Reinald Hillebrand

Learn More
The self-ordering of nanoporous anodic aluminum oxide (AAO) in the course of the hard anodization (HA) of aluminum in sulfuric acid (H2SO4) solutions at anodization voltages ranging from 27 to 80 V was investigated. Direct H2SO4-HA yielded AAOs with hexagonal pore arrays having interpore distances D(int) ranging from 72 to 145 nm. However, the AAOs were(More)
Transition metal dichalcogenides have attracted research interest over the last few decades due to their interesting structural chemistry, unusual electronic properties, rich intercalation chemistry and wide spectrum of potential applications. Despite the fact that the majority of related research focuses on semiconducting transition-metal dichalcogenides(More)
Dense, ordered arrays of <100>-oriented Si nanorods with uniform aspect ratios up to 5:1 and a uniform diameter of 15 nm were fabricated by block copolymer lithography based on the inverse of the traditional cylindrical hole strategy and reactive ion etching. The reported approach combines control over diameter, orientation, and position of the nanorods and(More)
We performed systematic adsorption studies using self-ordered nanoporous anodic aluminum oxide (AAO) in an extended range of mean pore diameters and with different pore topologies. These matrices were characterized by straight cylindrical pores having a narrow pore size distribution and no interconnections. Pronounced hysteresis loops between adsorption and(More)
We present a methodology for the analysis of the grain morphology of self-ordered hexagonal lattices and for the quantitative comparison of the quality of their grain ordering based on the distances between nearest neighbors and their angular order. Two approaches to grain identification and evaluation are introduced: (i) color coding the relative angular(More)
We present a new neural network-based method of image processing for determining the local composition and thickness of III±V semiconductors in high resolution electron microscope images. This is of great practical interest as these parameters in ̄uence the electrical properties of the semiconductor. Neural networks suppress correlated noise from amorphous(More)
High resolution electron microscopy can within certain limits provide quantitative information on morphology and composition of crystalline materials. In layered structures of III-V semiconductor compounds changes resulting from interdiffusion phenomena across interfaces may result in image contrast changes because of composition sensitive electron(More)