Charge build-up and re-distribution in SrTi<sub>x</sub>Nb<sub>1−x</sub>O<sub>3</sub> quantum wells and TiO<sub>2</sub>–SrTiO<sub>3</sub> heterostructure
Bibliographic record
Abstract
This work examined charge build-up and re-distribution in SrTi x Nb1−x O3 quantum wells and TiO2–SrTiO3 heterostructure based on thermoelectric power data reported in the literature. In this work, we first identified the equations that best related charge density to the thermoelectric power. Using such equations together with a distributed model that accounted for the layered structure, we computed the charge densities in the two structures over a broad temperature range. Our findings suggested that charge migration from the quantum wells into the substrate was primarily governed by the barrier height at the interface. A very different charge density profile was observed in the heterostructure and the computed charge spread into the substrate was immense (of the order of hundreds of micrometres). By comparing such charge spread with values taken from samples when the TiO2 top layer had been removed, we arrived at the conclusion that it could not have originated from the interface and must have arisen from other sources such as oxygen vacancies (acting as donors) embedded during film 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".