Study of compostable behavior of jute nano fiber reinforced biocopolyester composites in aerobic compost environment
Bibliographic record
Abstract
Abstract Jute nano fiber (JNF) reinforced biocopolyester‐based composite sheets were prepared with 2% and 10 wt % filler loading and compostability tests were performed in simulated aerobic compost environment at ambient temperature for a period of 50 days. Weight loss study revealed that the incorporation of JNF enhanced the rate of degradation significantly. The unreinforced sample exhibited a steady loss in weight, whereas, the JNF reinforced samples showed three phase degradation. They had a steady weight loss up to 30 days followed by a plateau zone between 30 and 40 days and after that, there was again an increase in weight loss up to 50 days. The biodegraded samples were investigated for their change in molecular weight by Gel Permeation Chromatography (GPC). The change in structure was examined by Differential Scanning Calorimetry (DSC) and morphological change was observed by Scanning Electron Microscopy (SEM). Molecular weight study revealed the fact that Biocopolyester molecules had a significant breakdown in chain length during melt mixing with 10 wt % JNF, which was much less predominant in 2 wt % JNF loaded composites. Such a decrease in chain length and presence of 10 wt % JNF might have facilitated the biodegradation process resulting in highest weight loss. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012
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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".