Development of appropriate models for the interpretation of impedance spectra in terms of physical properties requires, in addition to insight into the chemistry and physics of the system, an understanding of the measurement error structure. The time-varying character of electrochemical systems has prevented experimental determination of the stochastic contribution to the error structure. A method is presented by which the stochastic contribution to the error structure can be determined, even for systems for which successive measurements are not replicate. Although impedance measurements are known to be heteroskedastic in frequency (i.e., have standard deviations that are functions of frequency) * Electrochemical Society Student Member.

No abstract

No abstract

The advent of the Internet as a major communication channel has triggered a great deal of interest in real‐time services such as broadcast or interactive audio and video services. In this paper, a further step into the realm of real‐time services over the Internet is presented, namely, synchronous access to remote and distributed laboratory facilities. The proposed approach demonstrates the feasibility of using remote laboratory experiments to complement and enhance traditional as well as on‐line courses in control engineering education. The distributed laboratory effectively enables students to reinforce their learning through hands‐on studies carried out in a flexible environment.

Migration-enhanced epitaxy (MEE) has been successfully employed to grow epitaxial films of the ternary compound CuInSe2 on (001) GaAs that exhibit distinct coexisting domains of both a nonequilibrium crystallographic structure characterized by CuAu (CA) cation ordering, and the compound’s equilibrium chalcopyrite structure. X-ray diffraction, transmission electron diffraction, and Raman scattering data provide evidence for this structural polytype. Distinctive signatures of the CA polytype are found in the data from each of these methods, and their analyses are consistent with assignment of this crystallographic structure to the P4̄m2 space group. This structure is found to preferentially segregate into domains that constitute a distinct metastable phase, which may be stabilized by surface kinetic effects favored by the MEE growth process.

A new paradigm is introduced for the investigation of errors in frequency-domain measurements. The propagation of errors from time-domain measurements to the desired complex variables in the frequency domain was analyzed for the frequency response analysis ͑FRA͒ algorithm, one of two techniques commonly used for spectroscopy measurements. Errors in the frequency domain were found to be normally distributed, even when the errors in the time-domain were not normally distributed and when the measurement technique introduced bias errors. For additive errors in time-domain signals, the errors in the real and imaginary impedance were found to be uncorrelated, and the variances of the real and imaginary parts of the complex impedance were equal. The equality of variances was realized except for cases where the time-domain signals contained proportional errors. The statistical characteristics of the results were in good agreement with experimental observations. Weighted complex nonlinear regression techniques are typically used to extract information from electrochemical impedance data. The error structure of the measurement is used implicitly in regression analysis and has a significant influence on the quality and amount of information that can be extracted from impedance data. The variance of the stochastic error can be incorporated explicitly into the weighting strategy for the regression and can provide a means for determining whether observed features lie outside the noise level of the measurement. The stochastic errors can also influence the use of the Kramers-Kronig relations for determining the internal consistency of the data.For the purposes of the discussion presented here, the errors in an impedance measurement are expressed in terms of the difference between the observed value Z ob () and a model value Z mod () aswhere res represents the residual error, fit () is the systematic error that can be attributed to inadequacies of the model, bias () represents the systematic experimental bias error that cannot be attributed to model inadequacies, and stoch () is the stochastic error with expectation E͕ stoch ()͖ ϭ 0. The experimental bias errors, as referred to here, may be caused by a nonstationary behavior or by instrumental artifacts.Typically, the impedance is a strong function of frequency and can vary over several orders of magnitude through the experimentally accessible frequency range. The stochastic errors of the impedance measurement are strongly heteroskedastic, which means that the variance of the stochastic errors is also a strong function of frequency. 1-4 Selection of an appropriate weighting strategy is, therefore, critical for interpretation of data.A distinction is drawn, in the present work, between stochastic errors that are randomly distributed about a mean value of zero, errors caused by the lack of fit of a model, and experimental bias errors. The problem of interpretation of impedance data is therefore defined as consisting of two parts, one of identification of experimental errors, which ...

No abstract

No abstract