Current overview of carbon fiber: Toward green sustainable raw materials
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lignin, as a potential precursor of carbon fiber, has the characteristics of abundant reserves, renewable and high carbon content, and its application in the preparation of carbon fibers has substantial cost advantages if some important processing and quality hurdles can be overcome. This paper reviews the preparation process of lignin-based carbon fibers, and moreover, describes the characteristics of carbon fiber prepared by different precursors compared with the presently used precursors. Three preparation methods for lignin-based carbon fibers are introduced: melt spinning, solution spinning, and electrospinning. The applicability, advantages, and disadvantages of the three preparation methods are analyzed from the aspects of process conditions and performance characteristics. Possible directions for future research are considered, with the goal of providing a reference for further study of lignin-based carbon fibers.
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.
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 it