Recycled Carbon Black/High-Density Polyethylene Composite from Waste Tires: Manufacturing, Testing, and Aging Characterization
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
This study addresses the global issue of recycling used vehicle tires, typically burned out or trimmed to be reused in playground floors or road banks. In this study, we explore a novel environmentally responsive approach to decomposing and recovering the carbon black particles contained in tires (25–30 wt.%) by vacuum pyrolysis. Given that carbon black is well known for its UV protection in plastics, the objective of this research is to provide an ecological alternative to commercial carbon black of fossil origin by recycling the carbon black (rCB) from used tires. In our research, we create a composite material using rCB and high-density polyethylene (HDPE). In this article, we present the environmental aging studies carried out on this composite material. The topographic evolution of the samples with aging and the oxidation kinetics of the surface and through the thickness were studied. The Beer–Lambert law is used to relate the oxidative index to the characteristic depth of the samples. The UV photons are observed to penetrate up to 54% less with the addition of 6 wt.% of rCB compared to virgin HDPE. In this work, the addition of rCB as filler for HDPE used for outdoor applications has demonstrated to be an antioxidant for UV protection and a good substitute for commercial carbon black for industrial goods.
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) | 0.000 | 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 it