Sliding ferroelectricity-induced triple barrier modulation in van der Waals boron arsenide tunnel junctions
Bibliographic record
Abstract
To develop low-power, miniature, nonvolatile memory resistor integrated devices for in-memory computing technologies, the exploration of atomic-scale ferroelectric channel semiconductor devices is necessary. We theoretically designed tunnel junction devices based on two-dimensional ferroelectric semiconductors, with two-dimensional metal TaSe2 used as the top electrode and van der Waals bilayer boron arsenide (BAs) as the ferroelectric semiconductor channel, aiming to achieve high-performance, low-power, two-dimensional ferroelectric memory resistors. Our findings demonstrate that the bilayer BAs, upon contact with metal electrodes, can achieve two stable and switchable ferroelectric states. Interlayer relative sliding enables stable and alternating two-dimensional ferroelectric domains, altering the types of triple potential barriers at interfaces from Schottky contacts to Ohmic contacts. Thus, under the modulation of the “triple barrier” mechanism, control over channel carrier switching is achieved, resulting in a tunneling electroresistance of 104%. Additionally, non-equilibrium Green's function results indicate nonlinear changes in the I–V curve when switching between the two stable ferroelectric states, highlighting the multi-resistive state nature of channel resistance. Our research underscores the potential of sliding ferroelectric tunnel junctions in integrating nonvolatile storage and computing units, emphasizing their innovative applications in in-memory computing technologies.
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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) | 0.000 | 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".