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Allison Mis

Publications and source records attributed to Allison Mis.

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Improving Reproducibility of Sputter Deposited Ferroelectric Wurtzite Al0.6Sc0.4N Films using In-situ Optical Emission Spectrometry

High-Sc Al1-xScxN thin films are of tremendous interest because of their attractive piezoelectric and ferroelectric properties, but overall film quality and reproducibility are widely reported to suffer as x increases. In this study, we correlate the structure and electrical properties of Al0.6Sc0.4N with in-situ observations of glow discharge optical emission during growth. This in-situ technique uses changes in the Ar(I) and N2(I) emission lines of the glow discharge during growth to identify films that subsequently exhibit unacceptable structural and electrical performance. We show that a steady deposition throughout film growth produces ferroelectric Al0.6Sc0.4N with a reversible 80 {\mu}C cm-1 polarization and 3.1 MV cm-1 coercive field. In other films deposited using identical settings, fluctuations in both Ar(I) and N2(I) line intensities correspond to decreased wurtzite phase purity, nm-scale changes to the film microstructure, and a non-ferroelectric response. These results illustrate the power of optical emission spectroscopy for tracking changes when fabricating process-sensitive samples such as high-Sc Al1-xScxN films.

cond-mat.mtrl-sci

COMBIgor: data analysis package for combinatorial materials science

Combinatorial experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially-resolved characterization of structure and properties. Due to maturation of combinatorial methods and their successful application in many fields, the modern combinatorial laboratory produces diverse and complex data sets requiring advanced analysis and visualization techniques. In order to utilize these large data sets to uncover new knowledge, the combinatorial scientist must engage in data science. For data science tasks, most laboratories adopt common-purpose data management and visualization software. However, processing and cross-correlating data from various measurement tools is no small task for such generic programs. Here we describe COMBIgor, a purpose-built open-source software package written in the commercial Igor Pro environment, designed to offer a systematic approach to loading, storing, processing, and visualizing combinatorial data sets. It includes (1) methods for loading and storing data sets from combinatorial libraries, (2) routines for streamlined data processing, and (3) data analysis and visualization features to construct figures. Most importantly, COMBIgor is designed to be easily customized by a laboratory, group, or individual in order to integrate additional instruments and data-processing algorithms. Utilizing the capabilities of COMBIgor can significantly reduce the burden of data management on the combinatorial scientist.

cond-mat.mtrl-sci