Bioinspired waterproof, breathable materials: How does nature transport water across its surfaces and through its membranes?
Bibliographic record
Abstract
The controlled transport of water vapor and liquid water across membranes is a crucial biological process observed in natural systems for over 460 million years. Through evolution, plants have developed various methods to regulate water gradients between their internal structures and the external environment. The primary natural mechanisms used to modulate the water gradient effectively involve integrating specialized organs, like those responsible for gas exchange, in tandem with developing impermeable outer surfaces. Several applications in engineered materials – including rainwear, wound dressings, textiles, packaging, and building materials require breathability and waterproofing properties. Breathable materials can enable water vapor movement within their structure, while waterproof materials effectively resist the penetration and absorption of liquid water. Developing materials that can simultaneously exhibit waterproofness, and breathability presents a significant scientific and engineering challenge due to the inherent conflict between these properties. This review aims to delve into the physicochemical mechanisms governing plant water transport and establish a connection with developing bio-based and bio-inspired materials. We explore how plant components can give rise to hydrophobic, hydrophilic, porous, and responsively porous bio-inspired materials, addressing challenges encountered in the waterproof-breathable textile industry.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".