Optimization of the Number of Stacks in the Submonolayer Quantum Dot Heterostructure for Infrared Photodetectors PROJECT TITLE :Optimization of the Number of Stacks in the Submonolayer Quantum Dot Heterostructure for Infrared PhotodetectorsABSTRACT:We tend to studied the optical, electrical, and spectral properties of InAs submonolayer quantum dot infrared photodetectors with completely different variety of stacks. 3 samples with 4, half-dozen, and eight dot stacks were grown by molecular beam epitaxy below identical conditions. Increasing the quantity of stacks leads to a gradual shift in the photoluminescence ground-state transition energy of the samples from 1.195 to 1.111 eV. Cross-sectional transmission electron microscopy images ensure increase in dot size with increasing range of stacks from 4 to eight. Samples with four and six stacks measured moderately uniform dot size distribution and with any increasing the number of stacks four to eight variations in dot sizes along with improper dot size formation were observed. The activation energy of the samples was measured by both optical and electrical methods increase with increasing range of dots. All photodetectors exhibit a photocurrent peak within the range of 7.3-seven.8 μm at seventy seven K at an applied bias of -1 V. Highest peak responsivity value of 0.04523 A/W at seventy seven K was observed from the half-dozen stacked sample, which was highest among the 3 samples. It also exhibited highest detectivity of 5E9 Jones with lowest noise current density among the others. The sample with vi dot stacks is the simplest as it exhibited lowest dark current density of vi.1 (ten-seven A/cm2 and highest operating temperature of a hundred and ten K). Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Enhancing the Delay Performance of Dynamic Backpressure Algorithms Development and Evaluation of an Active Learning Support System for Context-Aware Ubiquitous Learning