Recycling polyethylene terephthalate – based automotive carpets using chain extenders via reactive extrusion
Bibliographic record
Abstract
Polyethylene Terephthalate (PET) is a common polyester used in various applications, ranging from packaging to clothing. The automotive industry utilizes this material to manufacture the velour carpet mats used in cars, rising environmental legislation surrounding this industry has led to the need of developing a recycling process for these velour carpet trims (Murray, 2017). In order to recycle this material, the challenge of polymer degradation must be addressed. To overcome this issue chain extenders will be used to conduct a reactive extrusion recycling method for this material. Pyromellitic dianhydride (PMDA) and 1,3 – Bis(4,5-dihydro-2-oxazolyl) benzene (PBO) will be synergistically used under reactive extrusion conditions, a twin-screw extrusion process was carried out at 60RPM and evaluated at a temperature range of 265-285°C and various chain extender concentrations. The target of this research paper is meeting the 0.7 dL/g I.V. recycling industry target for PET-based materials. Two design of experiments were utilized in this investigation; the first DOE was tested at a constant 265°C, a PMDA concentration of 5wt% and 3.50wt%, and a PBO concentration of 2.00 wt% and 0.75 wt%. The results from this DOE were used to generate a model that estimated a new optimized zone to evaluate, the second DOE evaluated the extrusion temperature, and chain extender formulation. In this second DOE the extrusion temperature was varied at 265 and 285°C and an optimized formulation was evaluated at a PMDA concentration of 3.50 wt% and 1.75wt%, with a PBO concentration of 2.75wt% and 1.00 wt%. Main parameter evaluated was the intrinsic viscosity and the conditions that yielded the highest I.V. value, 1.036 dL/g, was extruded at 285°C with a PMDA concentration of 3.0wt% and PBO at 1.00 wt%. The Mark-Houwink equation was then used to estimate the molecular weight of this material yielding an Mw of 83, 082. While the results obtained in this work met the goal of 0.70 dL/g, the formulation could still be further optimized to 3.0wt% PMDA, 0.05wt% PBO and 285°C to increase the I.V. to 1.20 dL/g.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".