Biomimetic Grooved Ribbon Aerogel Inspired by the Structure of Pinus sylvestris var. mongolica Needles for Efficient Air Purification
Bibliographic record
Abstract
Air pollutants, such as particulate matter (PM) and ammonia (NH3), generated by intensive animal farming pose considerable threats to human health, animal welfare, and ecological balance. Conventional materials are often ineffective at simultaneously removing multiple pollutants, maintaining a low pressure drop, and ensuring durability in heavily polluted environments. Inspired by the dust-retention properties of Pinus sylvestris var. mongolica (PS) needles, this study developed a biomimetic grooved ribbon fiber using electrospinning technology. These fibers were further assembled into a three-dimensional bioinspired aerogel structure through freeze-forming technology to achieve efficient dust capture. Additionally, the introduction of UiO-66-NH2 nanoparticles significantly enhanced the properties of the aerogels for NH3 adsorption. Among the various prepared aerogels (PG, UPG-5, UPG-10, UPG-15, and UPG-20), UPG-10 demonstrated the best performance, achieving a filtration efficiency of 99.24% with a pressure drop of 95 Pa. Notably, it exhibited a remarkable dust-holding capacity of 147 g/m2, and its NH3 adsorption capacity reached 99.89 cm3/g, surpassing PG aerogel by 31.46 cm3/g. Additionally, UPG-10 exhibited outstanding elasticity, maintaining over 80% of its original shape after 30 compression cycles. This biomimetic aerogel presents a promising solution for air purification, contributing to improved agricultural efficiency and environmental sustainability.
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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) | 0.000 | 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 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".