Emergence of Ferroelectricity in p‐Type 2D In<sub>1.75</sub>Sb<sub>0.25</sub>Se<sub>3</sub>
Bibliographic record
Abstract
p‐type 2D ferroelectric semiconductors (2D FeSs) play an increasingly essential role in the advanced nonvolatile and morphotropic beyond‐Moore electronic devices with high performance and low power consumption. But reliable p‐type 2D FeS with holes as majority carriers are still scarce. Herein, the first experimental realization of room‐temperature ferroelectricity in van der Waals layered β‐In1.75Sb0.25Se3 down to few layer is reported. The origin of ferroelectricity in β‐In1.75Sb0.25Se3 comes from aliovalent elemental substitution, antimony substituting to the indium sites (SbIn), changing the local environment of the central‐layer Se atoms. Thanks to the intrinsic ferroelectric and semiconducting natures, FeS field‐effect transistor (FeSFET) devices based on β‐In1.75Sb0.25Se3 exhibit reconfigurable, multilevel nonvolatile memory (NVM) states, which can be successively modulated by gate voltage stimuli. Furthermore, the inherent operation mechanism, due to the switchable polarization, indicates that a neuromorphic memory is also possible with 2D FeSFETs. These presented results facilitate the technological implementation of versatile 2D FeS devices for next‐generation logic‐in‐memory approach for Internet‐of‐Things entities.
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) | 0.001 | 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".