Defect‐Tolerant and Scalable Diffusio–Osmotic Power Generation with Sulfonated Covalent Organic Framework Membrane
Bibliographic record
Abstract
Salinity gradient energy extracted with the reverse electrodialysis technique is attracting great interest and has been suggested as a promising renewable and stable energy source. However, the reverse electrodialysis relies on highly charge-selective membranes, causing a range of problems including the selectivity-permeability trade-off, strong concentration polarization, and strict requirement on the material structure, severely limiting its viability for large scale applications. We demonstrate these problems may be addressed by adopting the diffusio-osmosis process to generate power using sulfonated covalent framework membranes (COF), which does not require any charge selectivity. As a result, the membrane shows much higher power density compared to similar-sized membranes and enables much higher scalability. Remarkably, the generator has loose requirement on material structure and could largely maintain its power generation performance even when a substantial number of pinholes are present. This could make the material fabrication significantly easier than before. We expect our work to advance the practical application of salinity gradient energy extraction.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".