Addition of microcrystalline cellulose to an alkyd resin/titanium dioxide film: effect on dielectric properties
Bibliographic record
Abstract
In this study, various composite films were prepared by varying the amounts of long-oil Alkyd Resin (AR), Titanium Dioxide (TiO 2 ) and Microcrystalline Cellulose (MCC). The effects of each component, TiO 2 and MCC, on the properties and microstructure of the dry film were determined by examining images obtained by scanning electron microscopy (SEM) and studying the evolution of dielectric properties, the dielectric constant and the loss factor, against frequency at room temperature. Results showed that the introduction of the TiO 2 /MCC powder with a weight ratio larger than 1 and a volumetric pigment concentration (VPC) less than 50% allowed a better dispersion of the particles and fitted well the Linchtencker logarithmic mixing law and the Maxwell-Garnett theory. Finally, a marked improvement of the dielectric constant with respect to those of pure alkyd resin and AR/TiO 2 composites was observed.
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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".