Regioselective magnetization in semiconducting nanorods
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Bibliographic record
Abstract
Chirality—the property of an object wherein it is distinguishable from its mirror image—is of widespread interest in chemistry and biology1–6. Regioselective magnetization of one-dimensional semiconductors enables anisotropic magnetism at room temperature, as well as the manipulation of spin polarization—the properties essential for spintronics and quantum computing technology7. To enable oriented magneto-optical functionalities, the growth of magnetic units has to be achieved at targeted locations on a parent nanorod. However, this challenge is yet to be addressed in the case of materials with a large lattice mismatch. Here, we report the regioselective magnetization of nanorods independent of lattice mismatch via buffer intermediate catalytic layers that modify interfacial energetics and promote regioselective growth of otherwise incompatible materials. Using this strategy, we combine materials with distinct lattices, chemical compositions and magnetic properties, that is, a magnetic component (Fe3O4) and a series of semiconducting nanorods absorbing across the ultraviolet and visible spectrum at specific locations. The resulting heteronanorods exhibit optical activity as induced by the location-specific magnetic field. The regioselective magnetization strategy presented here enables a path to designing optically active nanomaterials for chirality and spintronics. A double-buffer-layer engineering strategy enables the selective growth of magnetic materials at specific locations on a wide variety of semiconducting nanorods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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