Water transport and desalination through double-layer graphyne membranes
Bibliographic record
Abstract
Non-equilibrium molecular dynamics simulations of water-salt solutions driven through single and double-layer graphyne membranes by a pressure difference created by rigid pistons are carried out to determine the relative performance of the membranes as filters in a reverse osmosis desalination process. It is found that the flow rate of water through a graphyne-4 membrane is twice that of a graphyne-3 membrane for both single and double-layer membranes. Although the addition of a second layer to a single-layer membrane reduces the membrane permeability, the double-layer graphyne membranes are still two or three orders of magnitude more permeable than commercial reverse osmosis membranes. The minimum reduction in flow rate for double-layer membranes occurs at a layer spacing of 0.35 nm with an AA stacking configuration, while at a spacing of 0.6 nm the flow rate is close to zero due to a high free energy barrier for permeation. This is caused by the difference in the environments on either side of the membrane sheets and the formation of a compact two-dimensional layer of water molecules in the interlayer space which slows down water permeation. The distribution of residence times of water molecules in the interlayer region suggests that at the critical layer spacing of 0.6 nm, a cross-over occurs in the mechanism of water flow from the collective movement of hydrogen-bonded water sheets to the permeation of individual water molecules. All membranes are demonstrated to have a high salt rejection fraction and the double-layered graphyne-4 membranes can further increase the salt rejection by trapping ions that have passed through the first membrane from the feed solution in the interlayer space.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".