Quantum Chemical Molecular Dynamics Study of the Water–Gas Shift Reaction on a Pd/MgO(100) Catalyst Surface
Bibliographic record
Abstract
The water–gas shift (WGS) reaction on a Pd/MgO(100) catalyst surface was studied using the tight binding-quantum chemical molecular dynamics (TB-QCMD) method. Molecular adsorption of CO was observed. In contrast, we observed that H 2 O adsorption occurs first molecularly but the molecule then dissociates on the surface. The resultant hydroxyl group reacts with preadsorbed CO to form an OCOH intermediate and a single H atom. This process is relevant as the initial hydroxylation step, and it is part of the catalyzed hydrolysis mechanism. During the molecular dynamics simulation the OCOH intermediate inverted into an H–CO 2 like molecule and finally HCO 2 decomposed to CO 2 and H. Later on, the resultant H interacts with the previously dissociated single H atom (H released from the H–OH dissociation) and forms the WGS product H–H molecule. It was observed that the CO 2 desorbed from the supported Pd cluster while the H 2 molecule remains attached to the Pd cluster during the simulation. The geometries and dissociation energies of water molecules were obtained and the type of adsorption assessed. Chemical changes, changes in electronic and adsorption states, and structural changes were also investigated through TB-QCMD calculations, which indicate that the metal-oxide interface plays an essential role in the catalysis, helping in the dissociation of water and the formation of the OCOH intermediate. The present study indicates that the MgO(100) support has a strong interaction with the Pd catalyst, which may cause an increase in Pd activity as well as enhancement of the metal catalyst dispersion, hence, increasing the rate of the WGS reaction. Furthermore, from the molecular dynamics and electronic structure calculations, we have identified a number of consequences for the interpretation and modeling of the WGS reaction.
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 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 | 0.001 | 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 | 0.001 | 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".