Coatings To Reduce Wood Preservative Leaching
Bibliographic record
Abstract
The efficiency of semitransparent penetrating stains to reduce leaching of wood preservative components was evaluated. Five commercial wood deck finishes were applied to untreated and chromated copper arsenate (CCA), alkaline copper quat (ACQ), and copper azole (CA) treated wood, and leachates were collected and analyzed during 3 years of natural weathering exposure in Toronto, Canada. All stains evaluated effectively reduced the cumulative leaching of all inorganic preservative components by about 60% on average. Although most coatings showed significant film degradation starting around 12 months, the reduced leaching persisted even after 3 years. This suggests that temporary protection of wood with a coating during the early stages of use resulted in long-term reduction in preservative leaching potential. A two-week screening leaching test was able to predict the long-term leaching performance of different coatings reasonably well. Cured coating glass transition temperature (Tg) and liquid coating viscosity were the most important variables affecting a leaching prediction model. To effectively reduce leaching of preservative components from treated wood, coatings should have Tg low enough to withstand stresses caused by freezing in winter and have adequate viscosity to form a barrier film layer on the wood surface.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.034 | 0.003 |
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; both teacher heads agree on what is shown here.
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".