Recyclable Polydopamine-Functionalized Sponge for High-Efficiency Clean Water Generation with Dual-Purpose Solar Evaporation and Contaminant Adsorption
Bibliographic record
Abstract
Solar desalination of seawater is an attractive and environmentally friendly method to solve the long-standing water crisis. However, its efficiency is highly reliant on solar intensity. Additionally, increasing contamination in water makes it difficult to generate clean water through the solo desalination process. To address this, we propose a polydopamine (PDA)-functionalized hybrid material with dual-purpose solar evaporation and contaminant adsorption for highly efficient clean water production in all-weather conditions. The hybrid material is fabricated by polymerization of dopamine onto a commercial sponge in a facile, low-cost, and scalable manner. With excellent light absorption and chelation capabilities, the PDA film coated on sponge acts as both a photothermal material and adsorbent that allow us to achieve clean water production with solar desalination when sunshine and with contaminant adsorption when cloudy or at night. Meanwhile, the solar evaporation and contaminant adsorption of the PDA-sponge are synergized with one another, resulting in the PDA-sponge that is a desirable material with the capability of continuous clean water production in all-weather conditions. The PDA-sponge is also highly recyclable with a high retention rate of evaporation and adsorption efficiency even after 10 cycles. The promising PDA-based hybrid is believed to inspire new strategies for superior water treatment materials.
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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".