Ruthenium triphos complexes [Ru(X(CH<sub>2</sub>PPh<sub>2</sub>)<sub>3</sub>-<i>κ</i><sup>3</sup>-P)(NCCH<sub>3</sub>)<sub>3</sub>](OTf)<sub>2</sub>; X = H<sub>3</sub>C-C, N) as catalysts for the conversion of furfuryl acetate to 1,4-pentanediol and cyclopentanol in aqueous medium
Bibliographic record
Abstract
The ruthenium complexes [Ru(H 3 CC(CH 2 PPh 2 ) 3 -κ 3 -P)(NCCH 3 ) 3 ](OTf) 2 (1, (H 3 CC(CH 2 PPh 2 ) 3 = triphos) and [Ru(N(CH 2 PPh 2 ) 3 -κ 3 -P)(NCCH 3 ) 3 ](OTf) 2 (2, N(CH 2 PPh 2 ) 3 = N-triphos) have been evaluated as homogeneous ionic hydrogenation catalysts for the catalytic hydrodeoxygenation of furfuryl alcohol and furfuryl acetate to 1,4-pentanediol and cyclopentanol in aqueous media reaction mixtures. For furfuryl alcohol, only marginal yields of 1,4-pentanediol could be achieved with mass balance deficiencies due to humin formation ranging from 67% to 90%. Attempts to improve the catalytic activity of 2 by enhancing its water solubility by nitrogen protonation and (or) methylation failed. Employing the less self-reactive furfuryl acetate as the substrate substantially diminishes humin formation, yielding up to 43% of 1,4-pentanediol and 19% of cyclopentanol (via Piancatelli rearrangement) with 1 and up to 33% of 1,4-pentanediol and 5% of cyclopentanol with 2. A design of experiments study was used to determine and compare the yield responses of the multiple parallel reaction channels with 1,4-pentanediol, cyclopentanol, and humins as a function of reaction temperature, time, catalyst load, and substrate concentration. This explores the correlations between these parameters and their impact on the reaction outcome and suggests an extremely complex overall reaction cascade of interdependent pathways of both acid- and metal-catalyzed steps with some significant differences emerging between the two catalysts.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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; both teacher heads agree on what is shown here.
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".