Bioinspired Polypeptide Dendrimer‐Modified Thin‐Film Composite Membranes for Selective Lithium‐Magnesium Separation with DFT Insights
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Bibliographic record
Abstract
ABSTRACT Selective ion transport in nanofiltration (NF) enables sustainable lithium (Li + ) recovery. While many membranes rely on strong positive charge for Li⁺/Mg 2 ⁺ separation, we show that negatively charged membranes can also excel using a biomimetic approach. Inspired by biological ion channels that achieve cation selectivity via specific binding sites despite their negative charge, we designed a nitrogen‐rich polypeptide dendrimer (amino acid–based) bearing carboxylate coordination sites with higher affinity for Mg 2 ⁺ than Li⁺, while moderating the membrane's net negative charge. This biomimetic design enhanced Li + recovery by inhibiting Mg 2+ transport through stronger interactions, thereby allowing for preferential Li + permeation. This process occurred through a combination of electrostatic modulation and ligand‐assisted coordination. Density functional theory (DFT) calculations indicated strong oxygen‐donor coordination: lysine motifs bind hydrated Mg 2+ (E ≈ −170 kcal.mol −1 ) far more strongly than Li + (E ≈ −50.2 kcal.mol −1 ). The optimized membrane achieved Li + /Mg 2+ selectivity of 15.6 at neutral pH with 23 LMH flux, and 136 at pH 4, highlighting strong performance in acidic feeds. Long‐term tests showed ∼0.4% leaching over 10 days with stable rejection and enrichment of Li⁺ (feed Li⁺/Mg 2 ⁺ increased from 0.05 to 0.20). Antifouling tests showed a twofold lower flux‐decline ratio and higher flux‐recovery than the unmodified TFC.
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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 | 0.001 |
| 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