Copper distribution and oxidation states near corroded fasteners in treated wood
Bibliographic record
Abstract
Metal fasteners are used to hold wood structures together. In outdoor applications, these fasteners are subject to corrosion when the wood is treated with certain preservative treatments. Typically, these treatments contain copper. Prior work has hypothesized that the mechanism of corrosion in treated wood involves reduction of copper ions from the wood treatments. However, copper was rarely detected in the corrosion products of metals embedded in treated wood, which contradicts the hypothesized mechanism. This present work utilizes synchrotron based X-ray fluorescence microscopy (XFM) and X-ray absorption near edge spectroscopy to examine the corrosion mechanism in treated wood by looking at the spatial distribution and oxidation states of copper in the treated wood near the fastener and in the corrosion products removed from the fastener surface. The samples were obtained after a 1-year corrosion test. In the wood cell walls, the oxidation state of the copper treatment did not change in the immediate vicinity of the fastener, although there was a depletion of copper near the fastener. Furthermore, copper was detected in the corrosion products in trace amounts using XFM. Together, these techniques confirm that the corrosion mechanism involves transport of the cupric ions to the fastener surface, where they are reduced and suggest that previous attempts to detect copper were unsuccessful because the concentration of copper in the corrosion products was below the level of detection of the previously used techniques.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".