Hyperpolarized <sup>129</sup>Xe Nuclear Magnetic Resonance Studies of Isoreticular Metal-Organic Frameworks
Bibliographic record
Abstract
The pore environments of a series of isoreticular metal-organic frameworks (IRMOF) have been studied using hyperpolarized (HP) 129 Xe nuclear magnetic resonance (NMR) spectroscopy. Xenon gas behaved as an efficient probe molecule for interrogating the variability of adsorption sites in functionalized IRMOF materials through variations in the NMR chemical shift of the adsorbed xenon. The xenon adsorption enthalpies extracted from variable-temperature HP 129 Xe NMR were found to be lower than published values for the physisorption of xenon. The low heats of adsorption were corroborated by xenon adsorption measurements that revealed two atoms per pore under one atmosphere of pressure at 19 °C. Average pore diameters estimated from the empirical chemical shift and pore size correlations based on a geometrical model were compared with X-ray crystallography data. The exchange processes of xenon in IRMOFs also were explored using 2D exchange spectroscopy (EXSY) 129 Xe NMR. It was found the exchange of xenon from adsorption sites within the IRMOF to the free gas space is much slower than that between the adsorption sites within the lattice. Cross-polarization experiments showed that the preferred adsorption sites were spatially removed from the phenylene rings of the network. This agrees with previous spectroscopic, structural, and computational studies of gas adsorption (H 2, N 2, Ar) in IRMOFs that indicate the preferred binding sites reside near the carboxylate groups of the inorganic clusters.
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 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 | 0.000 |
| 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) | 0.001 | 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".