Efficient Aerial Water Harvesting with Self-Sensing Dynamic Janus Crystals
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Water scarcity is one of the most pressing issues of contemporary societal development that requires innovative technologies where the material not only harvests water but also plays an active role in the process. Here, we demonstrate a highly efficient optical self-sensing approach to humidity capture from the air, where both humidity-harvesting and water-transduction functionalities are imparted on slender organic crystals by partial silanization via layer-by-layer hybridization. We report that due to the integration of the harvesting of aerial moisture and the collection of the condensed water, the ensuing Janus-type crystals capture humidity with the highest-to-date water collection efficiency of 15.96 ± 0.63 g cm –2 h –1 . The water-collecting elements are also capable of delivering the water by reversible and periodic elastic deformation, and their high optical transparency allows real-time monitoring of the periodic fog collection process by deformational modulation of passively or actively transduced light that outcouples at the crystal-droplet interface. The results could inspire sophisticated approaches to humidity harvesting where optically transparent crystals combine fog capture with self-sensing capabilities for continuous and optimized operation to maximize the cost-gain balance of aerial fog capture.
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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".