Dynamic evolution of the submicrometer surface morphology of a copper grain undergoing electrodissolution in the “electroetching regime” has been monitored by in situ atomic force microscopy. Images obtained for a nominal current density of 400 μA cm-2 indicate rapid etching into the surface to reveal well-defined crystallographic faces. The thermodynamically most stable {111} facets develop first, forming the initial primary dissolution faces; but as dissolution progresses, they are replaced by stably dissolving {211} and {221} facets. Hence, surface morphology can either be thermodynamically or kinetically controlled. Local current density is distributed inhomogeneously at the submicrometer level, being 1 order of magnitude larger than the global average at some locations. Identical crystallographic facets do not etch at the same rate and the dissolving facets typically evolve in a complex temporal-spatial manner. This behavior may be related to nonlinear pattern formation. Images obtained for a lower current density of 20 μA cm-2 provide unequivocal evidence of a surface recrystallization phenomenon concurrent with the anodic dissolution process. The surface reordering extends up to the submicrometer length scale and leads to development of smooth facets.

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OBJECTIVES:A protocol for the valuation of SF-6D health states began with telling the participants that the "all-worst" health state (645655) was the worst among all health states to be considered. Respondents might decide if "all-worst" was worse or better than dead. This secondary analysis aimed to evaluate whether this practice would have an impact on the valuation results. METHODS: This was a population-based valuation study of the SF-6D, involving totally 1020 participants in Singapore. The SF-6D health states were valued using a visual analogue scale (full healthϭ100 points). This analysis focused on the 73 participants who valued the all-worst health state and at least one health state that was only one step better than the all-worst state in one or two of the six dimensions of the SF-6D (e.g. 645555 and 545654). We call these the "near all-worst" health states. We estimated the label effect (if any) by comparing the value assigned to the all-worst versus the near all-worst health states using graphical means and regression analysis. RESULTS: A total of 56/73 participants considered the all-worst state worse than death. Among them, the all-worst health state was valued significantly lower than the near allworst health states (30 points; PϽ0.001), even after adjustment for the difference attributable to the one step difference in the six dimensions. Among the 17/53 participants who considered the all-worst state better than death, the valuation result was as expected according to the differences in the six dimensions. CONCLUSIONS:The procedure to tell participants that one of the states was "allworst" had a labeling effect, but not every respondent was affected.

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