Acrylonitrile–butadiene rubber reinforced by graphene oxide/halloysite nanotubes hybrid nanofillers through mechanical blending method
Bibliographic record
Abstract
With the idea of improving the mechanical properties of acrylonitrile–butadiene rubber (NBR) for potential industrial application, hybrid nanofillers prepared by hybridizing graphene oxide (GO) with halloysite nanotubes (HNT), were incorporated through mechanical blending to reinforce NBR. Graphene oxide/halloysite nanotubes (GH) hybrid filler demonstrates significant synergetic reinforcement effect in mechanical properties of NBR. The substantial improvement in mechanical properties is attributed to the uniform dispersion of hybrid filler in the matrix and to the strong interaction between the hybrid filler and matrix. Scanning electron microscopy images obtained from the fractured surface of GH-reinforced NBR composites showed more uniform dispersion with less agglomerations and cracks than that of GO and HNT. The strong interaction between the hybrid filler and NBR was confirmed by the increase of glass transition temperature, storage modulus and crosslinking density.
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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".