Quantifying Water Friction in Misaligned Graphene Channels under Ångström Confinements
Bibliographic record
Abstract
Two-dimensional (2D) materials, such as graphene (GE), hold great potential to be employed as the fundamental building blocks of novel nanofluidic devices for a wide range of applications. Recent advances in experimental techniques are materializing such prospects by enabling the assembly of 2D material-based fluidic channels with heights as small as few Ångströms. Here, we conduct molecular dynamics simulations to probe the effect of the relative misalignment between the walls of the GE fluidic channel with Ångströms height on the resistance to water transport through the channel. Two types of misalignments are studied, namely, translational and rotational misalignments. Our results show that the relative misalignment of the GE lattices can lead to a substantial reduction in the friction between water and the channel walls. Moreover, a dependence of the friction on the degree of misalignment and flow direction is found for the cases with translational misalignment. In contrast, the resistance exerted by the channels with rotational misalignment is found to be independent of the rotation angle (θ) for 0° < θ < 60° but always lower than the perfectly aligned case. We associate such lowering of the resistance to water transport to the corrugation and the anisotropy in the corresponding potential energy landscape associated with each degree of misalignment. The findings, therefore, point to an unprecedented possibility of significantly enhancing the water transport in Ångströms height GE channels by engineering the misalignments of the GE channel walls.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".