Impact of particle size and associated minerals on rare earth desorption and incorporation mechanisms in a South American ion-adsorption clay
Bibliographic record
Abstract
This research delves into the intricate nexus of particle size, mineralogical composition, surface attributes, elemental mapping, and rare earth element (REE) adsorption mechanisms within an ion-adsorption clay sample from South America. The investigation entails the fractionation of the ion-adsorption clay into three size categories: S1 (< 0.25 mm), S2 (0.25-0.5 mm), and S3 (0.5-2 mm). Each fraction undergoes meticulous characterization to unveil its elemental composition, mineralogical composition, surface area, morphological characteristics, elemental mapping, and the mechanisms governing REE incorporation. The results indicate that S1 has 31% physiosorbed, 8% chemisorbed, and 61% mineralized REEs, while S2 has 40% physiosorbed, 5% chemisorbed, and 55% mineralized REEs, and S3 has 24% physiosorbed, 5% chemisorbed, and 71% mineralized REEs. The physisorbed REEs are attributed to the presence of kaolinite, conducive to mostly physisorption. In terms of grain size and REE content/type relationship, the results show that REE content decreases with increasing grain size; however, there is not a clear trend in terms of REE occurrence modes with grain size. Heavy rare earth elements (HREEs) are discernibly favored in adsorption over light rare earth elements (LREEs). This preference is underpinned by the weathering processes that led to the formation of ion-adsorption clay, which facilitated the transport and accumulation of HREEs. Notably, the ion-adsorption clay encompasses a substantial content of mineralized REEs, necessitating more demanding extraction methodologies, such as acid baking followed by water leaching if complete extraction of all REEs is desired. Among the desorbable REEs, physisorption dominates, encompassing over 80% of the total. Chemisorbed REEs exhibit versatility in association with various minerals, encompassing kaolinite, quartz, and goethite. In essence, this study unveils the intricate interplay between particle dimensions, mineralogical constitution, surface attributes, and REE adsorption modes within this ion-adsorption clay sample. The ion-adsorption clay in this study contains a significant portion of mineralized REEs that cannot be extracted using the mild conditions typically employed for the desorption process. Additionally, the REE concentration in this ion-adsorption clay is notably higher than the average found in clay deposits worldwide, reaching levels comparable to those of regolith deposits in China, which are a major global source of REEs. This remarkable concentration of REEs, along with the unique modes of their occurrence in this deposit, presents a significant interest to the scientific community.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".