Copper(I) electrode function of two types of copper(II) ion-selective electrodes.
The response of two types of solid-state copper ion-selective electrodes with homogeneous membranes of CuAgSe and Cu(2-x)Se has been investigated in copper(I) solutions, prepared electrochemically by insitu generation from a copper anode in chloride medium. The selectivity coefficient K(pot)(Cu+, Cu(2+)) both types of electrodes has been determined. It is 10(-5.7) for the copper selenide sensor, and 10(-6.2) for the copper silver selenide one. These values are very close to that calculated for an exchange reaction proceeding on the electrode surface. The similarity in K(pot)(Cu+ ,Cu(2+)) values for different chalcogenidebased sensors suggests a common potential-generating mechanism. High chloride concentration does not interfere with the electrode response towards Cu(I), but distorts the electrode response to Cu(II).
The behaviour of a Cu(II) ion selective electrode in seawater; copper consumption capacity and copper determinations
Abstract Determinations of copper consumption capacity (CuCs.C) and labile copper concentrations in surface coastal seawater, using a copper ion selective electrode (Cu-ISE) potentiometric method under predominantly diffusive conditions, are reported. For evaluation of the copper concentrations, the points of the endpoint contiguity zone of the CuCs.C titration curve were treated by an ISE multiple standard addition technique. The results were compared with those obtained by means of a Chelex-100 (calcic form) ‘batch’ procedure-potentiometric stripping analysis. The labile copper of the sample was determined at concentrations down to 10.70 nM with an average RSD of 12%, independent of the Cu-ISE employed. For adjacent subsamples, the mean CuCs.C values obtained for El Way seawater were equivalent to 81.05 and 48.00 nM copper, with an RSD of 4 and 7%, and for Isla Santa Maria seawater the value was equivalent to 70.27 nM copper, with an RSD of 7%. The theoretical approach of the electrode diffusive mechanism proposed, which would depend, fundamentally, on the adsorptive, complexing and reducing properties of the dissolved organic matter in the seawater sample, allows simultaneous analytical determination of CuCs.C and labile copper concentration in seawater.
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.