Electrically modulated photothermal force microscopy for revealing molecular conformation changes during polarization switching at the nanoscale
Bibliographic record
Abstract
Organic ferroelectrics have attracted extensive attention because of the broad tunability of polarization via chemical and structural modifications. However, simultaneous analysis of the evolution of chemical and polarization properties at the nanoscale remains a challenge, impeding the understanding of their origin. In this work, we report electrically modulated photothermal force microscopy (ePTFM), an atomic force microscopy (AFM)-based technique that integrates nanoscale analysis of polarization with chemical specificity. By characterizing electrodriven ferroelectric switching in edge-on poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) lamellae, ePTFM reveals not only the evolution of polarization but also in situ chemical correlations. The results show that ePTFM has less electrostatic interference than conventional AFM techniques do, allowing intrinsic characterization of polar evolution under bias. Furthermore, via multi-wavenumber analysis, we propose a conformational mechanism for chain-direction ferroelectric switching in face-on P(VDF-TrFE). The proposed ePTFM provides fresh insight into polarization evolution and paves the way for mechanistic studies of polar organics.
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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 | 0.001 |
| 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".