Optimization of absorption coefficient of quantum dot structures for infrared spectroscopy.

Infrared spectroscopy is a powerful tool used in chemical analysis and identification, material and polymer characteristics, pharmaceuticals and medical diagnostics, food industry, and environmental applications. Quantum Dots have shown significant potential as a top candidate for infrared photodetection of the transmitted and absorbed frequencies which is one of the main processes in IR spectroscopy. Therefore, the demand for accurate optimization techniques for enhanced detection is critically needed. In this work, we have developed an optimization study of the optical absorption coefficient of InAs/GaAs self-assembled quantum dots for IR photodetection specially in fingerprint region, where the Bound-to-bound absorption coefficient calculations are based on the bounded states estimation using the effective mass Hamiltonian diagonalization. Then, optimization has been performed which is based on the Nelder-Mead simplex algorithm where the objective function is maximizing the optical absorption coefficient at certain wavenumbers of interest of 600 and 800 cm. Also, the optimized absorption has been compared with previously published results for different dot shapes; semi-spherical, conical and truncated conical dots, showing a considerable enhancement of the optical absorption coefficient at the wavelengths of interest. A 5% sensitivity analysis has been performed for each QD cell parameters to study the effects of tolerances around the optimized design parameters. The presented optimization approach is generic that can be applied for different wavelengths, different QD structures, and different QD and barrier materials.