On the Existence of Negative Capacitance: Examining Ferroelectric-Dielectric Stack Experiments Using the NLS and LK Models
Bibliographic record
Abstract
The Landau–Khalatnikov (LK) model of ferroelectric switching includes an inherent region of negative capacitance (NC) in its lossless charge versus voltage description and allows the possibility of stabilization of the ferroelectric in this region to achieve quasi-static NC (QSNC). On the other hand, the nucleation-limited switching (NLS) model, which is another model used to describe ferroelectric switching, precludes QSNC and offers an alternative explanation for the appearance of an NC region in recent voltage-pulse experiments performed on ferroelectric-dielectric (FE-DE) stacks. As such, we investigate such experiments that probe the existence of an NC region using both the LK and NLS models. While the LK model can reproduce all experimental results seen in prior literature, we find that the NLS model is incapable of properly reproducing results under a multitude of investigation metrics. Hence, we conclude that the use of the NLS model to exclude the existence of QSNC is problematic.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".