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项目作者： garrettj403

项目描述 ：
Calculate the surface impedance of a rough metal surface using the Gradient Model.
高级语言： Python
项目地址: git://github.com/garrettj403/GradientModel.git
创建时间： 2021-02-25T03:02:26Z
项目社区：https://github.com/garrettj403/GradientModel
开源协议：MIT License
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Gradient Model

PyPI version
flake8
DOI

Calculate the surface impedance of a rough metal surface using the Gradient Model (GM)

Example: Surface Impedance of Gold

Surface impedance of gold (conductivity: 4.1e7 S/m) between 280 GHz and 360 GHz:



To use these results in HFSS, select Assign boundary > Impedance... and then copy/paste these values into the dialog box:

  1. 50 nm surface roughness:
  2.    Real:       -1.6644e-25 * Freq^2 + 5.1199e-13 * Freq^1 + 6.1107e-02
  3.    Imaginary:  -3.4813e-25 * Freq^2 + 2.2603e-12 * Freq^1 + 7.2291e-02
  4.    ur:         -1.3448e-23 * Freq^2 + 5.0514e-11 * Freq^1 + 3.9464e+00
  6. 75 nm surface roughness:
  7.    Real:       -1.5186e-25 * Freq^2 + 6.0379e-13 * Freq^1 + 5.8012e-02
  8.    Imaginary:  -4.5447e-25 * Freq^2 + 3.0960e-12 * Freq^1 + 7.9819e-02
  9.    ur:         -2.5105e-23 * Freq^2 + 9.6127e-11 * Freq^1 + 5.8256e+00
  11. 100 nm surface roughness:
  12.    Real:       -1.4427e-25 * Freq^2 + 7.0489e-13 * Freq^1 + 5.5407e-02
  13.    Imaginary:  -5.6445e-25 * Freq^2 + 3.8871e-12 * Freq^1 + 8.8834e-02
  14.    ur:         -3.9840e-23 * Freq^2 + 1.5236e-10 * Freq^1 + 8.0508e+00

References

Gradient model:

  • G. Gold and K. Helmreich, “A Physical Surface Roughness Model and Its Applications,” IEEE Trans. Microw. Theory Tech., vol. 65, no. 10, pp. 3720–3732, Oct. 2017, doi: 10.1109/TMTT.2017.2695192.

  • K. Lomakin, G. Gold, and K. Helmreich, “Analytical Waveguide Model Precisely Predicting Loss and Delay Including Surface Roughness,” IEEE Trans. Microw. Theory Tech., vol. 66, no. 6, pp. 2649–2662, Jun. 2018, doi: 10.1109/TMTT.2018.2827383.

Closed-form solution:

  • D. N. Grujic, “Closed-Form Solution of Rough Conductor Surface Impedance,” IEEE Trans. Microw. Theory Tech., vol. 66, no. 11, pp. 4677–4683, 2018, doi: 10.1109/TMTT.2018.2864586.