In-Plane Nanowires with Arbitrary Shapes on Amorphous Substrates by Artificial Epitaxy
Source abstract
Abstract
The challenge of nanowire assembly is still one of the major obstacles toward their efficient integration into functional systems. One strategy to overcome this obstacle is the guided growth approach, in which the growth of in-plane nanowires is guided by epitaxial and graphoepitaxial relations with the substrate to yield dense arrays of aligned nanowires. This method relies on crystalline substrates which are generally expensive and incompatible with silicon-based technologies. In this work, we expand the guided growth approach into noncrystalline substrates and demonstrate the guided growth of horizontal nanowires along straight and arbitrarily shaped amorphous nanolithographic open guides on silicon wafers. Nanoimprint lithography is used as a high-throughput method for the fabrication of the high-resolution guiding features. We first grow five different semiconductor materials (GaN, ZnSe, CdS, ZnTe, and ZnO) along straight ridges and trenches, demonstrating the generality of this method. Through crystallographic analysis we find that despite the absence of any epitaxial relations with the substrate, the nanowires grow as single crystals in preferred crystallographic orientations. To further expand the guided growth approach beyond straight nanowires, GaN and ZnSe were grown also along curved and kinked configurations to form different shapes, including sinusoidal and zigzag-shaped nanowires. Photoluminescence and cathodoluminescence were used as noninvasive tools to characterize the sine wave-shaped nanowires. We discuss the similarities and differences between in-plane nanowires grown by epitaxy/graphoepitaxy and artificial epitaxy in terms of generality, morphology, crystallinity, and optical properties.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Nanowire Synthesis and Applications · ZnO doping and properties · GaN-based semiconductor devices and materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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