Use of radiofrequency power to enable glow discharge optical emission spectroscopy ultrafast elemental mapping of combinatorial libraries with nonconductive components: nitrogen-based materials
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Combinatorial chemistry and high-throughput techniques are an efficient way of exploring optimal values of elemental composition. Optimal composition can result in high performance in a sequence of material synthesis and characterization. Materials combinatorial libraries are typically encountered in the form of a thin film composition gradient which is produced by simultaneous material deposition on a substrate from two or more sources that are spatially separated and chemically different. Fast spatially resolved techniques are needed to characterize structure, composition, and relevant properties of these combinatorial screening samples. In this work, the capability of a glow discharge optical emission spectroscopy (GD-OES) elemental mapping system is extended to nitrogen-based combinatorial libraries with nonconductive components through the use of pulsed radiofrequency power. The effects of operating parameters of the glow discharge and detection system on the achievable spatial resolution were investigated as it is the first time that an rf source is coupled to a setup featuring a push-broom hyperspectral imaging system and a restrictive anode tube GD source. Spatial-resolution optimized conditions were then used to characterize an aluminum nitride/chromium nitride thin-film composition spread. Qualitative elemental maps could be obtained within 16.8 s, orders of magnitude faster than typical techniques. The use of certified reference materials allowed quantitative elemental analysis maps to be extracted from the emission intensity images. Moreover, the quantitative procedure allowed correcting for the inherent emission intensity inhomogeneity in GD-OES. The results are compared to quantitative depth profiles obtained with a commercial GD-OES instrument.
KeywordsGlow discharge Optical emission spectroscopy Hyperspectral imaging Surface elemental mapping Materials combinatorial libraries
C. González de Vega acknowledges the FPI grant (ref. BES-2011-045044) associated with the MAT2010-20921-C02 project as well as her stay in the Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Mechanics of Materials and Nanostructures, Thun, Switzerland. The authors would like to acknowledge funding from the Swiss National Science Foundation through SNF project 206021_128738/1.