Orientation-Dependent Work-Function Modification Using Substituted Pyrene-Based Acceptors
Bibliographic record
Abstract
Abstract The adsorption of molecular acceptors is a viable method for tuning the work function of metal electrodes. This, in turn, enables adjusting charge injection barriers between the electrode and organic semiconductors. Here, we demonstrate the potential of pyrene-tetraone (PyT) and its derivatives dibromopyrene-tetraone (Br-PyT) and dinitropyrene-tetraone (NO2-PyT) for modifying the electronic properties of Au(111) and Ag(111) surfaces. The systems are investigated by complementary theoretical and experimental approaches, including photoelectron spectroscopy, the X-ray standing wave technique, and density functional theory simulations. For some of the investigated interfaces the trends expected for Fermi-level pinning are observed, i.e., an increase of the metal work function along with increasing molecular electron affinity and the same work function for Au and Ag with monolayer acceptor coverage. Substantial deviations are, however, found for Br-PyT/Ag(111) and NO2-PyT/Ag(111), where in the latter case an adsorption-induced work function increase of as much as 1.6 eV is observed. This behavior is explained as arising from a face-on to edge-on reorientation of molecules in the monolayer. Our calculations show that for an edge-on orientation much larger work-function changes can be expected despite the prevalence of Fermi-level pinning. This is primarily ascribed to a change of the electron affinity of the adsorbate layer that results from a change of the molecular orientation. This work provides a comprehensive understanding of how changing the molecular electron affinity as well as the adsorbate structure impacts the electronic properties of electrodes.
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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".