Low-Temperature Water Evaporation-Mediated Fusion and Densification of Wood for High-Performance and Sustainable Materials
Bibliographic record
Abstract
Developing high-performance wood products to replace carbon-intensive structural materials is a key approach to reducing carbon emissions, whereas transforming low-strength wood into high-performance bulk materials through eco-friendly processing techniques is challenging but highly desired. Herein, a facile and sustainable water processing strategy is reported to robustly assemble wood pieces into high-performance bulk materials via delignification, followed by room-temperature water evaporation, eliminating the need for traditional adhesives. As water penetrates and swells the microfibrils, the plasticity of the softened wood is significantly enhanced, thereby facilitating the mutual diffusion of the microfibrils. The strong capillary stresses drive the microfibrils so close that they eventually accomplish molecular-level fusion and densification, which endows self-assembled wood with superior mechanical strength (tensile strength ∼ 535.21 MPa, lap shear strength ∼ 5.02 MPa, and solvent stability). This eco-friendly, water-mediated processing technique paves the way for the development of advanced, sustainable, and high-performance wood products.
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".