Olefin Metathesis in Water: Speciation of a Leading Water-Soluble Catalyst Pinpoints Challenges and Opportunities for Chemical Biology
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The metathetical modification of biomolecules in aqueous environments holds great promise for advances at the interface of chemistry, biology, and medicine. However, rapid degradation of the metathesis catalysts necessitates their use in large stoichiometric excess, resulting in undesired side-reactions promoted by the ruthenium products. Although water is now known to play a central role in catalyst decomposition, the elusive nature of the intermediates has hampered insight into the pathways involved. We describe the detailed speciation in water of AquaMet ( AM ), the dominant ruthenium catalyst used for aqueous metathesis, and implications for catalysis. Potentiometric and spectroscopic speciation studies reveal that only trace AM is present under the pH-neutral, salt-free conditions routinely employed in synthetic applications of aqueous metathesis. Instead, metathesis-inactive hydroxide species dominate. Even at pH 3, Ru–H 2 O complexes dominate in 0.01 M NaCl (aq), and the water ligands are readily deprotonated as the pH is increased. Raising NaCl (aq) concentrations to 1 M suppresses deprotonation events below pH 8, stabilizing AM as the dominant solution species at neutral pH, and significantly expanding the metathesis-compatible regime. Hitherto unrecognized catalyst solubility issues are also revealed, pointing toward avenues for advance. More broadly, the capacity to directly link catalyst environment to structure and performance opens new opportunities for olefin metathesis in complex, water-rich settings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".