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We here present a novel device architecture consisting of multiple nanoscale electron injectors connected to the same contact and constituting one individual pixel: by appropriate spacing of the injectors within the diffusion length of the photogenerated excess carriers, the fill factor of such multi-injector pixel can be considerably improved. The presented design was successfully implemented into an integrated FPA for SWIR imaging, showing excellent pixel yield, and a sensitivity of ~10 photons. While the high sensitivity is enabled by the small size of the 1μm injectors, the multi-injector design allows to achieve an area fill factor or ~20% of the 30x30μm pixel area, which is considerably higher than that of a single-injector design.
In summary, we demonstrate a highly sensitive SWIR FPA based on 1μm electron multi-injector design, which allows for a substantial improvement of the imager’s quantum efficiency and sensitivity.
We present a novel approach for the systematic optimization of the design of electro-absorptive modulators, based on a combination of analytical modeling and supervised machine learning. Fully-validated analytical modeling of the electronic transitions and optical propagation in the semiconductor compound is used for the training of an evolutionary algorithm, which drives the global search for optimal design.
The approach was tested for the optimization of the superlattice design of the electro-absorptive modulator for two different applications: time-of-flight 3D ranging camera, and remote sensing of electro-chemical signal via optical tagging. In both cases, a system-specific figure-of-merit is proposed and employed for the evaluation and optimization of the performance, yielding two novel optimized designs which allow for considerable performance improvement of the respective systems.
In order to analyze detector deficiencies for a particular scientific application, accurately defined transient behavioral models of all the functional blocks are required. Furthermore, various simulations, such as transient, noise, Monte Carlo, inter-pixel effects, etc. of the entire array need to be performed within a reasonable time frame without trading off accuracy. The sensor and the analog front-end can be modeling using a real number modeling language, as complex mathematical functions or detailed data can be saved to text files, for further top-level digital simulations. Parasitically aware digital timing is extracted in a standard delay format (sdf) from the pixel digital back-end layout as well as the periphery of the ROIC. For any given input, detector level worst-case and best-case simulations are performed using a Verilog simulation environment to determine the output. Each top-level transient simulation takes no more than 10-15 minutes. The impact of changing key parameters such as sensor Poissonian shot noise, analog front-end bandwidth, jitter due to clock distribution etc. can be accurately analyzed to determine ROIC architectural viability and bottlenecks. Hence the impact of the detector parameters on the scientific application can be studied.
Growth and characterization of InAs/GaSb type-II superlattice for long-wavelength infrared detectors
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