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)
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".