Nitride materials feature strong chemical bonding character that leads to unique crystal structures, but many ternary nitride chemical spaces remain experimentally unexplored. The search for previously undiscovered ternary nitrides is also an opportunity to explore unique materials properties, such as transitions between cation-ordered and -disordered structures, as well as to identify candidate materials for optoelectronic applications. Here, we present a comprehensive experimental study of MgSnN2, an emerging II–IV–N2 compound, for the first time mapping phase composition and crystal structure, and examining its optoelectronic properties computationally and experimentally. We demonstrate combinatorial cosputtering of cation-disordered, wurtzite-type MgSnN2 across a range of cation compositions and temperatures, as well as the unexpected formation of a secondary, rocksalt-type phase of MgSnN2 at Mg-rich compositions and low temperatures. A computational structure search shows that the rocksalt-type phase is substantially metastable (>70 meV/atom) compared to the wurtzite-type ground state. Spectroscopic ellipsometry reveals optical absorption onsets around 2 eV, consistent with band gap tuning via cation disorder. Finally, we demonstrate epitaxial growth of a mixed wurtzite-rocksalt MgSnN2 on GaN, highlighting an opportunity for polymorphic control via epitaxy. Collectively, these findings lay the groundwork for further exploration of MgSnN2 as a model ternary nitride, with controlled polymorphism, and for device applications, enabled by control of optoelectronic properties via cation ordering.

Nitrides feature many interesting properties, such as a wide range of bandgaps suitable for optoelectronic devices including light-emitting diodes (LEDs), and piezoelectric response used in microelectromechanical systems (MEMS). Nitrides are also significantly underexplored compared to oxides and other chemistries, with many being thermochemically metastable, sparking interest from a basic science point of view. This paper reports on experimental and computational exploration of the Mg-Sb-N material system, featuring both metastable materials and interesting semiconducting properties. Using sputter deposition, we discovered a new Mg2SbN3 nitride with a wurtzite-derived crystal structure and synthesized the antimonide-nitride Mg3SbN with an antiperovskite crystal structure for the first time in thin film form. Theoretical calculations indicate that Mg2SbN3 is metastable and has properties relevant to LEDs and MEMS, whereas Mg3SbN has a large dielectric constant (28e0) and low hole effective masses (0.9m0), of interest for photovoltaic solar cell absorbers. The experimental solar-matched 1.3 eV optical absorption onset of the Mg3SbN antiperovskite agrees with the theoretical prediction (1.3 eV direct, 1.1 eV indirect), and with the measurements of room-temperature near-bandgap photoluminescence. These results make an important contribution towards understanding semiconductor properties and chemical trends in the Mg-Sb-N materials system, paving the way to future practical applications of these novel materials.

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 arXiv:1904.07989v2 [cond-mat.mtrl-sci] 30 Apr 2019 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.

Zinc tin nitride (ZnSnN2) is one of the emerging ternary nitride semiconductors considered for photovoltaic device applications due to its attractive and tunable material properties and earth abundance of constituent elements. Computational predictions of the material properties sparked experimental synthesis efforts, and currently there are a number of groups involved in ZnSnN2 research. In this article, we review the progress of research and development efforts in ZnSnN2 across the globe, and provide several highlights of accomplishments at the National Renewable Energy Laboratory (NREL). The interplay between computational predictions and experimental observations is discussed and exemplified by focusing on unintentional oxygen incorporation and the resulting changes in optical and electronic properties. The research progress over the past decade is summarized, and important future development directions are highlighted.

Cation-disordered ZnGeN₂ is found to exhibit structural and optical tunability with cation off-stoichiometry.