A Quantitative Metric for the Design of Selective Supercritical CO<sub>2</sub> Extraction of Lithium from Geothermal Brine
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Bibliographic record
Abstract
Abstract As demand grows for lithium, its recovery from geothermal brines provides an attractive alternative to slow mining. One promising extraction method uses crown ethers as extractants in supercritical carbon dioxide with cation exchangers to facilitate extraction from brine. Molecular dynamics modeling is used to understand the mechanism of binding between lithium (or sodium) and combinations of 14‐crown‐4 ethers and cation exchangers, and the predictive capability of computational modeling to test lithium selectivity is established for four combinations of crown ethers [methylene‐14‐crown‐4 (M14C4) and a fluorinated 14‐crown‐4 (F14C4)] and cation exchangers [di(2‐ethyl‐hexyl)phosphoric acid (HDEHP) and tetraethylammonium perfluoro‐1‐octanesulfonate (TPFOS)]. Binding free energies (given in kcal mol −1 ) of lithium and sodium, respectively, to crown ether–cation exchangers are 85 and 71 for M14C4–HDEHP, 90 and 71 for F14C4–HDEHP, 93 and 80 for M14C4–TPFOS, and 104 and 93 for F14C4–TPFOS. Good agreement is found between computational predictions and supercritical carbon dioxide extraction experiments at 60 °C and 250 bar. Binding free energy gives a suitable metric to describe extraction efficiency. Differences in the binding free energies of sodium and lithium to crown ethers determine the extraction selectivity. Fluorine groups are found to exert a positive influence to optimize extraction efficiency. Of the systems studied, F14C4 with TPFOS offers the most selective and efficient extraction system.
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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) | 0.000 | 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 it