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

TL;DR

This paper demonstrates a novel algorithmic approach to grow high-quality, linearly graded GeSn films on GaAs (001) substrates via molecular beam epitaxy, achieving compositions up to 16% with controlled grading.

Contribution

It introduces the first algorithmically driven method for producing linearly graded GeSn films, enabling precise composition control up to 16%.

Findings

Achieved GeSn compositions up to 16% on GaAs (001).

Demonstrated composition targeting and grading using a logarithmic-based algorithm.

Validated growth quality with X-ray diffraction, SIMS, and AFM analyses.

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.