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GaAs Cone-Shell Quantum Dots in a Lateral Electric Field: Exciton Stark-Shift, Lifetime, and Fine-Structure Splitting.

Ahmed Alshaikh | Robert H Blick | Christian Heyn
Nanomaterials (Basel, Switzerland) | 2024

Strain-free GaAs cone-shell quantum dots have a unique shape, which allows a wide tunability of the charge-carrier probability densities by external electric and magnetic fields. Here, the influence of a lateral electric field on the optical emission is studied experimentally using simulations. The simulations predict that the electron and hole form a lateral dipole when subjected to a lateral electric field. To evaluate this prediction experimentally, we integrate the dots in a lateral gate geometry and measure the Stark-shift of the exciton energy, the exciton intensity, the radiative lifetime, and the fine-structure splitting (FSS) using single-dot photoluminescence spectroscopy. The respective gate voltage dependencies show nontrivial trends with three pronounced regimes. We assume that the respective dominant processes are charge-carrier deformation at a low gate voltage U, a vertical charge-carrier shift at medium U, and a lateral charge-carrier polarization at high U. The lateral polarization forms a dipole, which can either enhance or compensate the intrinsic FSS induced by the QD shape anisotropy, dependent on the in-plane orientation of the electric field. Furthermore, the data show that the biexciton peak can be suppressed by a lateral gate voltage, and we assume the presence of an additional vertical electric field induced by surface charges.

Pubmed ID: 39057850

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Associated grants

  • Agency: Deutsche Forschungsgemeinschaft,
    Id: HE 2466/2-1
  • Agency: European Union's Horizon 2020 research and innovation program,
    Id: Marie 328 Skłodowska-Curie Grant No. 721394
  • Agency: Federal Ministry of Education and Research,
    Id: ForLab Helios

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GAAS (tool)

RRID:SCR_008967

An integrated software framework for efficient management, analysis and visualization of large amounts of gene expression data across replicated experiments.

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