Morphological development and environmental degradation of superhydrophobic aspen and black locust leaf surfaces
Bibliographic record
Abstract
ABSTRACT The complete adaxial surface development and degradation due to weathering of two superhydrophobic leaf species with (black locust, Robinia pseudoacacia and bigtooth aspen, Populus grandidentata) and one without (quaking aspen, Populus tremuloides) a protective downy layer of trichomes was followed over one entire growing season using scanning electron microscopy and wetting property measurements. Scanning electron microscopy micrographs illustrate the initial development period of a dual‐scale surface structure consisting of micrometre‐sized papillae and nanoscale wax crystals, which was followed by a period of environmental degradation as nanoscale wax features were subjected to environmental stress. It was discovered that robust micropapillae protect nanoscale wax morphologies in‐between them for quite some time allowing for a high tolerance to wear and erosion. Weather data was used to demonstrate the correlation between cumulative environmental stresses (temperature, relative humidity, precipitation and wind) and the loss of superhydrophobicity at the end of the growing season. Analysis of all binary combinations of the aforementioned environmental stress factors propose that cumulatively hot and humid weather have the most significant impact on degradation of nanoscale wax crystals and therefore result in the final loss of superhydrophobic behaviour. These findings were also tentatively linked to their importance in ecohydrology suggesting that canopy storage capacity, which has been previously correlated with leaf hydrophobicity, of superhydrophobic leaves may fluctuate considerably throughout an entire growing season. Copyright © 2013 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".