Tunable band-gap and isotropic light absorption from bismuth-containing GaAs core$-$shell and multi$-$shell nanowires

Abstract

Semiconductor core$-$shell nanowires based on the GaAs substrate are building blocks of many photonic, photovoltaic and electronic devices, thanks to the associated direct band-gap and the highly tunable optoelectronic properties. The selection of a suitable material system is crucial for custom designed nanowires tailored for optimised device performance. The bismuth containing GaAs materials are an imminent class of semiconductors which not only enable an exquisite control over the alloy strain and electronic structure but also offer the possibility to suppress internal loss mechanisms in photonic devices. Whilst the experimental efforts to incorporate GaBiAs alloys in the nanowire active region are still in primitive stage, the theoretical understanding of the optoelectronic properties of such nanowires is only rudimentary. This work elucidates and quantifies the role of nanowire physical attributes such as its geometry parameters and bismuth incorporation in designing light absorption wavelength and polarisation response. Based on multi-million atom tight-binding simulations of the GaBiAs/GaAs core$-$shell and GaAs/GaBiAs/GaAs multi$-$shell nanowires, our results predict a large tuning of the absorption wavelength, ranging from 0.9 $\mu$m to 1.6 $\mu$m, which can be controlled by engineering either Bi composition or nanowire diameter. The analysis of the strain profiles indicates a tensile character leading to significant light-hole mixing in the valence band states. This offers a possibility to achieve polarisation-insensitive light interaction, which is desirable for several photonic devices involving amplification and modulation of light. Furthermore, at low Bi compositions, the carrier confinement is quasi type-II, which further broadens the suitability of these nanowires for myriad applications demanding large carrier separations...

arXiv comment10 pages, 4 figures

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Cited by in corpus (1)

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