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Connecting Theory and Practice in Optoelectronics
It’s time again to reflect on my peer review experience over the past year. Supported by the availability of high-end commercial software, the number of journal paper submissions on optoelectronic device simulation keeps rising. However, authors often seem to view such software as magic tool that instantaneously delivers realistic results. Mathematical models always simplify reality. But how simple is too simple? Some papers don’t even discuss the underlying theory. There are different levels of simplification possible, which are all based on specific assumptions. Certain assumptions may be inappropriate in the given situation. That is why high-end software packages offer some alternative modeling approaches and let the user decide. In other words, the user should have a detailed understanding of internal device physics and of the models provided by the software.
However, this is only the first step of a successful simulation strategy. The next step is the evaluation of material parameters used in the software. Initial simulation results are typically far off measured characteristics because key parameters are inaccurate. Literature values are quite scattered in some cases. If crucial parameters cannot be measured directly on the device, they should be varied in the simulation until quantitative agreement with measurements is achieved. The model itself may be inadequate if such effort fails or if the fit value is outside the published range. On the other hand, competing models could deliver nearly identical results (see picture) so that more decisive measurements are needed. Such calibration process is often difficult and time-consuming, but in my view, it is the only way to accomplish realistic simulations. Otherwise, calculated results are unreliable and may lead to wrong conclusions. Read more of this post
In the last two decades, there has been an increasing interest in multiscale modeling applied to electronic devices. Several factors are driving this trend. On the one hand, device dimensions of “classical” devices like MOSFETs have continuously been scaled down in order to increase device performance. On the other hand, specific properties of quantum structures are systematically utilized in modern devices. The embedding of the active device region in its environment including access regions and contacts, and the mutual interaction between different aspects like optics, thermal heating, strain and carrier transport requires an involved multiscale/multiphysics simulation approach which can handle different physical models and different length or time scales.
Nearly all photovoltaic technologies exhibit changes in device performance under extended illumination, or “light soaking”. Experiments on both commercial modules and research cells based on CdTe technology have shown improvement of cell performance under light soaking conditions for up to 20 hours. Many accredited such phenomena to the passivation of traps and migration of Cu ions. In this work, we employed a self-consistent one-dimensional (1D) diffusion-reaction simulator to study the migration and passivation of Cu related dopants in CdTe solar cell as a function of soaking conditions. Read more of this post
Graphene and related 2-dimensional (2D) materials have emerged as potential building blocks for a variety of fundamental optical and electronic components, including field-effect transistors, nonvolatile memory devices, photonics devices, and phototransistors. Recently, molybdenum disulfide (MoS2) materializes as an alternative 2D nanoflake, due to its optical sensitivity, mechanical flexibility, extraordinary on/off ratio, absence of dangling bonds and compatibility to silicon CMOS processes, which may overcome the drawbacks of graphene. However, the performance of previously reported MoS2 phototransistors is limited by the low photoresponsivity which is largely due to its poor light absorption properties. Read more of this post
Semiconductor nanowires promise light detection with enhanced sensitivity and faster transport speed. However, the short photocarrier lifetime, small light-sensing area, and weak optical absorption of nanowires cause serious problems. A possible solution lies in the photogating effect of semiconductor nanostructures, which was recently utilized in graphene-based phototransistors. Photocarriers located near the conductive channel form a strong local electric field to regulate the channel conductance through capacitive coupling. Read more of this post