Temperature-sensitive microcapsules modification treatment to reduce formaldehyde emission from wood-based panels
Bibliographic record
Abstract
The formaldehyde emission performance of wood-based panels treated with temperature-sensitive microcapsules was evaluated in this study. Formaldehyde scavenger-filled microcapsules were synthesized by the emulsion-solvent method using ethylcellulose and poly(N-isopropylacrylamide) (PNIPAM) as shell materials containing urea. The results demonstrated that the temperature-sensitive microcapsules exhibited perfect core–shell structures at a core/shell/PNIPAM ratio of 2:2:1. The loading capacity and loading efficiency of the functional core material of the microcapsules reached 33% and 59%, respectively. Compared with untreated panels, panels based on the temperature-sensitive microcapsule scavenger had better performance in controlling free formaldehyde emissions, the formaldehyde emission of treated panels decreased by 42% and 41% at room temperature and 40°C, respectively. The results indicated that the reason why the wood-based panels had a long-term low-level emission was that the microcapsules showed different release behaviour at different temperature, so they have different release paths and release principles.
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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 | 0.000 | 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 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".