Thermal Analysis of Highly Filled Composites of Polystyrene with Lignin
Bibliographic record
Abstract
This paper focuses on the thermal properties of polystyrene/lignin composites over a wide range of lignin content. Blending with and without a compatibilizer (styrene/ethylene/butylene copolymer) was performed in an internal batch mixer to prepare samples between 0 and 80%wt of lignin. From the compounds, an extensive thermal study was performed, including thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and dynamic mechanical thermal analysis (DMTA). TGA results indicated that the thermal stability of polystyrene increases with increasing lignin content. DMTA analysis showed higher storage modulus and lower loss factor with increasing lignin content for the range of temperature studied (30-150 °C). DSC results showed that the lignin/PS composites have a single T g which is close to that of polystyrene. The addition of a compatibilizer up to 2%wt was found to improve the storage modulus of lignin/PS composite, especially at low temperature. Finally, scanning electron microscopy micrographs were used to show the state of interfacial adhesion or compatibility between lignin particles and the polystyrene matrix.
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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 | 0.000 |
| 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".