The effect of loading modes on the strain-dependent energy gap of CdTe quantum dots: A first-principles study

The strain-dependent photoluminescence (PL) properties of quantum dots (QDs) make them potential stress/strain sensing materials (SSM), especially for high-level stress states with nanometer and nanosecond resolution. However, the PL intensity and wavelength of QDs in experiments show nonlinear and...

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Veröffentlicht in:Computational materials science 2023-01, Vol.217, p.111915, Article 111915
Hauptverfasser: Wang, Jundiao, Shi, Ronghao, Xiao, Pan
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Sprache:eng
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Zusammenfassung:The strain-dependent photoluminescence (PL) properties of quantum dots (QDs) make them potential stress/strain sensing materials (SSM), especially for high-level stress states with nanometer and nanosecond resolution. However, the PL intensity and wavelength of QDs in experiments show nonlinear and non-monotonic dependence on applied strain/stress under some loading conditions, and the underlying mechanism needs microscopic investigations. In the work, first-principles calculations are performed on CdTe QDs of different sizes under three loading modes: hydrostatic compression (HC), shock compression (SC) and uniaxial compression (UC). Results show that the relationship between energy gap and applied strain is significantly dependent on the size of QD and the loading mode. Under the HC mode, the energy gap changes of CdTe QDs increase linearly with strain and the relationship is size-independent which is suitable for stress sensing. Under the SC mode, the energy gap also increases with strain, but the relationship is size-dependent. Under the UC mode, the relationship is negatively correlated for most cases and also shows significant size-dependence. LUMO/HOMO energies and electron cloud distributions are further investigated to find the key factor that controls the variations of energy gaps with strain under different loading modes. The findings help to understand the experimental phenomena of QDs under different loading modes, and also provide information for developing QDs-based SSMs.
ISSN:0927-0256
1879-0801
DOI:10.1016/j.commatsci.2022.111915