The Effect of Zn on Offretite Zeolite Properties. Acidic Characterizations and NH<sub>3</sub>-TPD Desorption Models
Bibliographic record
Abstract
This article reports the effect of adding zinc to an offretite (OFF) zeolite. It is observed that zinc addition does not significantly change the specific surface area, the pore volume, or the pore size distribution. It is noticed, however, that zinc addition influences acid properties of the OFF significantly. For instance, when employing FTIR pyridine adsorption, it is observed that in the Zn-OFF, there are 2.5 times higher Lewis acid sites than Brönsted acid sites. Furthermore, when applying NH 3 -TPD, three acid sites were identified: (a) abundant number of weak acid sites, (b) fair number of moderate acid strength sites, and (c) scarce number of strong acid sites. Furthermore, NH 3 desorption kinetic parameters were also calculated. Two numerical methodologies, linear and nonlinear regression, were implemented. It was noticed that E d augments with zinc as E d for OFF < E d for Zn(2.0 wt %)-OFF < E d for Zn(3.5 wt %)-OFF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".