Tuning Magnetic States of Planar Graphene/<i>h-</i>BN Monolayer Heterostructures via Interface Transition Metal-Vacancy Complexes
Bibliographic record
Abstract
Planar graphene/ h -BN (GPBN) heterostructures promise low-dimensional magnetic semiconductor materials of tunable bandgap. In the present study, interplay between 3d transition metal (TM) atoms and single vacancies (SVs) at the armchair interface in a planar GPBN monolayer was investigated through first principle density functional theory calculations. The TM-SV complexes were found to give rise to a rich set of magnetic states, originated from the interactions between valence electrons of the TM atom with dangling orbitals at the SV. The magnetic state at a TM-SV complex was further shown to be tunable upon the application of strain and electric field. The present study suggests a route to enrich and engineer the magnetic states of planar GPBN heterostructures, providing new insights for the design of tunable low-dimensional spintronic devices.
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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".