(217du) Computational Modeling of Electronic Energy Transfer Between Silicon Quantum Dots Using Foerster Theory
AIChE Annual Meeting
2013
2013 AIChE Annual Meeting
Student Poster Sessions
Undergraduate Student Poster Session: Materials Engineering and Sciences
Monday, November 4, 2013 - 10:00am to 12:30pm
The efficiency of photovoltaic devices is limited by material constraints. A thorough investigation of the nanostructure, composition, and behavior of such devices is essential to the advanced development of solar energy-conversion materials for practical use. Herein lies the motivation to characterize the nanostructures of silicon quantum dots, which hold the potential to greatly improve the theoretical efficiency of current photovoltaic devices. In this study, the photodynamic properties of crystalline and amorphous silicon quantum dot systems doped with a phosphorous or aluminum atom, or with an adsorbed silver atom, and a combination thereof were characterized using the computational method of time-dependent density functional theory (TD-DFT). The systems of interest were saturated Si29 and Si35structures. The approximations of the model for calculating system property trends have yielded consistent results with empirical studies of solid-state electronic structures. Our model allows calculation of the rate of photon energy transfer between two structurally identical doped silicon quantum dots. Using the Foerster theory of electronic energy transfer, the photoexcitation energy transfer rates were computed by introducing the electric dipole-dipole interaction. The strength of the dipole interaction is associated with the transition probability of states, and is characterized by the oscillator strengths for such spectral transitions. Spatial orientation of the electric dipole moments was chosen to relate energy transfer rates to the geometric configuration of the coupled systems. Our results show that it is possible to configure the structure and relative orientation of quantum dots to obtain desired rates of electronic energy transfer.
Work partly supported by the National Science Foundation, the Dreyfus Foundation, and the University of Florida HPC