Regression analysis of compositional data when both the dependent variable and independent variable are components

It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features

Enhancement of oxidation rate of a-Si nanoparticles during dehydrogenation

Oxidation of amorphous silicon (a-Si) nanoparticles grown by plasma-enhanced chemical vapor deposition were investigated. Their hydrogen content has a great influence on the oxidation rate at low temperature. When the mass gain is recorded during a heating ramp in dry air, an oxidation process at low temperature is identified with an onset around 250°C. This temperature onset is similar to that of hydrogen desorption. It is shown that the oxygen uptake during this process almost equals the number of hydrogen atoms present in the nanoparticles. To explain this correlation, we propose that oxidation at low temperature is triggered by the process of hydrogen desorption