Targeted High-Throughput Growth and Automated Phase Mapping of the Novel Semiconductor Zn₂SbN₃ Using the Analysis Package COMBIgor

High-throughput materials discovery has boomed in the past decade through the pairing of combinatorial growth methods and automated characterization routines. However, much of the data collected must still be processed manually, creating a bottleneck, notably for phase identification and phase space mapping. In this work, we will present semi-automated phase identification and targeted sputter growth of the novel semiconducting material Zn₂SbN₃, to date the only reported crystalline antimony nitride in which Sb functions as a cation with a positive oxidation state. This ternary nitride has a predicted effective electron mass of (0.15-0.19m_e) and direct band gap of 1.7 eV that may be tunable with cation disorder. X-ray diffraction patterns were run through an automated fitting routine, the fit parameters of which were fed into routines for the creation of phase maps, tracking thin-film texturing, and directed growth through the use of fit variables as proxies for properties like optical absorption. This work will present an expanded understanding of this unique and promising material as well as a widely-applicable add-on to the free, open-source data handling and analysis package COMBIgor.