Thermo-adaptive interfacial solar evaporation enhanced by dynamic water gating
Bibliographic record
Abstract
Abstract Solar-driven evaporation offers a sustainable solution for water purification, but efficiency losses due to heat dissipation and fouling limit its scalability. Herein, we present a bilayer-structured solar evaporator ( SDWE ) with dynamic fluidic flow mechanism, designed to ensure a thin water supply and self-cleaning capability. The porous polydopamine ( PDA ) layer on a nickel skeleton provides photothermal functionality and water microchannels, while the thermo-responsive sporopollenin layer on the bottom acts as a switchable water gate. Using confocal laser microscopy and micro-CT, we demonstrate that this unique structure ensures a steady supply of thin water layers, enhancing evaporation by minimizing latent heat at high temperatures. Additionally, the system initiates a self-cleaning process through bulk water convection when temperature drops due to salt accumulation, thus maintaining increased evaporation efficiency. Therefore, the optimized p-SDWE sample achieved a high evaporation rate of 3.58 kg m −2 h −1 using 93.9% solar energy from 1 sun irradiation, and produces 18–22 liters of purified water per square meter of SDWE per day from brine water. This dynamic water transport mechanism surpasses traditional day-night cycles, offering inherent thermal adaptability for continuous, high-efficiency evaporation.
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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".