Nickel carbonyl formation in a fluidized bed reactor: experimental investigation and modeling
Bibliographic record
Abstract
Abstract BACKGROUND The Mond process has been used in the industry for nickel purification over a century. However, theoretical studies on this process are few and primarily based on empirical models. In this article, experimental and theoretical modeling of nickel tetracarbonyl formation through the Mond process under different conditions in a fluidized bed reactor is presented. Nickel tetracarbonyl, known primarily as nickel carbonyl gas, is formed through the reaction between nickel powder and carbon monoxide. The apparent reaction rate is modeled as a function of reaction temperature, inlet gas pressure, and carbon monoxide flow rate. Experimental results were obtained using a fluidized bed reactor. A diffusion‐kinetics and a two‐phase bubbling bed model were developed to compare with experimental results. The reactor is considered as a differential flow reactor for the theoretical modeling. RESULTS Rate of reaction is measured in a fluidized bed and used for the verification of the studied models. The best performing model is a kinetic‐diffusion model with a rate of reaction that obeys r em = K em ([ CO ]) n , in which K em is a function of mass transfer as well as kinetic variables, but is primarily temperature dependent. Also, n for low‐pressure and high‐pressures regions is −1 and −3, respectively. CONCLUSIONS The reaction rate is strongly dependent on carbon monoxide gas pressure. The models developed are rather simple yet provide significant improvement in predictions of the reaction rate compared to the existing models in the literature. © 2020 Society of Chemical Industry
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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 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".