Large scalable, ultrathin and self-cleaning cellulose aerogel film for daytime radiative cooling
Bibliographic record
Abstract
Passive cooling strategy shows great potential in mitigating global warming and reducing energy consumption. Because of the high emissivity in the atmospheric transparency window (λ ≈ 8–13 μm), cellulose is considered as a good candidate for radiative cooling. However, traditional cellulose coolers generally show poor solar reflection and can be polluted by dust outside, thereby resulting in poor daytime cooling efficiency. To address these drawbacks, we developed sustainable cellulose nanowhiskers (CNWs)/ZnO composite aerogel films with favorable optical performance, mechanical robustness, and self-cleaning function for efficient daytime radiative cooling, which can be achieved via freeze casting and hot-pressing process. Due to formation of multi-level porous structure and chemical bonds (Si-O-C/Si-O-Si), such aerogel film exhibited high solar reflectance (97%) and high infrared emittance (92.5%). It achieved a sub-ambient temperature drop of 6.9 °C under direct sunlight in hot weather. Most importantly, the surface roughness and low surface energy enable cellulose aerogel film hydrophobicity (contact angle = 133°), thereby resulting in an anti-dust function. This work provides insight into the design of sustainable thermal regulating materials to realize carbon neutrality.
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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".