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Investigating the compatibility of PEEK polymer for the fabrication of sample cells for use in muon spin spectroscopy

2014· article· en· W1978932390 on OpenAlexaff
Lalangi Chandrasena, Iain McKenzie, Mina Mozafari, Stephen P. Cottrell, Paul W. Percival

Bibliographic record

VenueJournal of Physics Conference Series · 2014
Typearticle
Languageen
FieldEngineering
TopicMuon and positron interactions and applications
Canadian institutionsTRIUMFSimon Fraser University
Fundersnot available
KeywordsMuon spin spectroscopyCompatibility (geochemistry)PeekFabricationMaterials sciencePolymerSpectroscopyMuonNanotechnologyNuclear magnetic resonancePhysicsNuclear physicsComposite materialMedicine

Abstract

fetched live from OpenAlex

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 μSR have been constructed from PEEK. Muon levelcrossing resonance (μLCR) studies of PEEK revealed a broad, strong μLCR 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-μSR) and μLCR. Two different muoniated radicals were formed by Mu addition to 4,4/- dihydroxybenzophenone and one radical was formed in para-dimethoxybenzene. The μSR 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 μSR experiment.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.549
Threshold uncertainty score0.138

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.287
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2014
Admission routes1
Has abstractyes

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