| Autor: |
James A. Grant-Jacob, Michalis N. Zervas, Ben Mills |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2045-2322 |
| DOI: |
10.1038/s41598-024-81389-9 |
| Popis: |
Abstract The appearance of plasma generated during femtosecond laser machining depends strongly on the features present on the sample before machining occurs. However, the complexity of femtosecond light-matter interaction means that development of a theoretical understanding of plasma generation is challenging. In this work, principal component analysis is applied to experimental images of plasma generated during femtosecond laser machining of silicon to calculate the orthogonal spatial patterns of the plasma variance (plasma modes), and to identify which sample variance (sample modes) are associated with these plasma modes. The results demonstrate the potential of principal component analysis for data-driven scientific discovery in the field of femtosecond light-matter interactions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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