In Situ Cellulose Nanocrystal-Reinforced Glycerol-Based Biopolyester for Enhancing Poly(lactic acid) Biocomposites
Bibliographic record
Abstract
Abstract Biobased, elastomeric polymer poly(glycerol succinate-co-maleate) (PGSMA) was produced using a “green” synthesis with added cellulose nanocrystals (CNCs) to create a novel PGSMA–CNC material. PGSMA–CNC was synthesized with the aim of developing a new strategy for successfully dispersing CNCs within a poly(lactic acid) (PLA) matrix for optimal reinforcement of tensile strength and modulus while having the added benefit of the proven toughness enhancements of PLA/PGSMA blends. Optical microscopy and fractionation in tetrahydrofuran showed that CNCs agglomerated during PGSMA–CNC synthesis and remained in agglomerates during PLA/PGSMA–CNC reactive blending. Fourier transform infrared, differential scanning calorimetry, and dynamic mechanical analyses also showed that PGSMA–CNC inhibited the formation of PGSMA crosslinks and PLA-g-PGSMA during reactive blending. These two effects resulted in loss of impact strength and only a 4% increase in tensile modulus over PLA/PGSMA at the highest CNC content. Further work in preventing CNC aggregation could help improve mechanical properties of the final blend.
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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".