Electronic Properties of Self-Assembled Trimesic Acid Monolayer on Graphene
Bibliographic record
Abstract
The adsorption of trimesic acid (TMA) on a graphene surface has been studied with density functional theory. By considering the adsorption of a single TMA molecule on different sites on graphene, we have been able to perform a detailed analysis of the equilibrium geometry, charge transfer, electronic properties in terms of density of states and band structure, and finally scanning tunneling microscopy simulations on those simple systems. The results for isolated adsorption were then compared to the behavior of the TMA unit within two different self-assembled monolayers. Our results indicate that structural deformations of TMA may significantly contribute to the magnitude of p-doping and band gap opening in graphene. The formation of a hydrogen bonding network within the assembly improves the stability of the adlayer, but its adhesion on graphene is significantly reduced. The magnitude of p-doping in graphene per TMA unit remains nearly constant from the isolated to the assembled systems, but the magnitude of the band gap opening appears to be strongly correlated with the breaking of symmetry of π-states of graphene by the TMA patterning on the surface. Our results suggest that polymorphism in self-assembled adlayers could be used to tune and control the electronic properties of graphene.
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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".