Ultra-Thin Cation Exchange Membranes: Sulfonated Polyamide Thin-Film Composite Membranes with High Charge Density
Bibliographic record
Abstract
Advancements in membrane technology are crucial for electrochemical separations, such as ion exchange, and pressure-driven processes, such as nanofiltration (NF). This study introduces high-charge-density sulfonated polyamide thin-film composite membranes fabricated via interfacial polymerization using disulfonated monomers, resulting in ultra-thin (∼50 nm) films that serve as nanofiltration (NF) membranes or cation exchange membranes (CEMs). Post-modifications enabled precise control over membrane chemistry, enhancing CEM properties such as ion exchange capacity, water uptake, and fixed charge concentration. The high charge density led to ion selectivity in NF via the Donnan exclusion mechanism, facilitating effective separation of monovalent and divalent ions. The incorporation of sulfonic acids within an ultra-thin polyamide matrix significantly reduced the resistance for ion and proton transport, enabling high in-plane conductivities (Na +: >80 mS cm –1, H 3 O +: >200 mS cm –1 ) comparable to state-of-the-art polymer-based CEMs. Furthermore, the nanoscale thickness of these membranes dramatically enhanced ionic and proton conductance, achieving area conductance values 4 to 6 orders of magnitude higher than those of conventional thick CEMs. This enhancement is primarily attributed to the ultra-thin design of our sulfonated polyamide membrane, setting a new benchmark for the design and fabrication of highly conductive membranes, and laying the groundwork for future enhancements of ion conductive membranes for water purification and energy applications.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".