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Record W2321091595 · doi:10.1021/sc500255n

Development of Industrial Extractants into Functional Ionic Liquids for Environmentally Friendly Rare Earth Separation

2014· article· en· W2321091595 on OpenAlexafffund
Xiaoqi Sun, Kristian E. Waters

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSaponificationChemistryEnvironmentally friendlyIonic liquidExtraction (chemistry)YttriumBifunctionalNitric acidRare earthInorganic chemistryOrganic chemistryMineralogyCatalysis

Abstract

fetched live from OpenAlex

Rare earth elements (REEs) are critical materials in many cutting-edge technology products. Di(2-ethylhexyl)phosphate (HDEHP) and 2-ethyl(hexyl) phosphonic acid mono-2-ethylhexyl ester (HEH[EHP]) are the most commonly used industrial extractants in individual REE separation. However, acidic extractants, such as HDEHP and HEH[EHP], must be saponified for REEs separation, which often releases millions of tons of saponification wastewater into the environment annually. To develop effective and environmentally friendly extraction protocols for the REE separation industry, HDEHP and HEH[EHP] were prepared as acid–base coupling bifunctional ionic liquid extractants, and their extraction behavior and stripping properties for REEs were investigated.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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

Citations92
Published2014
Admission routes2
Has abstractyes

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