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Record W3018770225 · doi:10.1002/jctb.6452

Nickel carbonyl formation in a fluidized bed reactor: experimental investigation and modeling

2020· article· en· W3018770225 on OpenAlexafffund
Seyed Foad Aghamiri, Amin Ghobeity

Bibliographic record

VenueJournal of Chemical Technology & Biotechnology · 2020
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsSheridan College
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCarbon monoxideFluidized bedNickelReaction rateThermodynamicsChemistryDiffusionChemical kineticsMaterials scienceKineticsCatalysisOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.234
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes2
Has abstractyes

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