Hydrogenation of Carbon Monoxide and Carbon Dioxide over Nano γ-Alumina Supported Cobalt (III)/Molybdenum Catalyst
Classification
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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ligated dicobalt (III) heptamolybdate (CoL6)2(Mo7O24) multitransition-metal complex was prepared. This complex was deposited evenly on nano γ-alumina catalyst support. The partial reduction of cobalt (III)/ molybdate pre-catalyst was performed in a batch reactor with hydrogen gas at a pressure of 20 bars and temperature of 873oK for 5 hours. The catalyst was characterized using FTIR, XRD, BET and TEM. The nano cobalt (III)/molybdenum catalyst was employed for hydrogenation reaction of carbon monoxide and carbon dioxide. The assessment of the catalyst was carried out at different temperature over a pressure range of 10-50 bars with various H2/CO ratios. This catalyst was found to be active, and stable for usage at high temperature and moderate pressure. The catalyst gave an excellent conversion of carbon monoxide to hydrocarbons (95%); it also converted 78% of carbon dioxide to carbon monoxide (73) and methane (5%). TEM image demonstrated catalyst has nearly spherical morphology with the average particle size of 46.86 nm.Keywords: complex, carbon monoxide, Carbon dioxide, multitransition-metal, surface modified nano catalyst
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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 | 0.000 |
| 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 it