Dynamic postpolymerization of 3D‐printed photopolymer nanocomposites: Effect of cellulose nanocrystal and postcure temperature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Cellulose nanocrystal (CNC) reinforced methacrylate (MA) resin nanocomposite was prepared by 3D stereolithography printing. A postcure process, where the printed nanocomposite was heat‐treated under different temperatures, was applied to improve the property of the printed nanocomposites. To investigate the effect of CNC and postcure temperature on the kinetic behavior of the postpolymerization of printed nanocomposites, Fourier‐transform infrared spectroscopy and differential scanning calorimetry measurement of the printed nanocomposites before and after postcure were analyzed. The postpolymerization of MA nanocomposites was promoted at a postcure temperature of 140 °C for the printed 0.5% CNC/MA nanocomposites compared to the printed MA resin. The addition of CNC retarded the polymerization of MA resin during 3D printing, resulting in poorer mechanical properties of the printed nanocomposites compared to the printed MA resin. However, after postcure, the mechanical properties of the printed nanocomposites were improved by the postpolymerization of the MA nanocomposites. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2018 , 56 , 935–946
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it