Coprecipitation of Nickel−Copper−Aluminum Takovite as Catalyst Precursors for Simultaneous Production of Carbon Nanofibers and Hydrogen
Bibliographic record
Abstract
A series of nickel-, copper-, and aluminum-containing catalysts at a (Ni+Cu)/Al mole ratio of 3 and Cu/Ni mole ratio in the range of 0.03−0.4 was prepared by coprecipitation from corresponding metal nitrate solutions at alkaline pH. The composition and structure of the precipitates were determined by chemical analysis, thermogravimetric analysis (TGA), and X-ray diffraction (XRD). The XRD patterns confirmed that the precipitates are of hydrotalcite-like structures and, more specifically, they are takovite. The brucite-like layers consist of nickel, copper, and aluminum ions of composition [Cu y Ni x - y Al 1 - x (OH) 2 ] (1 - x )+, while the interlayers consist of CO 3 2- and crystalline water. The observed variation of lattice parameters with copper content led us to conclude that the copper and aluminum ions were randomly substituted for the nickel ions in the brucite layer. The catalytic conversion tests at 670 °C showed a significantly enhanced catalytic reactivity of 2 mol % copper-doped catalysts as compared to a pristine nickel catalyst. A higher copper doping led to a less significant improvement in catalytic reactivity. A scanning electron micrograph (SEM) confirmed the production of carbon nanofibers.
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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".