Structural and doping effects in the half-metallic double perovskite A2A_2CrWO6_6

he structural, transport, magnetic and optical properties of the double perovskite $A_2$CrWO$_6$ with $A=\text{Sr, Ba, Ca}$ have been studied. By varying the alkaline earth ion on the $A$ site, the influence of steric effects on the Curie temperature $T_C$ and the saturation magnetization has been determined. A maximum $T_C=458$ K was found for Sr$_2$CrWO$_6$ having an almost undistorted perovskite structure with a tolerance factor $f\simeq 1$. For Ca$_2$CrWO$_6$ and Ba$_2$CrWO$_6$ structural changes result in a strong reduction of $T_C$. Our study strongly suggests that for the double perovskites in general an optimum $T_C$ is achieved only for $f \simeq 1$, that is, for an undistorted perovskite structure. Electron doping in Sr$_2$CrWO$_6$ by a partial substitution of Sr$^{2+}$ by La$^{3+}$ was found to reduce both $T_C$ and the saturation magnetization $M_s$. The reduction of $M_s$ could be attributed both to band structure effects and the Cr/W antisites induced by doping. Band structure calculations for Sr$_2$CrWO$_6$ predict an energy gap in the spin-up band, but a finite density of states for the spin-down band. The predictions of the band structure calculation are consistent with our optical measurements. Our experimental results support the presence of a kinetic energy driven mechanism in $A_2$CrWO$_6$, where ferromagnetism is stabilized by a hybridization of states of the nonmagnetic W-site positioned in between the high spin Cr-sites.Comment: 14 pages, 10 figure

Role of Cu During Sintering of Fe0.96Cu0.04 Nanoparticles

Nanoparticle agglomerates of passivated Fe (n-Fe) and Fe0.96Cu0.04 (n-Fe0.96Cu0.04), synthesized through the levitational gas condensation (LGC) process, were compacted and sintered using the conventional powder metallurgy method. The n-Fe0.96Cu0.04 agglomerates produced lower green density than n-Fe, and when compacted under pressure beyond 200 MPa, they underwent lateral cracking during ejection attributed to the presence of a passive oxide layer. Sintering under dynamic hydrogen atmosphere can produce a higher density of compact in n-Fe0.96Cu0.04 in comparison to n-Fe. Both the results of dilatometry and thermogravimetric (TG) measurements of the samples under flowing hydrogen revealed enhancement of the sintering process as soon as the reduction of oxide layers could be accomplished. The shrinkage rate of n-Fe0.96Cu0.04 reached a value three times higher than n-Fe at a low temperature of 723 K (450 A degrees C) during heating. This enhanced shrinkage rate was the manifestation of accumulation of Cu at the surface of the particles. The formation of a thin-surface melted layer enriched with copper during heating to isothermal holding facilitated as a medium of transport for diffusion of the elements. The compacts produced by sintering at 773 K (500 A degrees C), with relative density 82 pct, were found to be unstable and oxidized instantly when exposed to ambient atmosphere. The stable compacts of density more than 92 pct with 300- to 450-nm grain size could only be produced when sintering was carried out at 973 K (700 A degrees C) and beyond. The 0.22 wt pct residual oxygen obtained in the sintered compact is similar to what is used for conventional ferrous powder metallurgy products

Exponential smoothing weighted correlations

In many practical applications, correlation matrices might be affected by the “curse of dimensionality” and by an excessive sensitiveness to outliers and remote observations. These shortcomings can cause problems of statistical robustness especially accentuated when a system of dynamic correlations over a running window is concerned. These drawbacks can be partially mitigated by assigning a structure of weights to observational events. In this paper, we discuss Pearson’s ρ and Kendall’s τ correlation matrices, weighted with an exponential smoothing, computed on moving windows using a data-set of daily returns for 300 NYSE highly capitalized companies in the period between 2001 and 2003. Criteria for jointly determining optimal weights together with the optimal length of the running window are proposed. We find that the exponential smoothing can provide more robust and reliable dynamic measures and we discuss that a careful choice of the parameters can reduce the autocorrelation of dynamic correlations whilst keeping significance and robustness of the measure. Weighted correlations are found to be smoother and recovering faster from market turbulence than their unweighted counterparts, helping also to discriminate more effectively genuine from spurious correlations