Influence of Graphene Oxide on Thermally Induced Shape Memory Behavior of PLA/TPU Blends: Correlation with Morphology, Creep Behavior, Crystallinity, and Dynamic Mechanical Properties
Bibliographic record
Abstract
Abstract In this study, shape memory is thermally induced in a series of graphene oxide (GO) filled poly(lactic acid)/thermoplastic polyurethane (PLA/TPU) blends, prepared via melt mixing process, and their shape recovery and shape fixity are measured, and the results are correlated with morphology, dynamic mechanical properties, crystallinity and creep recovery behavior. Morphological analysis by scanning and transmission electron microscopy reveals that the blends are immiscible, and GO platelets are mainly localized in the TPU phase of the blends, which lead to smaller and more elongated TPU droplets with improved interfacial adhesion being responsible for the improved shape recovery performance compared to the unfilled blend. A systematic enhancement found in storage and Young's modulus, tensile strength, creep resistance and creep recovery, and cold crystallinity as a result of GO inclusion are in agreement with the improved shape recovery, shape fixity and overall shape memory performance of the filled systems. The developed PLA/TPU/GO nanocomposites with highly improved mechanical properties can be utilized as a new class of environmentally friendly shape memory materials for a broad range of applications.
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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".