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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.
Based on such software validation procedure, the full potential of numerical simulation can be unleashed. High-end software allows for a deep insight into internal physical processes which are hard to assess experimentally. This often reveals key mechanisms that limit the device performance. Understanding these processes enables the final step of a typical simulation project, which is the optimization of device design and performance. Examples are given on the NUSOD website and more publication guidelines are discussed here.
In summary, these are my 5 recommended steps for working with commercial software: