Analysis of the Water Adsorption Isotherms in UiO-Based Metal–Organic Frameworks
Bibliographic record
Abstract
The present work takes a detailed look at the adsorption of nitrogen gas and water vapor in six related zirconium-based metal–organic frameworks (UiO-66, UiO-66-NH 2, UiO-67, UiO-67-NH 2, UiO-68-Me 4 /PCN-57, and UiO-68-NH 2 ). The work relates the role of defects, linker length, and linker functionality to the gas adsorption properties. The water adsorption isotherms showed no hysteresis consistent with capillary condensation. This suggests a node-based cluster growth mechanism is occurring. Analysis of the water adsorption isotherms illustrated that, prior to the water condensation step in the isotherm, each MOF adsorbed roughly one water molecule per zirconium center. As the linker length increases, the MOF becomes more hydrophobic. The amine functionality increases the hydrophilicity, but the effect of the functional group diminishes as the linker length increases. The latter point is illustrated by calculating the apparent contact angle between the pore wall and condensed water. The apparent contact angle increased from 54.0 to 83.1° from UiO-66 to UiO-68-Me 4 /PCN-57 and from 13.0 to 71.0° from UiO-66-NH 2 to UiO-68-NH 2 . From this, the water isotherm was used to construct a pore size distribution consistent with the distribution determined from nitrogen gas adsorption. We further explored the amine-unfunctionalized MOFs for long-term water vapor exposure. Below the water condensation step, the MOFs showed no change in nitrogen gas adsorption capacity/surface area for 100 days.
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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 | 0.000 |
| 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".