Hf<sub><i>x</i></sub>Zr<sub>1–<i>x</i></sub>O<sub>2</sub> Solid Solution Nanoclusters with Size-Specific Bandgaps
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Bibliographic record
Abstract
Combining zirconia and hafnia into a bimetallic oxide such as HZO (Hf 0.5 Zr 0.5 O 2 ) has attracted a lot of interest because the introduction of a novel orthorhombic phase with intrinsic polarization in HZO has led to strong ferroelectric properties. Here, we use a gas-phase aggregation technique to produce size-specific Hf x Zr 1– x O 2 ( x < 1) hybrid nanoclusters (NCs), which can be precisely tuned from 4 to 14 nm in size while adjusting the Zr and Hf composition, as demonstrated by detailed characterization of their morphologies and chemical states. The crystallinity of the hybrid NCs is found to vary with the NC size obtained under specific deposition conditions, from amorphous for small NCs < 6 nm to single crystalline for 6–10 nm NCs to core–shell for NCs with higher Hf content and polycrystalline NCs with high Zr content for larger NCs > 10 nm. For the single-crystalline Hf x Zr 1– x O 2 NCs, we observe, for the first time for NCs, the special orthorhombic ( Pbc 2 1 ) structure found previously only in the HZO film prepared under extreme conditions. The measured bandgaps of these NCs are found to increase with the cluster size, in contrast to the increase in the bandgap with decreasing size generally found in NCs. The X-ray photoelectron spectra clearly show, in the Zr 3d region, components that can be attributed to oxygen vacancy defects and the substitution of Hf for Zr in the lattice. A new model involving Hf-induced electron polarization is proposed to describe the physical and electronic structures of these novel bimetallic hybrid oxide NCs. This work establishes a general formation protocol for other hybrid semiconductor NCs, while the Hf x Zr 1– x O 2 ( x < 1) NCs with novel phase and polarization could provide promising electrical properties for the next-generation nonvolatile memory device applications.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it