Energy Level Alignment at Hybridized Organic–Metal Interfaces: The Role of Many-Electron Effects
Bibliographic record
Abstract
Hybridized molecule/metal interfaces are ubiquitous in molecular and organic devices. The energy level alignment (ELA) of frontier molecular levels relative to the metal Fermi level ( E F ) is critical to the conductance and functionality of these devices. However, a clear understanding of the ELA that includes many-electron self-energy effects is lacking. Here, we investigate the many-electron effects on the ELA using state-of-the-art, benchmark GW calculations on prototypical chemisorbed molecules on Au(111), in eleven different geometries. The GW ELA is in good agreement with photoemission for monolayers of benzene diamine on Au(111). We find that in addition to static image charge screening, the frontier levels in most of these geometries are renormalized by additional screening from substrate-mediated intermolecular Coulomb interactions. For weakly chemisorbed systems, such as amines and pyridines on Au, this additional level renormalization (∼1.5 eV) comes solely from static screened exchange energy, allowing us to suggest computationally more tractable schemes to predict the ELA at such interfaces. However, for more strongly chemisorbed thiolate layers, dynamical effects are present. Our ab initio results constitute an important step toward the understanding and manipulation of functional molecular/organic systems for both fundamental studies and applications.
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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 | 0.000 | 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) | 0.000 | 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".