Algorithm-Based Linearly Graded Compositions of GeSn on GaAs (001) via Molecular Beam Epitaxy

Abstract

The growth of high-composition GeSn films of the future will likely be guided via algorithms. In this study we show how a logarithmic-based algorithm can be used to obtain high-quality GeSn compositions up to 16 % on GaAs (001) substrates via molecular beam epitaxy. Within we demonstrate composition targeting and logarithmic gradients to achieve linearly graded pseudomorph Ge1-xSnx compositions up to 10 % before partial relaxation of the structure and a continued gradient up to 16 % GeSn. In this report, we use X-ray diffraction, simulation, SIMS and atomic force microscopy to analyze and demonstrate some of the possible growths that can be produced with the enclosed algorithm. This methodology of growth is a major step forward in the field of GeSn development and the first demonstration of algorithmically driven, linearly graded GeSn films.