Fabrication and Characterization of PZN-4.5PT Inorganic Perovskites Nanoparticles Thin Films Deposited on P-Type Silicon Substrate
Bibliographic record
Abstract
This work involves an investigation of nanostructures, microelectronic properties and domain engineering of nanoparticles thin layers of Pb(Zn1/ 3Nb2/3)O3-PbTiO3 (PZN-PT) ferroelectric single crystals deposited on nanostructured silicon substrate. In this study, devices made from PZN-4.5PT nanoparticles thin films successfully deposited on silicon substrate have been studied and discussed. SEM images show the formation of local black circles and hexagonal shapes probably due to the nucleation of a new Si-gel component or phase induced by annealing. Micro Xray Fluorescence mapping shows that the high values of Si and B atoms (≅7 and 4 normalized unit respectively) can be explained by the fact that the substrate is p-type silicon. The most interesting result of optical measurements is the very good absorption for all the thin films in UV, Visible and NIR regions with values from 70% to 90% in UV, from 75% to 93% in Visible and NIR. Tauc plots present particularities (rarely encountered behavior) with different segments or absorption changes showing the presence of multiple band gaps coming from the heterogeneity of the thin films (nanowires, gel and nanoparticles). Their values are 1.9 and 2.8 eV for DKRN-Gel, 2.1 and 3.1 eV for DKRN-UD and 2.1 and 3.2 eV for DKRN-D) corresponding respectively to the band gap of nanowires and that of the gel while the last ones correspond to the undoped and doped nanoparticles (3.1 and 3.2 eV respectively).
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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".