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Record W4385810208 · doi:10.1021/acs.iecr.3c01547

Separation of Praseodymium and Neodymium from Heavy Rare Earth Elements Using Extractant-Impregnated Surfaces Loaded with 2-Ethylhexyl Phosphonic Acid-mono-2-ethylhexyl Ester (PC88A)

2023· article· en· W4385810208 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2023
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPraseodymiumNeodymiumChemistryExtraction (chemistry)Yield (engineering)SolventLeaching (pedology)LanthanideAdsorptionImpurityInorganic chemistryChromatographyMaterials scienceOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

In the rare earth industry, the next step after leaching and impurity removal is separation. The most common technology for separation is solvent extraction. Although promising, it faces a few challenges including the large consumption of organic solvents, large volumes of waste generation, and the need for multiple stages to achieve the desired separation factor. An alternative approach to solvent extraction is supported-liquid extraction (SLE) in which the extractant phase is supported in place by a solid support media in which the liquid extraction takes place. The main advantages of SLE over solvent extraction are lower solvent consumption and less generation of hazardous waste. Here, an extractant-impregnated surface (EIS) made of a microtextured silicon substrate coated with octadecyltrichlorosilane for hydrophobicity and impregnated with 2-ethylhexyl phosphonic acid-mono-2-ethylhexyl ester (PC88A) is developed to separate praseodymium and neodymium from a mixture of heavy rare earth elements. The possible contact modes including impaled, impregnated, and encapsulated are investigated, and it is found that the impregnated mode can be achieved when 0 < θ es(w) < θ c . The feed contains 10 mg/L of all REEs at pH 2.5. The key separation performance indicators including yield, purity, and separation factor are determined, and the results indicate that the final praseodymium + neodymium purity is 92% with 96% yield, and a separation factor of 171 that is comparable with solvent extraction is achieved. Kinetic studies indicate that the pseudo-second-order kinetic model fits the kinetic data, which means that the adsorption is controlled by chemisorption with an activation energy of 69.3 kJ mol –1 . Thermodynamic studies indicate that the adsorption process of the studied REEs on PC88A-EIS is endothermic (Δ H ads = 31.3 kJ/mol). The Gibbs free energy of praseodymium and neodymium is positive, whereas that of heavy rare earth elements is negative (−8.56 kJ/mol), indicating that the heavy rare earth elements’ adsorption on PC88A is spontaneous whereas that of praseodymium and neodymium is not spontaneous. Therefore, the system can selectively separate heavy rare earths over praseodymium and neodymium. Isotherm studies indicate that the Langmuir model better fits the adsorption data, suggesting that the monolayer homogeneous adsorption mechanism is the controlling mechanism. The maximum heavy rare earths’ adsorption amount was found to be 671.4 mg/cm 2, which is comparable to those obtained using functionalized adsorbents. The adsorbed heavy rare earths were eluted with 4.5 M H 2 SO 4, and the EIS was regenerated and reused for several cycles, indicating a cost-effective potential material in real applications.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.083
GPT teacher head0.339
Teacher spread0.256 · 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