Determination of Isophthalic Acid Comonomer Content in Poly(Ethylene Terephthalate) (PET) Using Raman Spectroscopy
Bibliographic record
Abstract
Poly(ethylene terephthalate) (PET) is one of the leading polymers in the packaging industry. It is often copolymerized with isophthalic acid (IPA) to tune its properties, yet its comonomer content is not always known. In this work, we develop simple Raman spectroscopy methods to quantify the IPA content of PET samples in the range most used for bottle production without any pretreatment. The calibration curves allow precise quantification of IPA content for amorphous samples (R 2 = 0.997), and good estimates for semicrystalline samples (R 2 = 0.952) and commercial products exhibiting common spectroscopic challenges. This work leverages the speed and accessibility of Raman spectroscopy for solid-state IPA quantification, making it a practical alternative to established techniques.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".