961 resultados para carbonium ions
Resumo:
Soft X-ray lasing across a Ni-like plasma gain-medium requires optimum electron temperature and density for attaining to the Ni-like ion stage and for population inversion in the View the MathML source3d94d1(J=0)→3d94p1(J=1) laser transition. Various scaling laws, function of operating parameters, were compared with respect to their predictions for optimum temperatures and densities. It is shown that the widely adopted local thermodynamic equilibrium (LTE) model underestimates the optimum plasma-lasing conditions. On the other hand, non-LTE models, especially when complemented with dielectronic recombination, provided accurate prediction of the optimum plasma-lasing conditions. It is further shown that, for targets with Z equal or greater than the rare-earth elements (e.g. Sm), the optimum electron density for plasma-lasing is not accessible for pump-pulses at View the MathML sourceλ=1ω=1μm. This observation explains a fundamental difficulty in saturating the wavelength of plasma-based X-ray lasers below 6.8 nm, unless using 2ω2ω pumping.
Resumo:
The numerical simulations of the magnetic properties of extended three-dimensional networks containing M(II) ions with an S = 5/2 ground-state spin have been carried out within the framework of the isotropic Heisenberg model. Analytical expressions fitting the numerical simulations for the primitive cubic, diamond, together with (10−3) cubic networks have all been derived. With these empirical formulas in hands, we can now extract the interaction between the magnetic ions from the experimental data for these networks. In the case of the primitive cubic network, these expressions are directly compared with those from the high-temperature expansions of the partition function. A fit of the experimental data for three complexes, namely [(N(CH3)4][Mn(N3)] 1, [Mn(CN4)]n 2, and [FeII(bipy)3][MnII2(ox)3] 3, has been carried out. The best fits were those obtained using the following parameters, J = −3.5 cm-1, g = 2.01 (1); J = −8.3 cm-1, g = 1.95 (2); and J = −2.0 cm-1, g = 1.95 (3).
Resumo:
As Rosetta was orbiting comet 67P/Churyumov-Gerasimenko, the Ion and Electron Sensor detected negative particles with angular distributions like those of the concurrently measured solar wind protons but with fluxes of only about 10% of the proton fluxes and energies of about 90% of the proton energies. Using well-known cross sections and energy-loss data, it is determined that the fluxes and energies of the negative particles are consistent with the production of H- ions in the solar wind by double charge exchange with molecules in the coma.
Resumo:
A stratigraphy-based chronology for the North Greenland Eemian Ice Drilling (NEEM) ice core has been derived by transferring the annual layer counted Greenland Ice Core Chronology 2005 (GICC05) and its model extension (GICC05modelext) from the NGRIP core to the NEEM core using 787 match points of mainly volcanic origin identified in the electrical conductivity measurement (ECM) and dielectrical profiling (DEP) records. Tephra horizons found in both the NEEM and NGRIP ice cores are used to test the matching based on ECM and DEP and provide five additional horizons used for the timescale transfer. A thinning function reflecting the accumulated strain along the core has been determined using a Dansgaard-Johnsen flow model and an isotope-dependent accumulation rate parameterization. Flow parameters are determined from Monte Carlo analysis constrained by the observed depth-age horizons. In order to construct a chronology for the gas phase, the ice age-gas age difference (Delta age) has been reconstructed using a coupled firn densification-heat diffusion model. Temperature and accumulation inputs to the Delta age model, initially derived from the water isotope proxies, have been adjusted to optimize the fit to timing constraints from d15N of nitrogen and high-resolution methane data during the abrupt onset of Greenland interstadials. The ice and gas chronologies and the corresponding thinning function represent the first chronology for the NEEM core, named GICC05modelext-NEEM-1. Based on both the flow and firn modelling results, the accumulation history for the NEEM site has been reconstructed. Together, the timescale and accumulation reconstruction provide the necessary basis for further analysis of the records from NEEM.