Influence of a realistic multiorbital band structure on conducting domain walls in perovskite ferroelectrics
Bibliographic record
Abstract
Domain wall morphologies in ferroelectrics are believed to be largely shaped by electrostatic forces. Here, we show that for conducting domain walls, the morphology also depends on the details of the charge-carrier band structure. For concreteness, we focus on transition-metal perovskites like ${\mathrm{BaTiO}}_{3}$ and ${\mathrm{SrTiO}}_{3}$. These have a triplet of ${t}_{2g}$ orbitals attached to the Ti atoms that form the conduction bands when electron doped. We solve a set of coupled equations---Landau-Ginzburg-Devonshire (LGD) equations for the polarization, tight-binding Schr\"odinger equations for the electron bands, and Gauss' law for the electric potential---to obtain polarization and electron density profiles as a function of electron density. We find that at low electron densities, the electron gas is pinned to the surfaces of the ferroelectric by a Kittel-like domain structure. As the electron density increases, the domain wall evolves smoothly through a zigzag head-to-head structure, eventually becoming a flat head-to-head domain wall at high density. We find that the Kittel-like morphology is protected by orbital asymmetry at low electron densities, while at large electron densities the high density of states of the multiorbital band structure provides effective screening of depolarizing fields and flattens the domain wall relative to single-orbital models. Finally, we show that in the zigzag phase, the electron gas develops tails that extend away from the domain wall, in contrast to na\"{\i}ve expectations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".