Robust Room Temperature Ferromagnetism In Cobalt Doped Graphene by Precision Control of Metal Ion Hybridization
Bibliographic record
Abstract
Abstract Graphene‐based magnetic materials exhibit novel properties and promising applications in the development of next‐generation spintronic devices. Modern synthesis techniques have paved the way to design precisely the local environments of metal atoms anchored onto a nitrogen‐doped graphene matrix. Herein, it is demonstrated that grafting cobalt (Co) into the graphene lattice induces robust and stable room‐temperature ferromagnetism. These comprehensive experiments and first‐principles calculations unambiguously identify that the mechanism for this unusual ferromagnetism is π‐ d orbital hybridization between Co d xz and graphene p z orbitals. Here, it is found that the magnetic interactions of Co–carbon ions are mediated by the spin‐polarized graphene p z orbitals, and room temperature ferromagnetism can be stabilized by electron doping. It is also found that the electronic structure near the Fermi level, which sets the nature of spin polarization of graphene p z bands, strongly depends on the local environment of the Co moiety. This is the crucial, previously missing, ingredient that enables control of the magnetism. Overall, these observations unambiguously reveal that engineering the atomic structure of metal‐embedded graphene lattices through careful d to p orbital interactions opens a new window of opportunities for developing graphene‐based spintronics devices.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".