Direct Observation of Core–Shell Structures in Individual Lead Titanate Ferroelectric Nanostructures by Tip‐Enhanced Refractive Index Mapping
Bibliographic record
Abstract
Abstract Ferroelectrics undergo a size‐driven phase transition at the nanoscale below which the spontaneous polarization, their defining property, irrevocably ceases. This threshold often referred to as the superparaelectric limit has tremendous technological relevance in an era of progressing integration. Just as the balance of short‐range elastic and long‐range electrostatic ordering in bulk, the critical size depends on temperature. Room‐temperature tip‐enhanced Raman spectroscopy (TERS) imaging of individual lead titanate (PbTiO3) nanoislands is reported with a spatial resolution of ≈3 nm. Monitoring the spectral shift of the gold‐tip enhanced luminescence, which depends on the local refractive index, images grains composing the nanoislands. The wavelength of the enhanced luminescence shifts between the grains and their boundaries indicating the predicted core–shell structure of ferroelectric and paraelectric phase. The shear force configuration rules out the distance dependence of capacitive plasmonic coupling between tip and substrate as the origin of the observed shift. As the reported temperature‐changes in nonresonant TERS do not account for noticeable thermal effects, the underlying, even though weak, tip‐enhanced Raman spectrum of the grain core reflects PbTiO3 close to the ferroelectric‐to‐paraelectric phase transition which is primarily related to the finite size of the grains.
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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".