Hydrophobic Nano‐Silica for the Surface Modification of Graphite Flake
Bibliographic record
Abstract
Abstract Graphite flake is an electromagnetic interference material of importance for IR screening. In this study, an attempt to improve the performance of graphite flake by coating it with nano‐silica using cyclomix (Hosokawa) and hybridizer (Nara) processes was made. Uncoated and coated graphite flakes were examined by scanning electron microscopy (SEM). It was shown that a more uniform coating was obtained using the hybridizer process. Coated graphite flake with a mass ratio of nano‐silica equal to 5.25 % exhibited the best hydrophobic properties. The test chamber experiments demonstrated that the deposition velocity of coated graphite flake decreased from 0.227 cm s−1 to 0.187 cm s−1 and its IR interference performance was improved, compared with uncoated graphite flake. The obtained results showed that the coatings on the graphite flake powder with hydrophobic nano‐silica enhanced the moisture resistance and electromagnetic interference performance of the graphite flake.
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".