Polybenzimidazole-Modified Cation-Exchange Membrane with High Monovalent Ion Selectivity for Electrodialysis Separation of Alkaline/Alkaline Earth Metals
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide One of the keys to sustainable mining and recycling of alkaline/alkaline earth metals is using membrane technology for mono/divalent ion separation. Developing membrane materials with high selectivity could significantly enhance minerals’ extraction and recycling. In this work, polybenzimidazole (PBI) was incorporated into the matrix of the commercial cation-exchange Nafion-117 membrane via in situ polymerization of 1,2,4,5-benzenetetraamin (BTA) and teraphthalaldehyde, forming a hybrid cation-exchange membrane with high selectivity for monovalent ions. The optimum membrane was obtained within 6 min of contact time with BTA (denoted as PBI-6m). Fourier transform infrared and Raman spectroscopy and small-angle X-ray scattering confirmed the successful penetration of PBI into the membrane structure. PBI-6m was tested in electrodialysis separation of mixed electrolyte solutions containing Li, Na, K, Mg, Ca, and Sr chlorides for a current range of 0.4–3.0 mA/cm 2 and concentration range of 3–9 mM of each electrolyte. The modified membrane exhibited a high selectivity to less hydrated and monovalent ions, providing a high separation for Na/Mg, Li/Mg, and Na/Ca of up to 27, 11, and 3.8, respectively, with a current efficiency of more than 80%. The membrane behavior was scrutinized through current–voltage polarization experiments and impedance spectroscopy in individual and mixed ionic environments. The results demonstrated that the separation mechanism is based on the low mobility of the divalent ions, which is explained by the ionic blockage emanating from the reduction of pores and channels’ diameter upon the integration of PBI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".