Chemical and Elemental Depth Profiling of Very Thin Organic Layers by Constant Kinetic Energy XPS: A New Synchrotron XPS Analysis Strategy
Bibliographic record
Abstract
We present a new synchrotron X-ray photoelectron spectroscopy strategy for surface chemical analysis of materials. Our approach is based on the acquisition of photoelectron spectra at constant kinetic energies with the help of a tunable synchrotron X-radiation source. This ensures both constant and tunable information depth for all elements in a very thin organic layer. Many of the problems known to XPS depth profiling using laboratory equipment are thereby avoided. Using our methodology, the 95% information depth, z(95%), can be tuned down to about 0.7 nm in organic materials. The upper limit in our study at the HE-SGM monochromator dipole magnet beamline at the synchrotron radiation source BESSY II is about 4.3 nm. Elemental quantification is achieved through relative sensitivity factors (RSF) specific to the measurement conditions, determined either with the help of calculated photoionization cross sections and inelastic mean free paths or experimentally. The potential of the technique is demonstrated for the in-depth analysis of plasma deposited nitrogen-rich organic thin films used in biomedical applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".