How Solvent Mediates the Catalytic Fate of 2-Methoxyphenol in Hydrodeoxygenation Catalysis?
Bibliographic record
Abstract
Kinetic and isotopic assessments combined with theoretical calculations shed light on the mechanistic differences in terms of the number of hydrogen addition steps and the electronic charges of reactive hydrogen in the catalytic sequence leading to the Ar–OCH 3 scission of 2-methoxyphenol occurring at various interfaces of vapor–Ru, cyclohexane–Ru, and water–Ru. At vapor–Ru and cyclohexane–Ru interfaces, the initial hydrogen adatom (H*) additions on the phenyl ring disrupt its aromaticity, as a step required to occur before kinetically relevant Ar–OCH 3 scission on an ensemble of Ru sites. The number of H* addition events prerequisite to the formation of the kinetically relevant Ar–OCH 3 scission transition state, however, is larger at the cyclohexane–Ru interface than those at the vapor–Ru and water–Ru interfaces. The preferential solvation of 2-methoxyphenol derived reaction precursors and H* weakens their adsorption on Ru sites, which leads to a decrease in the activation barrier for the third H* addition step and in turn a larger number of H* additions. At the water–Ru interface, water as a polar protic solvent promotes the Ar–OCH 3 scission by enabling a mechanistically distinct catalytic route─an adjacent water molecule from the solvent layer assists with the intramolecular proton shuttling from the hydroxyl group (−OH) to the vicinal methoxy group (−OCH 3 ) of 2-methoxyphenol, evolving a highly charged transition state that is further stabilized by the water solvent layer, thereby leading to Ar–OCH 3 scission rate constants that are much higher than those at the vapor–Ru interface and, when comparing at the same H 2 chemical potential, higher Ar–OCH 3 scission turnovers. These distinct mechanistic details of the Ar–OCH 3 scission at various reaction interfaces, inferred from experiment and theory, illustrate how a solvent either solvates reaction intermediates and transition states or directly participates in the formation of kinetically relevant transition states, leading to changes in the free energy landscape, thus rewriting the catalytic fates in hydrodeoxygenation reactions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".