Hygromechanical mechanisms of wood cell wall revealed by molecular modeling and mixture rule analysis
Bibliographic record
Abstract
Despite the thousands of years of wood utilization, the mechanisms of wood hygromechanics remain barely elucidated, owing to the nanoscopic system size and highly coupled physics. This study uses molecular dynamics simulations to systematically characterize wood polymers, their mixtures, interface, and composites, yielding an unprecedented micromechanical dataset including swelling, mechanical weakening, and hydrogen bonding, over the full hydration range. The rich data reveal the mechanism of wood cell wall hygromechanics: Cellulose fiber dominates the mechanics of cell wall along the longitudinal direction. Hemicellulose glues lignin and cellulose fiber together defining the cell wall mechanics along the transverse direction, and water severely disturbs the hemicellulose-related hydrogen bonds. In contrast, lignin is rather hydration independent and serves mainly as a space filler. The moisture-induced highly anisotropic swelling and weakening of wood cell wall is governed by the interplay of cellulose reinforcement, mechanical degradation of matrix, and fiber-matrix interface.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".