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Record W6967026508 · doi:10.48336/5cs7-7s60

Mass transfer resistance of CuCl₂ hydrolysis in a fixed bed reactor

2023· article· en· W6967026508 on OpenAlexaff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2023
Typearticle
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMass transferDiffusionReaction rateSphericityParticle sizeParticle (ecology)Mass transfer coefficientAnalytical Chemistry (journal)

Abstract

fetched live from OpenAlex

The hydrolysis reaction of the Copper-Chlorine (Cu-Cl) cycle is examined in this research to investigate corresponding reaction kinetics with respect to mass transfer resistance through an experimental approach. The experiment was operated at a temperature of 390 °C at atmospheric pressure. The reaction is heterogeneous in which solid reactant CuCl₂ and gaseous reactant H₂O produce Cu₂OCl₂ and HCl. The heterogeneous behaviour of the reaction causes resistance to mass transfer of gaseous reactant H₂O. The resistance in internal diffusion and a surface reaction with mass transfer were analyzed with respect to the initial solid reactant particle size using a shrinking core model (SCM). The results present the thermophysical property of the reaction rate coefficient 0.201 65 s⁻¹ for a particle size of 620 μm and sphericity of 0.68. The experimentally determined reaction and conversion rates of hydrolysis with respect to time are presented, which are experimentally calculated parameters. Scanning Electron Microscopy (SEM) and X-Ray Diffraction (XRD) analysis were used for more accurate results. An uncertainty analysis for the sensors and transducers of the experiment shows that the experimental results have an uncertainty of ±30.1%.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.225
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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