Density Functional Theory Study of Pyrrole Adsorption on Mo(110)
Bibliographic record
Abstract
The objective of the present study is to identify possible adsorption configurations of pyrrole on Mo(110) using density functional theory (DFT) calculations. Several adsorption configurations were studied including pyrrole and pyrrolyl adsorption as parallel, perpendicular, and tilted adsorption modes relative to the Mo(110) surface plane. Based on the DFT calculations, pyrrole is suggested to adsorb in a parallel mode with respect to the Mo(110) surface through its pi-orbital as mu3,eta(5)-Pyr-0 degrees with an adsorption energy of -28.7 to -31.5 kcal mol(-1). The possibility of a coexisting mode where pyrrole adsorbs on the surface with a slightly tilted molecular plane as mu3,eta(4)(N,C2,C3,C4)-Pyr-5 degrees is also likely to occur, particularly at higher pyrrole coverages. The slightly tilted configuration is suggested to arise from the lateral interactions of adsorbed pyrrole on Mo(110), and not the result of a phase transformation on the surface since this requires a relatively high activation energy as indicated by additional linear synchronous transit (LST)/quadratic synchronous transit (QST) calculations. Both adsorption geometries bond to three surface Mo atoms, and Mo(110) did not promote hydrogen abstraction. Pyrrolyl adsorption on Mo(110) is energetically possible, but unlikely to occur because gas-phase hydrogen has not been previously experimentally observed as a pyrrole decomposition product on Mo(110).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".