The Improvement of Durability of Marine Wood with Polymer and its Mechanism
Bibliographic record
Abstract
In order to improve the durability of marine wood against the long-term marine corrosion, the study explores to use two bifunctional reagents, maleic anhydride (Man) and glycidyl methacrylate(GMA), to react with wood by impregnating them into the porous structure of wood and further initiating them to polymerize with an initiator, AIBN, through a heat process. After the above modification, the durability of the marine wood treated with polymer was tested, and its mechanism was further analyzed as well. The testing results of the durability show that the acid resistance, the alkali resistance, the decay resistance against marine borers and the dimensional stability of the treated wood increases by 2.02 times, 12.39 times, 4.96 times and 3 times over untreated wood, respectively; and its Anti Swelling Efficiency (ASE) for dimensional stability reaches 53%, which almost equals the value of the wood treated by PEG-1500 under the same condition, while its leachability resistance is greatly higher than wood treated by PEG-1500. The analysis result with FTIR indicates that Man and GMA both react with wood, and Man reacts with the hydroxyl group of wood cell walls by its anhydride group, and GMA polymerizes in the porous structure of wood. The charactering result with SEM reveals that the resultant polymer fills in wood cell lumina as a solid form, which contacts tightly the wood cell walls without obvious gaps. The greatly reducing amount of hydroxyl groups after the reaction and the heavy jamming channels for water and marine borers approaching to wood cell walls both contribute to the improving durability of the modified wood.
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 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".