Bonding regimes of nitrogen in amorphous carbon

Nitrogen can have numerous effects on diamond-like carbon: it can dope, it can form the hypothetical superhard compound C3N4, or it can create fullerene-like bonding structures. We studied amorphous carbon nitrogen films deposited by a filtered cathodic vacuum arc as a function of nitrogen content, ion energy and deposition temperature. The incorporation of nitrogen from 10-2 to 10 at% was measured by secondary ion mass spectrometry and elastic recoil detection analysis and was found to vary slightly sublinearly with N2 partial pressure during deposition. In the doping regime from 0 to about 0.4% N, the conductivity changes while the sp3 content and optical gap remain constant. From 0.4 to approximately 10% N, existing sp2 sites condense into clusters and reduce the band gap. Nitrogen contents over 10% change the bonding from mainly sp3 to mainly sp2. Ion energies between 20 and 250 eV do not greatly modify this behaviour. Deposition at higher temperatures causes a sudden loss of sp3 bonding above about 150 °C. Raman spectroscopy and optical gap data show that existing sp2 sites begin to cluster below this temperature, and the clustering continues above this temperature. This transition is found to vary only weakly with nitrogen addition, for N contents below 10%.

The silent base flow and the sound sources in a laminar jet.

An algorithm to compute the silent base flow sources of sound in a jet is introduced. The algorithm is based on spatiotemporal filtering of the flow field and is applicable to multifrequency sources. It is applied to an axisymmetric laminar jet and the resulting sources are validated successfully. The sources are compared to those obtained from two classical acoustic analogies, based on quiescent and time-averaged base flows. The comparison demonstrates how the silent base flow sources shed light on the sound generation process. It is shown that the dominant source mechanism in the axisymmetric laminar jet is "shear-noise," which is a linear mechanism. The algorithm presented here could be applied to fully turbulent flows to understand the aerodynamic noise-generation mechanism.