Formulation‐properties versatility of wood fiber biocomposites based on polylactide and polylactide/thermoplastic starch blends
Bibliographic record
Abstract
This article discusses the interrelation between formulation, processing, and properties of biocomposites composed of a bioplastic reinforced with wood fibers. Polylactide (PLA) and polylactide/thermoplastic starch blends (PLA/TPS) were used as polymeric matrices. Two grades of PLA, an amorphous and a semicrystalline one, were studied. TPS content in the PLA/TPS blends was set at 30, 50, and 70 wt%. Two types of wood fiber were selected, a hardwood (HW) and a softwood (SW), to investigate the effect of the fiber type on the biocomposite properties. Finally, the impact of different additives on biocomposite properties was studied with the purpose to enhance the bioplastic/wood fiber adhesion and, therefore, the final mechanical performance. The biocomposites containing 30 wt% of wood fibers were obtained by twin‐screw extrusion. The properties of the biocomposites are described in terms of morphology, thermal, rheological, and mechanical properties. Furthermore, the biocomposites were tested for humidity and water absorption and biodegradability. An almost 100% increase in elastic modulus and 25% in tensile strength were observed for PLA/wood fiber biocomposite with the best compatibilization strategy used. The presence of the TPS in the biocomposites at 30 and 50 wt% maintained the tensile strength higher or at least equal as for the virgin PLA. These superior tensile results were due to the inherent affinity between the matrices and wood fibers improved by the addition of a combination of coupling and a branching agent. In addition to their outstanding mechanical performance, the biocomposites showed high biodegradation within 60 days. POLYM. ENG. SCI., 54:1325–1340, 2014. © Her Majesty the Queen in Right of Canada 2013
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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) | 0.000 | 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 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".