CO<sub>2</sub>‐induced crystallization of polylactide and its self‐templating ‘stack of coins’ crystalline microstructure
Bibliographic record
Abstract
Can we learn from biomineralization process of natural materials to fabricate a three‐dimensional (3D) thick laminate microstructure by stacking of two‐dimensional (2D) crystalline structure? By adopting this self‐organization principle of biomineralization process, a polymer is crystallized two‐dimensionally into a multi‐layered architecture. Herein, we demonstrate a 2D crystallization method of polylactide and its principle of self‐organization to develop the discontinuous laminate microstructures. We find that instead of building a multilayered morphology layer‐by‐layer, the lamellar microstructures can be built in one step by using self‐organization principle of 2D crystallization. The biopolymer PLA is compression molded, and the molded samples are crystallized by using supercritical CO2 in a high pressure vessel. The CO2‐induced crystallization has a unique diffusion‐controlled crystallization mechanism, which tends to produce a disc‐shape spherultic structure. From microscopy analysis, we observe that these 2D spherulites are self‐organizing in nature and form 3D thick laminate structures with integrated amorphous phase in between. The obtained discontinuous laminate microstructure is comparable to “stack of coins” structure and we report the biomimetic approach of crystallization process. Thus, our study shows an innovative approach to engineer the crystalline microstructure of PLA. POLYM. ENG. SCI., 57:365–373, 2017. © 2016 Society of Plastics Engineers
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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".