Supramolecular Ordering of PTCDA Molecules: The Key Role of Dispersion Forces in an Unusual Transition from Physisorbed into Chemisorbed State
Bibliographic record
Abstract
Adsorption and self-assembly of large π-conjugated 3,4,9,10-perylene tetracarboxylic dianhydride (PTCDA) molecules on rutile TiO(2)(110) surface have been investigated using a combination of high-resolution scanning tunneling microscopy (STM), low-energy electron diffraction, and density functional theory calculations with inclusion of Grimme treatment of the dispersion forces (DFT-D). Evolution of the STM images as a function of PTCDA coverage is caused by transition of the adsorption mode from physisorbed single adspecies and meandering stripes into spontaneously ordered chemisorbed molecular assemblies. This change in the adsorption fashion is accompanied by significant bending of the intrinsically flat, yet elastic, PTCDA molecule, which allows for strong electronic coupling of the dye adspecies with the TiO(2) substrate. Extensive DFT-D modeling has revealed that adsorption is controlled by interfacial and intermolecular dispersion forces playing a dominant role in the adsorption of single PTCDA species, their self-organization into the meandering stripes, and at the monolayer coverage acting collectively to surmount the chemisorption energy barrier associated with the molecule bending. Analysis of the resulting density of states has revealed that alignment of the energy levels and strong electronic coupling at the PTCDA/TiO(2) interface are beneficial for dye sensitization purposes.
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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".