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Record W6961283194 · doi:10.14288/1.0431368

Kinetic investigation of rare earth leaching on Labrador Canada rare earth ore in acidic sulphate medium

2023· article· en· W6961283194 on OpenAlexaboutno aff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLeaching (pedology)Kinetic energyParticle sizeRare earthPorosityKineticsDiffusionSulfuric acid

Abstract

fetched live from OpenAlex

The kinetics of sulphuric acid leaching of rare earth elements in a sample from the Foxtrot deposit in Labrador, Canada was investigated. The selected parameters were, particle size fraction of +38 –53 µm, +53 -75 µm, +75 -106 µm, and +106 -150 µm, sulphuric acid concentration of 0.5 M, 1.5 M and 3 M, temperature of 30, 60, and 90 ℃. The highest extraction efficiency for Ce, Nd and Y was 96.72%, 84.91% and 72.83%, respectively at the highest temperature, highest sulphuric acid concentration and smallest particle size fraction. The highest selectivity was achieved at +106 -150 μm, temperature of 90 ℃, and sulphuric acid concentration of 0.5 M. It was determined that the kinetic experimental data followed the Jander product layer diffusion kinetic model, a type of shrinking core model, for all three elements. The activation energies for Ce, Nd, and Y were found to be 56.19 kJ/mol, 57.09 kJ/mol, and 38.57 kJ/mol, respectively. After identifying the most suitable kinetic model and calculating the activation energies, the rate orders were calculated for the mathematical model. These values were used to develop semi-empirical mathematical models for each element. The results showed that Y was the least affected by acid concentration and particle size, while Ce and Nd were the most affected. The acid leaching process resulted in crack and porosity formation for certain minerals but no notable change in particle size which is in a good agreement with the Jander kinetic model. The high activation energies with product layer diffusion control suggested that a mixed kinetic model might be in control of the leaching mechanism.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.196
Teacher spread0.182 · 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 designObservational
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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