-crystalline II-VI semiconductors

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    http://www.sciencedirect.com/science/article/B6TVH-4V2NP2J-Y/2/3738c97c2d99528da5d86b486571793

    Study of using marker assisted selection on a beef cattle breeding program by model comparison

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    [EN] A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.We are grateful to the Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Merialilgenity and Conselho Nacional de apoio a Pesquisa (CNPq) for the financial support, to Agro-Pecuaria CFM for data set and the Institut de Investigacion y Tecnologia Agroalimentarias de Cataluña (IRTA) as the host institution for its full backing while preparing the research and the manuscript.Rezende, F.; Ferraz, J.; Eler, J.; Silva, R.; Mattos, E.; Ibáñez-Escriche, N. (2012). Study of using marker assisted selection on a beef cattle breeding program by model comparison. Livestock Science. 147(1-3):40-48. https://doi.org/10.1016/j.livsci.2012.03.017S40481471-
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