How can you choose the best boundary conditions for numerical simulations of electronic devices?

2 Why are boundary conditions important?

Boundary conditions are important because they influence the quality and validity of your simulation results. Depending on the type and value of the boundary conditions you choose, you can obtain different solutions for the same problem, some of which may be more realistic and reliable than others. Moreover, boundary conditions can affect the convergence and stability of your numerical method, as well as the computational cost and time of your simulation. Therefore, you should always check and justify your boundary conditions carefully, and compare them with experimental or analytical data if possible.

4 How to choose boundary conditions?

Choosing boundary conditions is not an easy task, as it requires a deep understanding of the physics of your device, the numerical method you use, and the output you want to obtain. As a general guideline, always try to use physical boundary conditions that reflect the actual physical situation of your device, and avoid artificial or arbitrary ones. Additionally, make sure that your boundary conditions are consistent with each other and with the equations you are solving. Moreover, consider the numerical method you use and the output you want to obtain when choosing your boundary conditions. This will ensure that your simulation results are consistent with reality and avoid numerical artifacts or errors. Furthermore, it will guarantee that your solution is unique and well-posed, and prevent numerical instabilities or singularities.

5 How to test boundary conditions?

Before running your simulation, it's important to test and validate your boundary conditions to ensure they are correct and applicable for your problem. Analytical solutions can be used to compare simulation results with the analytical solution in order to identify the best boundary conditions for your problem and quantify their impact. If there is experimental data, you can compare the simulation results with it to verify the validity and reliability of the boundary conditions. Lastly, if there is no analytical solution or experimental data, a sensitivity analysis can be done by varying the type and value of the boundary conditions to evaluate their influence and uncertainty. This will help you choose the most robust and stable boundary conditions for your problem.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?