Nickel Aluminum Spinel Derived Ni‐F‐Al Active Site for the Catalytic Dehydrofluorination of Potent Greenhouse Gas 1,1,1,2‐Tetrafluoroethane
Bibliographic record
Abstract
ABSTRACT HFC‐134a (1,1,1,2‐tetrafluoroethane) is one of the most common refrigerants with global warming potential (100 years) of 1300. It is regulated to be phased out gradually according to the Kigali Amendment to the Montreal Protocol. Treatment of this stable chemical poses significant challenge. Highly efficient nickel aluminum spinel catalysts were fabricated by sol–gel method for the catalytic dehydrofluorination of HFC‐134a. The effect of Ni/Al ratio in the NiAl2O4 spinel precursors on the performance of NiAl catalysts was studied by x‐ray diffraction (XRD), Brunauer–Emmett–Teller (BET), scanning electron microscope (SEM), transmission electron microscopy (TEM), NH3‐TPD, and XPS. Nickel–aluminum ratio in the nickel–aluminum spinel precursor plays a major role on the formation of strong acid and active species Ni‐F‐Al. With Ni/Al ratio of 4, the (3 1 1) crystal face of NiAl2O4 interfaced with the (1 1 1) crystal face of NiO and the (4 0 0) crystal face of NiAl2O4. This interaction facilitates the formation of Ni‐F‐Al active species following the dehydrofluorination reaction. Furthermore, the Ni‐F‐Al species altered the acid structure of NiAl catalysts. It was found that NiAl catalyst with a Ni/Al ratio of 4 has the best catalytic performance compared with other catalysts (with conversion of 35%), and no deactivation trend was observed after 50 h of time on stream. (Reaction conditions: N2/CF3CH2F = 10, T = 450°C, GHSV = 660 h−1).
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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".