Excess noise and thermoelectric effect in magnetron-sputtered VO2 thin films
Bibliographic record
Abstract
This work presents the excess noise and thermoelectric (Seebeck) measurements on polycrystalline vanadium dioxide (VO2) thin films. Noise spectral power density (SPD) of current fluctuations in the semiconducting (SC) phase had a typical flicker noise (f−γ) characteristic with an average slope parameter γ of 1.13. Normalized SPD (Sn) values obtained in the SC-phase indicate that the noise originates in the bulk of the film. On the contrary, in the metallic (M)-phase, γ values were greater than unity, and the observed Sn values indicated that the origin of the noise is most likely from the contacts or surface rather than the bulk. A general decrease was observed in Sn by a factor of 4–5 from the SC- to M-phase. Moreover, Sn in the SC-phase showed no temperature dependence. An interpretation based on the number of charge carrier fluctuations in Hooge's model led to an unrealistically high Hooge parameter and had to be ruled out. We propose that the fluctuations are related to the mobility fluctuations of carriers arising primarily from grain-boundary scattering which explains the observed characteristics well. The Seebeck coefficients (S) obtained under both heating and cooling schedules showed the n-type nature of magnetron-sputtered VO2 films in the SC-phase. Differently, in the M-phase, the S value was positive. The S values obtained from the cooling schedule signified the low percolation threshold of the metal-to-insulator transition already demonstrated for VO2 thin films grown on r-cut sapphire using the Efros–Shklovskii percolation model.
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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) | 0.000 | 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".