Novel Ni‐Ga alloy based catalyst for converting CO<sub>2</sub> to methanol
Bibliographic record
Abstract
Abstract Novel and advanced catalysts based on Ni‐Ga alloy were prepared through co‐condensation method with and without evaporation of water solvent for converting CO2 to methanol. The co‐condensations used Ni(NO3)2 and Ga metal as beginning precursors under alkaline media. Various Ni/Ga molar ratios and temperature of the co‐condensation‐evaporation method were investigated in order to obtain Ni5Ga3 alloy composition as active phase for the catalysts. The results confirmed that the stoichiometry of 5/3 could be reached at the same molar ratio of the beginning precursors, and the suitable temperature of the method was 80 °C for a certain time of 24 h. The Ni‐Ga based catalyst activity and selectivity were also tested in the conversion of CO2 to methanol at atmospheric pressure and 220 °C for different periods of time. The results showed that the catalyst was an excellent candidate for this process compared to other catalysts when exposing good selectivity over 90 % during long periods of time. Many techniques were used including X‐Ray Diffraction (XRD), Thermogravimetric Analysis (TGA), X‐Ray Photoelectron Spectroscopy (XPS), Nitrogen Adsorption–Desorption Analysis (BET), and Gas Chromatography (GC) to characterize the catalyst structure and the reaction performance, respectively.
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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) | 0.000 | 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 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".