Investigating the compatibility of PEEK polymer for the fabrication of sample cells for use in muon spin spectroscopy
Bibliographic record
Abstract
Polyether ether ketone (PEEK) is a thermoplastic polymer with a wide range of applications due to its chemical inertness and thermal stability, and for these reasons sample cells for gas and liquid phase μ SR have been constructed from PEEK. Muon levelcrossing resonance ( μ LCR) studies of PEEK revealed a broad, strong μ LCR signal that, we hypothesize, is due to multiple overlapping resonances from the various muonium (Mu) adducts of PEEK. To investigate this, two monomer units from PEEK (4,4'-dihydroxybenzophenone and para -dimethoxybenzene) were studied in solution using transverse-field muon spin rotation (TF- μ SR) and μ LCR. Two different muoniated radicals were formed by Mu addition to 4,4 / - dihydroxybenzophenone and one radical was formed in para -dimethoxybenzene. The μ SR spectra were assigned by comparing the experimentally measured muon and proton hyperfine coupling constants with values calculated for the possible structures using Gaussian-09 software with the B3LYP functional and 6-31G basis set. Good agreement was found for cyclohexadienyl- type radicals formed by Mu addition to the benzene rings of the monomer units. We can also infer that these radicals are being formed in PEEK, and based on this we conclude that sample cells made of PEEK are unsuitable for many types of μ SR experiment.
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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 | 0.000 | 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) | 0.002 | 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".