Electronic and Magnetic Properties of Co‐Decorated Molecular Organic Network Adsorbed on Graphene
Bibliographic record
Abstract
Abstract First‐principles calculations based on density functional theory (DFT) are performed for investigating the electronic and magnetic properties of a heterostructure formed by Co‐decorated trimesic acid (TMA) self‐assembling network (SAN) adsorbed on graphene. The concentration and spatial position of Co adatom on graphene is regulated by the architecture of SAN. The obtained optimized geometry shows that Co adatom ends up at the top of a C atom on graphene in the heterostructure. The spin‐polarized calculations upon Co‐SAN/G, illustrate that Co adsorption on top site, which is favored by the self‐assembling network, causes an alternating change in the local density of states (LDOS) of graphene that consequently gives rise to sublattice symmetry‐breaking effects reflected in the different gap opening at K valleys. It is demonstrated that a single Co atom adsorbed on top of a C atom on graphene generates similar physical properties as Co‐SAN/G and, in fact, the SAN acts as a template for patterning Co on graphene without interfering with the magnetic properties originated from the adsorbate. Furthermore, Co atoms in the Co‐SAN/G structure, which are localized on just one sublattice type and separated by 10 Å in a triangular lattice, constitute ferromagnetically aligned spin centers.
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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) | 0.002 | 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".