Defect-Rich Dopant-Free ZrO<sub>2</sub> Nanoclusters and Their Size-Dependent Ferromagnetism
Bibliographic record
Abstract
As an intermediate form of matter between a single atom or molecule and the bulk, nanoclusters (NCs) provide novel properties because of their high surface area-to-volume ratios and distinct physical and electronic structures. These ultrasmall NCs offer a new approach to advance charge–spin manipulation for novel devices, including spintronics and magnetic tunneling junctions. Here, we deposit monosized ZrO 2 NCs over a large area by using gas-phase aggregation followed by in situ size selection by a quadrupole mass filter. These size-specific NCs exhibit sub-oxide photoemission features at binding energies that are dependent on the cluster size (from 3 to 9 nm), which are attributed to different oxygen vacancy defect states. These dopant-free ZrO 2 NCs also show strongly size-dependent ferromagnetism, which provides distinct advantages in solubility and homogeneity of magnetism when compared to traditional dilute magnetic semiconductors. A defect-band hybridization-induced magnetic polaron model is proposed to explain the origin of this size-dependent ferromagnetism. This work demonstrates a new protocol of magnetization manipulation by size control and promises potential applications based on these defect-rich size-selected NCs.
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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".