Abstract
To characterize additional conductor loss introduced by conductor surface roughness, various models have been proposed to describe the relationship between foil roughness levels and surface roughness correction factor. However, all these empirical or physical models require a PCB sample to be manufactured and analyzed in advance. The procedure requires dissecting the PCB and is time- and labor-consuming. To avoid such a process, a new surface roughness extraction process is proposed here. Only the measured S-parameter and nominal cross-sectional information of the board are needed to extract the roughness level of conductor foils. Besides, this method can also deal with boards having non-equal roughness on different conductor surfaces, which is common in the manufactured printed circuit boards (PCB). The roughness level on each surface can be extracted separately to accurately model their contribution to the total conductor loss. The presented method is validated by both simulation and measurement. A good correlation is achieved between extracted roughness level and the measured value from the microscope.
Recommended Citation
Z. Sun et al., "Extraction of Stripline Surface Roughness using Cross-Section Information and S-Parameter Measurements," 2022 IEEE International Symposium on Electromagnetic Compatibility and Signal/Power Integrity, EMCSI 2022, pp. 80 - 85, Institute of Electrical and Electronics Engineers, Jan 2022.
The definitive version is available at https://doi.org/10.1109/EMCSI39492.2022.9889527
Department(s)
Engineering Management and Systems Engineering
Second Department
Electrical and Computer Engineering
Keywords and Phrases
printed circuit board; signal integrity; striplines; Surface roughness
International Standard Book Number (ISBN)
978-166540929-2
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2023 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2022
Comments
National Science Foundation, Grant IIP-1916535