Hf<sub>1–<i>x</i></sub>Zr<sub><i>x</i></sub>O<sub>2</sub>/ZrO<sub>2</sub> Nanolaminate Thin Films as a High-κ Dielectric
Bibliographic record
Abstract
Engineering of HfO 2 –ZrO 2 ferroelectric thin films can substantially increase their dielectric constant. Here, we investigate dielectric and structural properties of ∼10 nm thin films consisting of stacked 1 nm thin ferroelectric (FE) Hf 1– x Zr x O 2 (HZO( x )) and antiferroelectric (AFE) ZrO 2 layers. At x < 0.5, the measurements of polarization vs electric field revealed pure FE hysteresis loops, whereas at x > 0.5, pinched hysteresis loops with some remnant polarization were observed, which indicate a coexistence of FE and AFE orderings. Finally, a pure ZrO 2 thin film ( x = 1) exhibits only an AFE double hysteresis loop. In this way, we demonstrate that the coexistence of FE and AFE orderings can be controlled by adjusting the composition of HZO( x ) layers in the HZO( x )/ZrO 2 nanolaminate films. At x = 0.5, the dielectric constant is ∼60 in nanolaminate films, which is much higher than that of the conventional HZO( x ) solid solution thin films. Structural investigations confirm a coexistence of polar orthorhombic and nonpolar tetragonal structures, which is consistent with the observed polarization hysteresis loops. We also show that the strain generated in the nanolaminate structure significantly facilitates a field-induced transition from the AFE to the FE phase. The design does not considerably affect the leakage current in HZO( x )/ZrO 2 nanolaminate films, which makes this system highly promising for complementary metal oxide semiconductor-compatible capacitors.
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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".