Robust Hydrophobic Rare Earth Oxide Composite Electrodeposits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Inspired by the lotus leaf, nonwetting surfaces have drawn widespread attention in the field of surface engineering due to their remarkable water repelling characteristics. There are many applications for these surfaces, for instance, self‐cleaning walls and windows, anti‐icing surfaces, or low drag microfluidic channels. However, the adoption of nonwetting surfaces in large scale industrial applications has been hampered by synthesis techniques that are not easily scalable and the limited long term stability and wear robustness of these surfaces in service. This study demonstrates a simple, low cost, and scalable electrochemical technique to produce robust composite coatings with tunable nonwetting properties. The composite coatings are composed of an ultrafine grain nickel matrix with embedded hydrophobic cerium oxide ceramic particles. A comprehensive characterization is performed, including wetting property measurements, electron microscopy, focused ion beam analysis, hardness measurements, and abrasive wear testing to establish the structure–property relationships for these materials. The ultrafine grain structure of the nickel matrix contributes to the high hardness of the composites. As a result of the bimodal CeO 2 particle size, hierarchical roughness is present on the surface of the composite, leading to remarkable nonwetting properties, even after 720 m of abrasive wear.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 it