Metadynamics-Biased ab Initio Molecular Dynamics Study of Heterogeneous CO<sub>2</sub> Reduction via Surface Frustrated Lewis Pairs
Bibliographic record
Abstract
The recent discovery of frustrated Lewis pairs (FLPs) capable of heterolytically splitting hydrogen gas at the surface of hydroxylated indium oxide (In 2 O 3– x (OH) y ) nanoparticles has led to interesting implications for heterogeneous catalytic reduction of CO 2 . Although the role of surface FLPs in the reverse water-gas shift (RWGS) reaction (CO 2 + H 2 → CO + H 2 O) has been experimentally and theoretically demonstrated, the interplay between surface FLPs and temperature and their consequences for the reaction mechanism have yet to be understood. Here we use well-tempered metadynamics-biased ab initio molecular dynamics to obtain the free energy landscape of the multistep RWGS reaction at finite temperatures. The reaction is simulated at 20 and 180 °C, and the minimum energy reaction pathways and energy barriers corresponding to H 2 dissociation and CO 2 reduction are obtained. The reduction of CO 2 at the surface FLP catalytically active site, where H 2 is heterolytically dissociated and bound, is found to be the rate-limiting step and is mostly unaffected by increased temperature conditions; however, at 180 °C the energetic barriers associated with the splitting of H 2 and the subsequent adsorption of CO 2 are reduced by 0.15 and 0.19 eV, respectively. It is suggested that increased thermal conditions may enhance reactivity by enabling the surface FLP to become further spatially separated. Product H 2 O is found to favor dissociative adsorption over direct desorption from the surface of In 2 O 3– x (OH) y and may therefore impede sustained catalytic activity by blocking surface sites.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".