Adsorption and Dissociation of H<sub>2</sub>O on Monolayered MoS<sub>2</sub> Edges: Energetics and Mechanism from <i>ab Initio</i> Simulations
Bibliographic record
Abstract
The dissociation of water on 2D monolayer molybdenum disulfide (MoS 2 ) edges was studied with density functional theory. The catalytically active sites for H 2 O, H, and OH adsorption on MoS 2 edges with 0% (Mo-edge), 50% (S50-edge), and 100% (S100-edge) sulfur coverage were determined, and the Mo-edge was found to be the most favorable for adsorption of all species. The water dissociation reaction was then simulated on all edges using the climbing image nudged elastic band (CI-NEB) technique. The reaction was found to be endothermic on the S100-edge and exothermic for the S50- and Mo-edges, with the Mo-edge having the lowest activation energy barrier. Water dissociation was then explored on the Mo-edge using metadynamics biased ab initio molecular dynamics (AIMD) methods to explore the reaction mechanism at finite temperature. These simulations revealed that water dissociation can proceed by two mechanisms: the first by splitting into adsorbed OH and H species produced a particularly small activation free energy barrier of 0.06 eV (5.89 kJ/mol), and the second by formation of desorbed H 2 and adsorbed O atom had a higher activation barrier of 0.36 eV (34.74 kJ/mol) which was nevertheless relatively small. These activation barrier results, along with reaction rate calculations, suggest that water dissociation will occur spontaneously at room temperature on the Mo-edge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".