New-phase retention in colloidal core/shell nanocrystals <i>via</i> pressure-modulated phase engineering
Bibliographic record
Abstract
Core/shell nanocrystals (NCs) integrate collaborative functionalization that would trigger advanced properties, such as high energy conversion efficiency, nonblinking emission, and spin-orbit coupling. Such prospects are highly correlated with the crystal structure of individual constituents. However, it is challenging to achieve novel phases in core/shell NCs, generally non-existing in bulk counterparts. Here, we present a fast and clean high-pressure approach to fabricate heterostructured core/shell MnSe/MnS NCs with a new phase that does not occur in their bulk counterparts. We determine the new phase as an orthorhombic MnP structure (B31 phase), with close-packed zigzagged arrangements within unit cells. Encapsulation of the solid MnSe nanorod with an MnS shell allows us to identify two separate phase transitions with recognizable diffraction patterns under high pressure, where the heterointerface effect regulates the wurtzite → rocksalt → B31 phase transitions of the core. First-principles calculations indicate that the B31 phase is thermodynamically stable under high pressure and can survive under ambient conditions owing to the synergistic effect of subtle enthalpy differences and large surface energy in nanomaterials. The ability to retain the new phase may open up the opportunity for future manipulation of electronic and magnetic properties in heterostructured nanostructures.
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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".