Organic additive-copper(II) complexes as plating precursors

Cu(II) ions previously coordinated with typical electroplating organic additives were investigated as an alternative source of metal for plating bath. The coordination complexes were isolated from reaction between CuSO(4) and organic additives as ligands (oxalate ion, ethylenediamine or imidazole). Deposits over 1010 steel were successfully obtained from electroplated baths using the complexes without any addition of free additives, at pH = 4.5 (H(2)SO(4)/Na(2)SO(4)). These deposits showed better morphologies than deposits obtained from CuSO(4) solution either in the absence or presence of oxalate ion as additive (40 mmol L(-1)), at pH = 4.5 (H(2)SO(4)/Na(2)SO(4))It is suggestive that the starting metal plating coordinated with additives influences the electrode position processes, providing deposits with corrosion potentials shifted over + 200 mV in 0.5 mol L(-1) NaCl (1 mV s(-1)). The resistance against corrosion is sensitive to the type of additive-complex used as precursor. The complex with ethylenediamine presented the best deposit results with the lowest pitting potential (-0.27 V vs 3.0 mol L(-1) CE). It was concluded that the addition of free additives to the electrodeposition baths is not necessary when working with previously coordinated additives. Thus, the complexes generated in ex-situ are good alternatives as plating precursors for electrodeposition bath. (C) 2009 Elsevier B.V. All rights reserved.

Laws of large numbers for non-additive probabilities

We apply the concept of exchangeable random variables to the case of non-additive robability distributions exhibiting ncertainty aversion, and in the lass generated bya convex core convex non-additive probabilities, ith a convex core). We are able to rove two versions of the law of arge numbers (de Finetti's heorems). By making use of two efinitions. of independence we rove two versions of the strong law f large numbers. It turns out that e cannot assure the convergence of he sample averages to a constant. e then modal the case there is a true" probability distribution ehind the successive realizations of the uncertain random variable. In this case convergence occurs. This result is important because it renders true the intuition that it is possible "to learn" the "true" additive distribution behind an uncertain event if one repeatedly observes it (a sufficiently large number of times). We also provide a conjecture regarding the "Iearning" (or updating) process above, and prove a partia I result for the case of Dempster-Shafer updating rule and binomial trials.

Integral representation with convex capacities that are squeeze of (additive) probability measures

In this paper I will investigate the conditions under which a convex capacity (or a non-additive probability which exhibts uncertainty aversion) can be represented as a squeeze of a(n) (additive) probability measure associate to an uncertainty aversion function. Then I will present two alternatives forrnulations of the Choquet integral (and I will extend these forrnulations to the Choquet expected utility) in a parametric approach that will enable me to do comparative static exercises over the uncertainty aversion function in an easy way.