Organic–inorganic hybrid thin films based in HfO<sub>2</sub> nanoparticles as dielectric for flexible electronics
Bibliographic record
Abstract
In this work the synthesis and characterization of an organic–inorganic hybrid composite film based on hafnium oxide (HfO2) and polyvinylpyrrolidone (PVP) with dielectric properties is presented. These films were prepared using the sol-gel process adjusting the chemical composition to tailor the material properties, such as the dielectric and the optical band gap. The HfO2 was obtained by the hydrolysis of hafnium chloride (HfCl4) under catalysis of ethanol and deionized water, later the PVP was subsequently added to complete the hydrolysis. Finally the films were dried at 150 °C. The structural characterization of the hybrid material showed a hafnium nanoparticle size around 100 nm into the polymer matrix. The chemical structure and the high purity of the hybrid material were corroborated by X-ray photoelectron spectroscopy measurements, which showed the bounding of HfO2–PVP. The electrical characterization demonstrated that the nanostructured materials with hafnium nanoparticles improve the dielectric constant in the films with values around k = 18.5. The optical band gap, Eo, was obtained from 4 to 5.7 eV. These characteristics in our hybrid material are very promising for flexible electronics applications with the advantage of its low temperature, thermal stability, and low cost process of deposition.
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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".