Copper precipitation of Cu-monoethanolamine preservative in wood
Bibliographic record
Abstract
Abstract Copper precipitation is one of the important Cu fixation mechanisms of Cu-amine-treated wood. In the present work, possible pathways of Cu precipitation have been investigated via in vitro and in situ studies focusing on effects of pH and temperature and Cu species formed in Cu-monoethanolamine (Cu-Mea)-treated wood. Higher-concentration Cu-Mea solutions required a lower pH and higher amounts of acid for the precipitation because of the higher amount of free Mea in the preservative-wood system. For this reason, Cu fixation during wet conditioning of wood treated to high Cu retention (2.0% treating solution) resulted in only a slight pH decrease and low Cu fixation. When lower-concentration solutions (0.67% and 0.2%) were applied, the pH decreased enough for Cu precipitation, and the much higher Cu fixation rate was driven by both chemisorption and precipitation. Evaluation of leaching after wet conditioning and drying showed that additional Cu precipitation could occur during drying. Wet conditioning of Cu-Mea-treated wood at 50°C showed outwardly faster and higher Cu fixation, but resulted in higher Cu leaching. According to X-ray diffraction analysis, the in vitro precipitated Cu was a mixture of azurite and malachite, and possibly, Cu 2 O formed as a result of Cu-Mea decomposition.
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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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".