A Redox‐Tunable Carborane Crown: Toward Highly Selective Electrochemical Lithium Capture
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Bibliographic record
Abstract
Abstract Lithium is a critical element with a projected exponential rise in demand due to its widespread use in battery energy storage. New methods to extract Li + , such as through membrane adsorption‐based direct Li + extraction (DLE) technologies, are at various stages of development and aim to separate Li + from brine and even seawater. In this report, we present a fundamentally new class of highly selective Li + ‐capture agent, the carborane‐crown compound, 1,2‐((6,6,7,7‐Me 4 )14‐crown‐4)‐ ortho ‐carborane ( 14C4 Cb ), which is electrochemically activated for strong, selective Li + binding over Na + and K + . This newly synthesized extractant features a redox‐tunable cavity size, giving rise to tunable binding constants for Li + capture, favorable coulombic interactions between the reduced anionic capture agent and the Li + cations, and boasts the benefit of rapid, electrochemically driven capture kinetics. Weak, negligible binding to Li + was observed in the neutral “ closo ” carborane state ( 14C4 Cb ), whereas strong binding was observed in the cage‐opened reduced nido state ( 14C4 Cb 2− ). Equilibrium ( K ) binding constants were measured through experimental and simulated voltammetry, yielding the following log K metal (experimental; simulation ) values: log K Li (6.8 ± 0.6; 8.0 ), log K Na (3.7 ± 0.2; 4.9 ), log K K (1.7 ± 0.2; 2.2 ). Rapid mass transport of Li + to the electrode surface resulted in the simulated value (log K Li = 8.0) representing a lower‐limit value for log K Li as described herein. The observed strong binding to Li + over Na + and K + is attributed to both the favorable redox‐tunable crown cavity size of the 14C4 Cb/ 14C4 Cb 2− couple, combined with strong coulombic interactions in the reduced nido state. This platform offers a potential new, rapid, and highly selective technique for Li + capture in next‐generation electrochemical DLE technologies.
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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 | 0.001 |
| 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