Determination of the free-ion concentration of rare earth elements by an ion-exchange technique: implementation, evaluation and limits
Bibliographic record
Abstract
Environmental context The lanthanides are a group of heavy elements (from lanthanum to lutetium) increasingly used in many electronic consumer products and little is known about their environmental mobility and toxicity. In natural systems, these elements will bind to natural organic matter but metal toxicity is usually defined by the free metal ion concentration. Here, we propose a method based on sample equilibration with an ion-exchange resin to measure the free lanthanide ion concentration in the presence of natural organic matter. Abstract An ion-exchange technique that employs a polystyrene sulphonate ion-exchange resin was developed for determining environmentally relevant free-ion concentrations of Ce, Eu, La and Nd. Owing to the high affinity of rare earth elements (REE) for the selected resin, this method requires the addition of an inert salt to increase the concentration of the counter-ions (i.e. cations that are exchanged with REE bound to the resin). The use of a batch equilibration approach to calibrate the resin allowed the implementation of the ion-exchange technique at reasonably low ionic strength (I = 0.1 M). Several ligands were used to test the selectivity of the method, which proved to be highly selective for the free metal ion in presence of the tested cationic and anionic complexes (REE–nitrate, REE–malic acid and REE–nitrilotriacetic acid systems) and operational for very low proportions of REE3+, owing to the strong REE–resin interactions. The ion-exchange technique was also implemented to determine [Eu]inorg in the presence of natural humic matter (Suwannee River Humic Acid) and the results were compared with those obtained using equilibrium dialysis and those calculated with chemical equilibrium models. At pH 4.00, the measured [Eu]inorg values were in fairly good agreement with those predicted with the Windermere Humic Aqueous Model and Stockholm Humic Model, whereas the Non-Ideal Competitive Absorption model appeared to underestimate the [Eu]inorg. However, the inorganic europium concentrations were strongly underestimated (4 < [Eu]inorg, IET/[Eu]inorg, calc < 18) with the three prediction models at higher pH (5.3 and 6.2).
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".