Defect structure in aliovalently-doped and isovalently-substituted PbTiO<sub>3</sub>nano-powders
Bibliographic record
Abstract
The defect structure of Fe(3+)-, Cu(2+)-, Mn(4+)- and Gd(3+)-doped PbTiO(3) nano-powders has been studied by electron paramagnetic resonance (EPR) spectroscopy. Analogous to the situation for 'bulk' ferroelectrics, Fe(3+) and Cu(2+) act as acceptor-type functional centers that form defect complexes with charge-compensating oxygen vacancies. The corresponding defect dipoles are aligned along the direction of spontaneous polarization, P(S), and possess an additional defect polarization, P(D). Upon the transition to the nano-regime, the defect structure is modified such that orientations perpendicular to P(S), [Formula: see text] and [Formula: see text] also become realized. Moreover, the binding energy for the defect complexes is lowered such that instead 'free' Fe'(Ti) and V··(O)-centers are formed. As a consequence, the concentration of mobile V··(O) that enhances the ionic conductivity through drift diffusion is increased for the nano-powders. Finally, in the nano-regime the ferroelectric 'hardening' is expected to be considerably decreased as compared to the 'bulk' compounds. In contrast to the acceptor-type dopants, the donor-type Gd(3+) dopant is incorporated as an 'isolated' functional center, where charge compensation by means of lead vacancies is performed in distant coordination spheres.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".