Soft X‐ray spectromicroscopy studies of pitting corrosion of reinforcing steel bar
Bibliographic record
Abstract
Pitting corrosion of reinforcing steel bar (rebar) imbedded in concrete by chloride ions can cause concrete degradation. It is thus necessary to develop methods to mitigate concrete corrosion which could include using a protective polymer rebar coating. Corrosion studies of polyvinyl butyral‐carbon black polymer‐coated rebar using soft X‐ray fluorescence (XRF) microprobe and micro‐X‐ray absorption near edge spectroscopy (μ‐XANES) are reported in this study. After removal of the polyvinyl butyral‐carbon black polymer coating, Fe Lα 1 , Mn Lα 1 , and O Kα 1 XRF maps were collected as well as Fe and Mn L 3 ‐edge μ‐XANES spectra from different regions across the whole rebar surface by collection of total electron yield (TEY) and partial XRF yield (PFY) spectra. The distribution of metallic Fe and Fe corrosion products was determined by analysis of the Fe XRF map. The μ‐XANES spectra indicated a higher fraction of Fe (III) phases on the corroded rebar surface, while Fe (II/III) phases were the major corrosion products beneath the surface region. In addition, Mn (II) and Mn (III) were determined as the valence states of the manganese corrosion products.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".