Low-frequency polarization in molecular-scale noble-metal/metal–oxide nanocomposites
Bibliographic record
Abstract
Materials with high dielectric permittivity are highly desirable in the electronics industry. One avenue for enhancing the permittivity of standard metal oxide and ceramic dielectrics is to incorporate nanoscale Ag and Au inclusions in the material. Given the small scale of modern day devices, these inclusions will necessarily be up to a few nanometers in size. We develop methodology by which polarization in nanocomposites with molecular-scale inclusions can be obtained from first-principles calculations, and partitioned into inclusion and matrix contributions. The methodology is applied to a model Ag8/MgO nanocomposite. A 4% volume loading of Ag8 nanoparticles leads to a 30% enhancement of the dielectric permittivity. The enhancement arises from both the electronic polarization of the nanoparticle and the additional polarization of matrix ions in the interfacial region.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".