Ligand-stabilized CdSe nanoplatelet hybrid structures with tailored geometric and electronic properties. New insights from theory

Abstract

Quasi-two dimensional CdSe nanoplatelets with a well-controlled thickness exhibit several advantageous properties for optical and opto-electronic application, such as in quantum dot sensitized solar cells. Due to the quantum confinement effects arising from their thickness of typically a few nanometers, the excitonic and charge carrier properties of these nanoobjects can be easily tuned by varying the number of monolayers they are composed of and the passivating ligands adsorbed on their surface. We have performed a density functional theory (DFT) investigation of the geometrical and electronic properties of non-stoichiometric CdSe zinc blende nanoplatelets with different thicknesses in the (100) direction, stabilized by various organic (HCOO⁻) and inorganic (SH⁻ and OH⁻) ligands. The relaxation parameters and adsorption energies of the studied ligands on the polar zinc blende (100) surface have been calculated, along with the band gaps, band structures, density of states and a detailed Mulliken charge analysis of these hybrid nanostructures. The latter revealed a major electron transfer from the SH⁻ ligand towards the surface of the nanocrystals, in line with what is observed from the orbital-projected density of states. CdSe zinc blende nanoplatelets of various thicknesses, stabilized by fatty acids, SH⁻ and OH⁻ ligands have also been synthesized, and their band gaps have been measured by absorption spectroscopy. A good agreement is found between the experimental and calculated values, especially for the evolution of the band gaps with the thickness of the nanoplatelets. Taken all together, the established theoretical model and computational approach can potentially serve as a powerful tool to provide a qualitative and quantitative description of the geometrical and electronic properties of quasi-two dimensional nonstoichiometric polar inorganic semiconductor materials, at low computational cost.