Maximum a posteriori estimation for high-throughput peak fitting in X-ray photoelectron spectroscopy
We introduce a peak fitting method to estimate the model parameters and the number of peaks without using the conventional trial-and-error approach. The proposed method automatically removes excess peaks using maximum a posteriori estimation. The computation is performed efficiently by the spectrum-...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Science and Technology of Advanced Materials: Methods |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/27660400.2024.2373046 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | We introduce a peak fitting method to estimate the model parameters and the number of peaks without using the conventional trial-and-error approach. The proposed method automatically removes excess peaks using maximum a posteriori estimation. The computation is performed efficiently by the spectrum-adapted expectation–conditional maximisation algorithm with deterministic annealing. We apply the proposed method to synthetic and experimental data from a tunnel field-effect transistor. The proposed method identified two peak components in the experimental data from a [Formula: see text] sheet, which are interpreted to be the Mo [Formula: see text] and Mo [Formula: see text] peaks. No peaks were detected on the [Formula: see text]-[Formula: see text] sheet and hexagonal boron nitride ([Formula: see text]-BN) within the measured binding energy range. |
|---|---|
| ISSN: | 2766-0400 |