Getting Ring‐Closing Metathesis off the Bench: Reaction‐Reactor Matching Transforms Metathesis Efficiency in the Assembly of Large Rings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Reported is the first study of the influence of reactor configuration on the efficiency of a challenging ring-closing metathesis (RCM) reaction. With the intention of increasing the generality of RCM scaleup and reducing its dependence on substrate modification, macrocyclization of an unmodified, low effective-molarity diene was explored using different reactor types, in conjunction with a commercial, homogeneous Grubbs catalyst. Optimized performance is compared for a conventional batch reactor (BR), a continuous plug-flow reactor (PFR), and a continuous stirred-tank reactor (CSTR). In the PFR, maximum conversion is achieved most rapidly, but product yields and selectivity are adversely affected by co-entrapment of ethylene with the catalyst, substrate, and product in the traveling "plug". Use of the CSTR, in which ethylene is efficiently swept out, affords an order-of-magnitude increase in total turnover numbers, and reduces the required catalyst loadings by 25× relative to the BR (to 0.2 mol %), while improving RCM yields and selectivity to quantitative levels. Continuous-flow methodologies that support liberation of the ethylene co-product thus show great promise for industrial uptake of RCM.
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.
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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it