Engineering Electro‐Optic BaTiO<sub>3</sub> Nanocrystals via Efficient Doping
Bibliographic record
Abstract
Abstract Electro‐optic (EO) modulators provide electrical‐to‐optical signal conversion relevant to optical communications. Barium titanate (BaTiO3) is a promising material system for EO modulation in light of its optical ultrafast nonlinearity, low optical loss, and high refractive index. To enhance further its spontaneous polarization, BaTiO3 can be doped at the Ba and Ti sites; however, doping is often accompanied by ion migration, which diminishes EO performance. Here, donor–acceptor doping and its effect on EO efficiency are investigated, finding that La‐doped BaTiO3 achieves an EO coefficient of 42 pm V−1 at 1 kHz, fully twice that of the pristine specimen; however, it is also observed that, with this single‐element doping, the EO response falls off rapidly with frequency. From impedance spectroscopy, it is found that frequency‐dependent EO is correlated with ion migration. Density functional theory calculations predict that the ion‐migration barrier decreases with La3+ doping but can be recovered with further Mn2+ doping, a finding that prompts to prevent ion migration by incorporating Mn2+ into the Ti‐site to compensate for the charge imbalance.
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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".