A method for preparing epoxy-cellulose nanofiber composites with an oriented structure
Bibliographic record
Abstract
A method was developed for processing cellulose nanocomposites using conventional vacuum infusion. Porous cellulose nanofiber networks were prepared via ice-templating and used as preforms for impregnation with a bio-epoxy resin. Microscopy studies showed a unidirectionally oriented micrometer-scale pore structure that facilitated the infusion process by providing flow channels for the resin. The permeability of the preforms was comparable to that of natural fiber mats, and the infusion time significantly decreased after optimizing the processing temperature. The flexural modulus of the bio-epoxy increased from 2.5 to 4.4 GPa, the strength increased from 89 to 107 MPa, and the storage modulus increased from 2.8 to 4.2 GPa with 13 vol% cellulose nanofibers. The mechanical properties also showed anisotropy, as the flexural and storage moduli were approximately 25% higher in the longitudinal direction, indicating that the nanofiber network inside the epoxy matrix had an oriented nature.
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 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) | 0.001 | 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".