12 resultados para near net shape

em Diposit Digital de la UB - Universidade de Barcelona


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Experimental data from ultrasonic and inelastic neutron scattering measurements are analyzed for different families of Cu-based shape-memory alloys. It is shown that the transition occurs at a value, independent of composition and alloy family, of the ratio between the elastic constants associated with the two shears necessary to accomplish the lattice distortion from the bcc to the close-packed structure. The zone boundary frequency of the TA2[110] branch evaluated at the transition point (TM), weakly depends, for each family, on composition. A linear relationship between this frequency and the inverse of the elastic constant C', both quantities evaluated at TM, has been found, in agreement with the prediction of a Landau model proposed for martensitic transformations.

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Measurements of the entropy change at the martensitic transition of two composition-related sets of Cu-Al-Mn shape-memory alloys are reported. It is found that most of the entropy change has a vibrational origin, and depends only on the particular close-packed structure of the low-temperature phase. Using data from the literature for other Cu-based alloys, this result is shown to be general. In addition, it is shown that the martensitic structure changes from 18R to 2H when the ratio of conduction electrons per atom reaches the same value as the eutectoid point in the equilibrium phase diagram. This finding indicates that the structure of the metastable low-temperature phase is reminiscent of the equilibrium structure.

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We have measured the adiabatic second order elastic constants of two Ni-Mn-Ga magnetic shape memory crystals with different martensitic transition temperatures, using ultrasonic methods. The temperature dependence of the elastic constants has been followed across the ferromagnetic transition and down to the martensitic transition temperature. Within experimental errors no noticeable change in any of the elastic constants has been observed at the Curie point. The temperature dependence of the shear elastic constant C' has been found to be very different for the two alloys. Such a different behavior is in agreement with recent theoretical predictions for systems undergoing multi-stage structural transitions.

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We report on measurements of the adiabatic temperature change in the inverse magnetocaloric Ni50Mn34In16 alloy. It is shown that this alloy heats up with the application of a magnetic field around the Curie point due to the conventional magnetocaloric effect. In contrast, the inverse magnetocaloric effect associated with the martensitic transition results in the unusual decrease of temperature by adiabatic magnetization. We also provide magnetization and specific heat data which enable to compare the measured temperature changes to the values indirectly computed from thermodynamic relationships. Good agreement is obtained for the conventional effect at the second-order paramagnetic-ferromagnetic phase transition. However, at the first-order structural transition the measured values at high fields are lower than the computed ones. Irreversible thermodynamics arguments are given to show that such a discrepancy is due to the irreversibility of the first-order martensitic transition.

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We analyze the heat transfer between two nanoparticles separated by a distance lying in the near-field domain in which energy interchange is due to the Coulomb interactions. The thermal conductance is computed by assuming that the particles have charge distributions characterized by fluctuating multipole moments in equilibrium with heat baths at two different temperatures. This quantity follows from the fluctuation-dissipation theorem for the fluctuations of the multipolar moments. We compare the behavior of the conductance as a function of the distance between the particles with the result obtained by means of molecular dynamics simulations. The formalism proposed enables us to provide a comprehensive explanation of the marked growth of the conductance when decreasing the distance between the nanoparticles.