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Studying Quantum Dots using Atomic Force Microscopy
Quantum Dots are semiconductor nanocrystals whose diameter is in the range of 2-10 nm, corre- sponding to 10 to 50 atoms in diameter and a total of 100 to 100,000 atoms within the quantum dot volume. Many types of quantum dot emit light of specific frequencies if electricity or light is applied to them, and these frequencies can be precisely tuned by changing the dots’ size, shape and material, giving rise to many applica- tions. Because of their high tunable properties, quantum dots are of wide interest. It finds its applications in nanotechnology, medical imaging, transistors, solar cells, LED’s, diode lasers, quantum computing, etc. With this project, we intend to further understand and study the properties of quantum dots by using atomic force microscopy.
Propagation of thermal diffusive waves in a metal by Fourier analysis
Thermal wave phenomenon is observed is thin metallic rod by application of periodic heating. In this way, it is demonstrated that there is no wave nature in these improperly called thermal waves by showing that they do not transport energy and its propagation properties can be used to determine the thermal diffusivity of the material.
syed waqar ahmed
Modeling spatial inhomogeneities in solar cells (MSc Thesis)
Microscopic spatial defects (inhomogeneities) in solar cells have a detrimental impact on the overall performance of the solar cells. These defects can be due to the polycrystalline nature of the photovoltaic absorber (general case) or on the other hand, the characterization method itself can induce such inhomogeneities (ex: local excitation with confocal system). Photoluminescence imaging in particular is the most attractive type of experimental character- ization technique which has been studied by many research groups. Since it is contactless, it allows a complete analysis of the photovoltaic material and it can actually be performed at each step of the solar cell fabrication process. To properly analyze the recorded images, one has to model the transport properties. In this work we model the transport properties in 2D using both a numerical and analytic approach. First,we model the global illumination of the sample, we then analyze the effects of grains and surface recombination. Second, we study lateral transport that can be influenced by recombination at the surface (passivation issues), grain boundaries (polycrystalline cells) or local artifacts (shunts, defects...). At the same time we are able to extract the lifetime knowing the generation rate and solving the excess carrier density from our model. And finally we implement our model to extract some cell parameters like the diffusion length from experimental data through data fitting.
Data acquisition from mobile sensors
Coursework project on data analysis. Using machine learning and android sensors data to predict whether gadget is located indoors or outdoors.