Effect of Pretreatment on Physicochemical Properties and Performance of Multiwalled Carbon Nanotube Supported Cobalt Catalyst for Fischer–Tropsch Synthesis
Bibliographic record
Abstract
The influence of different nitric acid concentrations (35, 50, 70 wt %) on the physicochemical properties of multiwalled carbon nanotube was investigated. 15 wt % cobalt was impregnated on acid treated nanotubes. The corresponding catalysts were characterized by BET, XRD, Raman, SEM, TEM, TPR, CO chemisorption techniques to further study the impact of acid functionalization on textual properties, metal dispersion, crystallite size, defect generation, and reducibility of 15Co/CNT catalysts. The performance of prepared catalysts was tested for 30% CO and 60% H 2 with balanced Ar in a fixed bed microreactor for Fischer–Tropsch synthesis at 220 °C, 2 MPa, and GHSV of 3000 cm 3 ·g –1 ·h –1 . Pretreatment of CNTs with 70 wt % nitric acid exhibited improved physicochemical properties of 15Co/CNT catalyst and hydrocarbon yield by 35% as compared to untreated CNT supported catalyst.
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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".