Quantification and Optimization of Dynamic Kinetic Resolution
Bibliographic record
Abstract
A complete and exact kinetic analysis of the phenomenon of dynamic kinetic resolution is presented. This\nanalysis is applicable to reactions of stable stereoisomeric substrates whose ratios can be controlled and is\nvalid for any set of kinetic conditions within the constraint of first-order and pseudo-first-order processes.\nTwo new linear relationships are found for the dependence of the initial product ratio on the initial substrate\nratio and for the dependence of the final product excess on the initial substrate excess. These relationships\nyield the minimum number of rate constant ratios needed to characterize the energetics of a chemical system\nexhibiting dynamic kinetic resolution completely. A distinct experimental advantage of this method is that it\nis based entirely on product studies. A simple graphical representation of the second linear relationship depicts\nvisually the limiting Curtin−Hammett and anti-Curtin−Hammett conditions. From these conditions, a new\nparameter is defined that characterizes the efficiency of dynamic kinetic resolution and Curtin−Hammett\nefficiency. Simulations based on enantiomeric substrates illustrate how reactions may be optimized using\nthis graphical treatment. An extension of this analysis to related kinetic schemes of varying degrees of\ncomplexity shows that the above linear relationships are universal. Results from these treatments are compared\nwith Noyori's quantitative work on the stereoselective hydrogenation of β-ketoesters. Implications of this\nnew analysis are also discussed in light of previous work done on the applicability of the Winstein−Holness\nand Curtin−Hammett approximations to reactions of substrates that are interconverting conformers. For these\ncases, an alternate definition of Curtin−Hammett efficiency is proposed that is based on the experimental\ndetermination of the initial and final product ratios and the equilibrium constant for substrate interconversion.\nThis unified analysis can be readily applied to a wide variety of synthetic and mechanistic problems in organic\nchemistry where dynamic kinetic resolution is applicable.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.031 | 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".