Anomalous water molecular gating from atomic-scale graphene capillaries for precise and ultrafast molecular sieving
Bibliographic record
Abstract
Abstract The pressing crisis of clean water shortage requires membranes to possess effective ion sieving as well as fast water flux. However, effective ion sieving demands reduction of pore size, which inevitably hinders water flux in hydrophilic membranes, posing a major challenge for efficient water/ion separation. Herein, we introduce anomalous water molecular gating based on nanofiltration membranes full of graphene capillaries at 6 Å, which were fabricated from spontaneous π-π restacking of island-on-nanosheet graphitic microstructures. We found that the membrane can provide effective ion sieving by suppressing osmosis-driven ion diffusion to negligible levels (~10 –4 mol m –2 h –1 ); unexpectedly, ultrafast bulk flow of water (45.4 L m –2 h –1 ) was still functional with ease, as gated on/off by adjusting hydrostatic pressures within only 10 –2 bar. We attribute this seemingly incompatible observation to graphene nanoconfinement effect, where crystal-like water confined within the capillaries hinders diffusion under osmosis but facilitates high-speed, diffusion-free water transport in the way analogous to Newton’s cradle-like Grotthus conduction. This strategy establishes a type of liquid-solid-liquid, phase-changing molecular transport for precise and ultrafast molecular sieving.
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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".