In situ dynamic study of hydrogen oxidation on rhodium.
The reaction of hydrogen/oxygen gas mixtures with rhodium single crystals was studied using video-FIM (Field Ion Microscopy) at temperatures between 350 and 550 K and up to 2 x 10(-2) Pa total pressure. Imaging at 500 K in a hydrogen rich gas mixture (H2:O2 = 9) revealed considerable morphological changes of the (0 0 1)-oriented field emitter tip, i.e. the growth of low-index at the expense of high-index planes and strong crystal coarsening. Decreasing the hydrogen partial pressure led to chemical and structural changes of the Rh sample. Starting on the [1 1 0] planes a surface oxide formed, which spread anisotropically across the surface until it finally covered the whole visible surface area. The transformation was reversible upon increasing the hydrogen pressure back to its initial value. However, a hysteresis behavior was observed, i.e. a larger hydrogen partial pressure was found to be necessary to re-establish the initial patterns of a reactive Oad/Had layer. By varying the temperature from 400 to 500 K a phase diagram was established for the Oad/Had system. Increasing the electric field proved to shift the phase diagram towards higher H2 pressures. At 550K self-sustained kinetic oscillations with a cycle time of approximately 40s could be observed.
Visualizing catalyst heterogeneity by a multifrequential oscillating reaction
It is well documented that different surface structures of catalytically active metals may exhibit different catalytic properties. This is typically examined by comparing the catalytic activities and/or selectivities of various well-defined smooth and stepped/kinked single crystal surfaces. Here we report the direct observation of the heterogeneity of active polycrystalline surfaces under reaction conditions, which is manifested by multifrequential oscillations during hydrogen oxidation over rhodium, imaged in situ by photoemission electron microscopy. Each specific surface structure, i.e. the crystallographically different µm-sized domains of rhodium, exhibits an individual spiral pattern and oscillation frequency, despite the global diffusional coupling of the surface reaction. This reaction behavior is attributed to the ability of stepped surfaces of high-Miller-index domains to facilitate the formation of subsurface oxygen, serving as feedback mechanism of the observed oscillations. The current experimental findings, backed by microkinetic modeling, may open an alternative approach towards addressing the structure-sensitivity of heterogeneous surfaces.The structurally different domains of a polycrystalline material may exhibit differing catalytic properties. Here, the authors directly visualize this phenomenon by observing the catalytic hydrogen oxidation that oscillates, simultaneously exhibiting different frequencies for structurally different rhodium domains.
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.