Investigations on deep-level defects in HgTe nanocrystals-based photovoltaic devices using a novel instrumentation for deep level transient spectroscopy

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PhD; 2023; Physics

Colloidally produced nanocrystals (NCs) arranged in thin films hold promise for next-generation semiconductors. These NCs offer tunability in semiconductor properties due to their size, shape, composition, and surface characteristics. However, the performance of NC-based optoelectronic devices still lags behind theoretical predictions. This is primarily attributed to electronic deep-level trap states, which act as recombination centres and limit effective mobility. The large surface area, hybrid nature, and disordered structure of NCs contribute to the abundance of trap states. To improve device performance, it is crucial to identify these defects and understand their impact on electrical characteristics. This work employs Deep Level Transient Spectroscopy (DLTS) to identify deep-level defects in NCs and NC-based photovoltaic devices. DLTS allows for determining defect level energy, concentration, capture cross-section, and differentiation between minority and majority carrier traps. This technique is highly sensitive, capable of detecting low defect concentrations, and resolves signals from various traps. The conventional DLTS system suffers from drawbacks, including the need for multiple temperature cycles, which can lead to poor device contact and thin film adhesion.