Characterization of the Mechanical, Biodegradation, and Morphological Properties of NBR/Biopolymer Blend, Integrated with a Risk Evaluation
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Biopolymer blends have attracted considerable attention in industrial applications due to their notable mechanical properties and biodegradability. This work delves into the innovative combination of butadiene-acrylonitrile (referred to as NBR) with a pectin-based biopolymer (NGP) at a 90:10 mass ratio through a detailed analysis employing mechanical characterization, Fourier transform infrared (FTIR) analysis, thermogravimetric analysis (TGA), and morphology studies using SEM. Additionally, biopolymer’s biodegradability under aerobic and anaerobic conditions is tested. The study’s findings underscore the superior tensile strength and elongation at break of the NGP/NBR blend in comparison to pure NBR, while also exhibiting a decrease in puncture resistance due to imperfect bonds at the particle–matrix interfaces, necessitating the use of a compatibilizer. In anaerobic conditions, evaluation of biodegradable properties reveals 2% and 12% biodegradability in NBR and NGP/NBR blend, respectively. The degradation properties were also aligned with TGA results highlighting a lower decomposition temperature for NGP. Additionally, this research integrates the application of a conditional value-at-risk (CVaR)-based analysis of the blend’s tensile properties to evaluate the uncertainty impact in the experiment. Under risk, a significant enhancement in the tensile performance (by 80%) of the NGP/NBR blend was shown compared to pure NBR. Ultimately, the study shows that adding pectin to the NBR compound amplifies the overall performance of the biopolymer significantly under select criteria.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".