Water‐Assisted Programmable Assembly of Flexible and Self‐Standing Janus Membranes
Bibliographic record
Abstract
Abstract Janus membranes with asymmetric wettability have been considered cutting‐edge for energy/environmental‐sustainable applications like water/fog harvester, breathable skin, and smart sensor; however, technical challenges in fabrication and accurate regulation of asymmetric wettability limit their development. Herein, by using water‐assisted hydrogen‐bonded (H‐bonded) assembly of small molecules at water/oil interface, a facile strategy is proposed for one‐step fabrication of membranes with well‐regulable asymmetric wettability. Asymmetric orderly patterns, beneficial for mass transport based on abundant high‐permeability sites and large surface area, are constructed on opposite membrane surfaces. Upon tuning water‐assisted H‐bonding via H‐sites/configuration design and temperature/pH modulation, double‐hydrophobic, double‐hydrophilic, and hydrophobic‐hydrophilic membranes are facilely fabricated. The Janus membranes show smart vapor‐responsive curling and unidirectional water transport with promising flux of 1158±25 L m−2 h−1 under natural gravity and 31500±670 L·(m−2 h−1 bar−1) at negative pressure. This bottom‐up approach offers a feasible‐to‐scalable avenue to precise‐manipulation of Janus membranes for advanced applications, providing an effective pathway for developing tailor‐made self‐assembled nanomaterials.
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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".