| Autor: |
Jiachen Wan, Chuhui Wang, Chunnan Wang, Shuqing Sun, Hui Ma |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Physics, Vol 10 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2296-424X |
| DOI: |
10.3389/fphy.2022.815539 |
| Popis: |
Mueller matrix polarimetry is exploited to find a potential polarization feature sensitive to subwavelength pore size variation in porous alumina samples. After careful analysis using standard machine learning methods, it is observed that existing Mueller matrix decomposition methods and parameters are insufficient to distinguish areas with different pore sizes. Thus, a new angular-based Mueller matrix polarimetry parameter capable of linearly separating areas with varying pore sizes is proposed. Such an angular-based parameter is novel because it is based on angular parameters, it utilizes multi-angle measurements, and it extracts physical information independent of existing decomposition methods or parameters. Hopefully this work should inspire future research on the angular parameters in Mueller matrix polarimetry and their relationships to microstructure information. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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