Highly porous nanocoatings tailored for inverse nanoparticle‐polymer composites
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 A novel nanoparticle‐polymer composite is proposed, named inverse nanocomposites in this work. First, a rigid percolating scaffold of nanoparticles is formed, which is filled with a matrix and then polymerized. Targeted for use in thin‐film applications, these mesoporous nanoparticle scaffolds are prepared by combining the sol–gel chemistry of functionalized silanes with nanoparticles in dispersions. The nanoparticle coatings have high porosity, low density, good adhesion to the substrate, and interesting non‐classical properties, such as absorbency of highly viscous fluids. The porosity, which can be adjusted by changing the composition and preparation parameters, reaches 75%. The porous scaffold can be infiltrated with various fluids, including acrylic and epoxy monomers and even highly viscous pressure‐sensitive adhesives. If the monomers are polymerized after imbibition, the inverse nanocomposite is formed, consisting of a percolating particle network surrounded by a polymeric binder. Hence, the morphology comprises an interpenetrating system of two co‐continuous phases and not merely particles dispersed in a polymeric phase, as is typical for conventionally prepared nanocomposites.
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) | 0.000 | 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 it