Rare Earth Element Adsorption to Clay Minerals: Mechanistic Insights and Implications for Recovery from Secondary Sources
Bibliographic record
Abstract
The energy transition will have significant mineral demands and there is growing interest in recovering critical metals, including rare earth elements (REE), from secondary sources in aqueous and sedimentary environments. However, the role of clays in REE transport and deposition in these settings remains understudied. This work investigated REE adsorption to the clay minerals illite and kaolinite through pH adsorption experiments and extended X-ray absorption fine structure (EXAFS). Clay type, pH, and ionic strength (IS) affected adsorption, with decreased adsorption under acidic pH and elevated IS. Illite had a higher adsorption capacity than kaolinite; however, >95% adsorption was achieved at pH ∼7.5 regardless of IS or clay. These results were used to develop a surface complexation model with the derived binding constants used to predict REE speciation in the presence of competing sorbents. This demonstrated that clays become increasingly important as pH increases, and EXAFS modeling showed that REE can exist as both inner- and outer-sphere complexes. Together, this indicated that clays can be an important control on the transport and enrichment of REE in sedimentary systems. These findings can be applied to identify settings to target for resource extraction or to predict REE transport and fate as a contaminant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".