4 resultados para Coupled Bose-Einstein condensate

em Universidade do Minho


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The paper presents studies of Bose--Einstein Correlations (BEC) for pairs of like-sign charged particles measured in the kinematic range pT> 100 MeV and |η|< 2.5 in proton--proton collisions at centre-of-mass energies of 0.9 and 7 TeV with the ATLAS detector at the CERN Large Hadron Collider. The integrated luminosities are approximately 7 μb−1, 190 μb−1 and 12.4 nb−1 for 0.9 TeV, 7 TeV minimum-bias and 7 TeV high-multiplicity data samples, respectively. The multiplicity dependence of the BEC parameters characterizing the correlation strength and the correlation source size are investigated for charged-particle multiplicities of up to 240. A saturation effect in the multiplicity dependence of the correlation source size is observed using the high-multiplicity 7 TeV data sample. The dependence of the BEC parameters on the average transverse momentum of the particle pair is also investigated.

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In this study, Ag:SiC nanocermets were prepared via rapid thermal annealing (RTA) of pulsed laser-deposited SiC/Ag/SiC trilayers grown on Si substrate. Atomic force microscope images show that silver nanoparticles (Ag NPs) are formed after RTA, and the size of NPs increases with increasing Ag deposition time (t Ag). Sharp dip observed in the reflectance spectra confirmed the existence of Ag surface plasmons (SPs). The infrared transmission spectra showed an intense and broad absorption band around 780–800 cm−1 that can be assigned to Si-C stretching vibration mode. Influence of t Ag on the spectral characteristics of SP-enhanced photoluminescence (PL) and electrical properties of silicon carbide (SiC) films has been investigated. The maximum PL enhancement by 5.5 times for Ag:SiC nanocermets is achieved when t Ag ≈ 50 s. This enhancement is due to the strong resonant coupling between SiC and the SP oscillations of the Ag NPs. Presence of Ag NPs in SiC also induces a forming-free resistive switching with switching ratio of 2 × 10−2. The analysis of I–V curves demonstrates that the trap-controlled space-charge-limited conduction with filamentary model is the governing mechanism for the resistive switching in nanocerment thin films.

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The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

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We demonstrate the first example of silicon nanowire array photocathodes coupled with hollow spheres of the emerging earth-abundant cobalt phosphide catalysts. Compared to bare silicon nanowire arrays, the hybrid electrodes exhibit significantly improved photoelectrochemical performance toward the solar-driven H2 evolution reaction.