Power Spectral Density Analysis for Optimizing SERS Structures

The problem of optimizing the topography of metal structures allowing Surface Enhanced Raman Scattering (SERS) sensing is considered. We developed a model, which randomly distributes hemispheroidal particles over a given area of the glass substrate and estimates SERS capabilities of the obtained structures. We applied Power Spectral Density (PSD) analysis to modeled structures and to atomic force microscope images widely used in SERS metal island films and metal dendrites. The comparison of measured and calculated SERS signals from differing characteristics structures with the results of PSD analysis of these structures has shown that this approach allows simple identification and choosing a structure topography, which is capable of providing the maximal enhancement of Raman signal within a given set of structures of the same type placed on the substrate.

Frequency Analysis of Transients in Electrochemical Noise of Superalloys Waspaloy and Ultimet

Nickel or Cobalt-based superalloys represent an important class of engineering materials, finding widespread application in critical components within the gas turbine engines used for jet propulsion and electricity generation. This research aimed at the frequency analysis of transients in electrochemical noise of Waspaloy and Ultimet superalloys, immersed in 3.5 wt.% in H2SO4 and NaCl solutions at two different temperatures, 25 and 60 °C. Localized corrosion behavior of superalloys was assessed using the electrochemical noise technique (EN) according to ASTM-G199 standard. Three different statistical methods filtered the EN signal, and the polynomial method was employed to obtain the noise resistance (Rn), the localization index (LI), skew and kurtosis, and the power spectral density analysis (PSD). Results indicate that the current and potential noise transients have a better behavior with better clarity when a polynomial is used to show a localized corrosion kurtosis for both superalloys.