Water-Dispersible and Ferroelectric PEGylated Barium Titanate Nanoparticles
Bibliographic record
Abstract
Dispersions of ferroelectric nanoparticles in aqueous medium can find promising applications in electro-optical, medical, and smart fluid technologies. In this report, we show the development of highly dispersed nano-sized ferroelectric barium titanate (BaTiO3) powders with high dielectric constant prepared using a simple, one-step low temperature solution method. The surface of these tetragonal-structured nanoparticles were modified with polyethylene glycol as a stabilizer and dispersant. The crystal structure, morphology and dielectric constant of samples are discussed in detail. The colloidal stability and surface behavior of these PEGylated barium titanate nanoparticles are studied by means of z -potential and dynamic light scattering measurements. We show changing the reaction conditions allows to tune the nanoparticle size. This research promotes a pathway to develop advanced ferroelectric nanomaterials with engineered properties in a simple way.
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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".