Ab Initio Adsorption Thermodynamics of H<sub>2</sub>S and H<sub>2</sub>on Ni(111): The Importance of Thermal Corrections and Multiple Reaction Equilibria
Bibliographic record
Abstract
The presence of trace amounts of H 2 S in H 2 -rich fuel poisons Ni-based solid oxide fuel cell anodes, adversely affecting the electrochemical performance. This study uses density functional theory (DFT) to describe the competitive adsorption thermodynamics of H 2 S and H 2 on Ni(111). Unlike previous DFT-based studies on the H 2 S−H 2 −Ni system, a vibrational analysis of the adsorbates is performed to calculate the thermal corrections to the enthalpy and entropy of the surface species. Parallel adsorption reactions of H 2 on Ni explicitly accounting for coverage effects of the S and H adatoms on the Ni(111) surface are included in the analysis. The resulting equilibrium equations for the multiple adsorption/desorption reactions are then solved to calculate the S and H coverage over a wide range of T, P H 2 S, and P H 2 .This study illustrates the errors introduced in the predicted S coverage if H 2 adsorption in parallel with H 2 S adsorption is neglected or if the thermal corrections to the enthalpy and entropy of reaction are not handled properly.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".