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Record W4415588124 · doi:10.1021/acs.iecr.5c03555

Chelation Assisted Electrodialysis as a Practical Alternative to the SX-5 Stage for Separating (Tb, Dy) from (Sm, Eu, Gd)

2025· article· en· W4415588124 on OpenAlexafffund
Lingyang Ding, Gisele Azimi

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2025
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrodialysisSelectivitySolubilityProcess (computing)Separation processChelationMembranePrecipitation

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide This study demonstrates a chelation-assisted electrodialysis (CAED) process using DCTA as a potential solvent-free alternative to the SX-5 stage in rare earth element (REE) separation. The process was evaluated using synthetic feed solutions representative of the middle-to-heavy REE fraction, and its performance was compared with that of the conventional EDTA-assisted system. DCTA exhibited superior selectivity and faster precipitation kinetics, leading to improved separation performance under controlled laboratory conditions. A phenomenological model was developed, experimentally validated, and applied to identify an optimal operation window, providing insight into ion transport behavior and stage-wise selectivity trends. While DCTA offers clear chemical advantages, practical factors such as its higher cost, solubility limits, and recycling requirements remain important considerations for scale-up. The CAED approach demonstrated the potential to reproduce the SX-5 separation step while eliminating organic solvent use, offering a pathway toward more sustainable REE separation processes.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.191
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.132
GPT teacher head0.432
Teacher spread0.301 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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