Characterization of electrospun lignin based carbon fibers
Bibliographic record
Abstract
The production of lignin fibers has been studied in order to replace the need for petroleum based precursors for carbon fiber production. In addition to its positive environmental effects, it also benefits the economics of the industries which cannot take advantage of carbon fiber properties because of their high price. A large amount of lignin is annually produced as the byproduct of paper and growing cellulosic ethanol industry. Therefore, finding high value applications for this low cost, highly available material is getting more attention. Lignin is a biopolymer making about 15 – 30 % of the plant cell walls and has a high carbon yield upon carbonization. However, its processing is challenging due to its low molecular weight and also variations based on its origin and the method of separation from cellulose. In this study, alkali solutions of organosolv lignin with less than 1 wt/v% of poly (ethylene oxide) and two types of lignin (hardwood and softwood) were electrospun followed by carbonization. Different heating programs for carbonization were tested. The carbonized fibers had a smooth surface with an average diameter of less than 5 µm and the diameter could be controlled by the carbonization process and lignin type. Scanning electron microscopy (SEM) was used to study morphology of the fibers before and after carbonization. Thermal conductivity of a sample with amorphous carbon was 2.31 W/m.K. The electrospun lignin carbon fibers potentially have a large range of application such as in energy storage devices and water or gas purification systems.
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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".