A Polymer NMR Cell for the Study of High-Pressure and Supercritical Fluid Solutions
Bibliographic record
Abstract
Nuclear magnetic resonance (NMR) offers researchers unique, highly localized molecular information. The importance of this technique is well established in studies using chemical shift, spin coupling, and relaxation times providing detailed structural information, determining chemical equilibria and kinetics, and understanding molecular dynamic processes. However, the widespread application of NMR spectroscopy to high-pressure liquids and supercritical fluids has been limited due to the complexity of the necessary instrumentation. One approach to these studies is to build a dedicated high-pressure probe. Another involves the utilization of a high-pressure cell designed to fit in commercially available probes. Here we present the design and implementation of a simple, three-piece, high-pressure NMR cell constructed of high-performance polymers. The present cell has pressure capabilities of up to 400 bar; however, the ultimate temperature and pressure limits will be determined by the specific polymer chosen. High-resolution NMR spectra of methanol modified and tributyl phosphate (IBP) modified supercritical CO2 are presented. An example of supercritical fluid phase behavior monitored with NMR is demonstrated for the TBP system in which the chemical shift changes in the 31P nucleus as a function of density are indicative of solution phase separation. The multinuclear NMR data demonstrate the utility of this cell for studying supercritical fluid solution systems relevant to analytical separations and extractions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".