Nucleation and Growth of GaAs on a Carbon Release Layer by Halide Vapor Phase Epitaxy.

We couple halide vapor phase epitaxy (HVPE) growth of III-V materials with liftoff from an ultrathin carbon release layer to address two significant cost components in III-V device - epitaxial growth and substrate reusability. We investigate nucleation and growth of GaAs layers by HVPE on a thin amorphous carbon layer that can be mechanically exfoliated, leaving the substrate available for reuse. We study nucleation as a function of carbon layer thickness and growth rate and find island-like nucleation. We then study various GaAs growth conditions, including V/III ratio, growth temperature, and growth rate in an effort to minimize film roughness. High growth rates and thicker films lead to drastically smoother surfaces with reduced threading dislocation density. Finally, we grow an initial photovoltaic device on a carbon release layer that has an efficiency of 7.2%. The findings of this work show that HVPE growth is compatible with a carbon release layer and presents a path toward lowering the cost of photovoltaics with high throughput growth and substrate reuse.

Metal chalcogenides for neuromorphic computing: emerging materials and mechanisms.

The approaching end of Moore's law scaling has significantly accelerated multiple fields of research including neuromorphic-, quantum-, and photonic computing, each of which possesses unique benefits unobtained through conventional binary computers. One of the most compelling arguments for neuromorphic computing systems is power consumption, noting that computations made in the human brain are approximately 106times more efficient than conventional CMOS logic. This review article focuses on the materials science and physical mechanisms found in metal chalcogenides that are currently being explored for use in neuromorphic applications. We begin by reviewing the key biological signal generation and transduction mechanisms within neuronal components of mammalian brains and subsequently compare with observed experimental measurements in chalcogenides. With robustness and energy efficiency in mind, we will focus on short-range mechanisms such as structural phase changes and correlated electron systems that can be driven by low-energy stimuli, such as temperature or electric field. We aim to highlight fundamental materials research and existing gaps that need to be overcome to enable further integration or advancement of metal chalcogenides for neuromorphic systems.

Synthesis of Tunable SnS-TaS2 Nanoscale Superlattices.

Nanoscale superlattices represent a compelling platform for designed materials as the specific identity and spatial arrangement of constituent layers can lead to tunable properties. A number of kinetically stabilized, nonepitaxial superlattices with almost limitless structural tunability have been reported in telluride and selenide chemistries but have not yet been extended to sulfides. Here, we present SnS-TaS2 nanoscale superlattices with tunable layer architecture. Layered amorphous precursors are prepared as thin films programmed to mimic the targeted superlattice; subsequent low temperature annealing activates self-assembly into crystalline nanocomposites. We investigate structure and composition of superlattices comprised of monolayers of TaS2 and 3-7 monolayers of SnS per repeating unit. Furthermore, a graded precursor preparation approach is introduced, allowing stabilization of superlattices with multiple stacking sequences in a single preparation. Controlled synthesis of the architecture of nanoscale superlattices is a critical path toward tuning their exotic properties and enabling integration with electronic, optical, or quantum devices.

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. Because of the 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 and designed to offer a systematic approach to loading, storing, processing, and visualizing combinatorial data. 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.

Nanocrystalline Iron Monosulfides Near Stoichiometry.

Solids composed of iron and sulfur are earth abundant and nontoxic, and can exhibit interesting and technologically important optical, electronic, and magnetic phenomena. However, the iron-sulfur (Fe-S) phase diagram is congested in regions of slight non-stoichiometric iron vacancies, and even when the iron atomic composition changes by even a few percent at standard temperature and pressure, there are myriad stable crystal phases that form with qualitatively different electronic properties. Here, we synthesized and characterized nanocrystals of the pyrrhotite-4M structure (Fe7S8) in an anhydrous oleylamine solvent. Upon heating from 140 °C to 180 °C, the solid sequentially transformed into two kinetically trapped FeS intermediate phases before reaching the pyrrhotite-4M final product. Finally, we assessed the effects of iron vacancies using the stoichiometric end-member, troilite, as a reference system. Density functional theory calculations show that iron vacancies in troilite shift the structure from hexagonal FeS to a monoclinic structure, similar to crystal structures of pyrrhotites, and suggest that this iron deficient troilite may be a stable intermediate between the two crystal structures. The calculations predict that defects also close the band gap in iron deficient troilite.