Challenges in Predicting Δ<sub>rxn</sub><i>G</i>in Solution: The Mechanism of Ether-Catalyzed Hydroboration of Alkenes
Bibliographic record
Abstract
Ab initio (coupled-cluster and density-functional) calculations of Gibbs reaction energies in solution, with new entropy-of-solvation damping terms, were performed for the ether-catalyzed hydroboration of alkenes. The goal was to test the accuracy of continuum-solvation models for reactions of neutral species in nonaqueous solvents, and the hope was to achieve an accuracy sufficient to address the mechanism in the "Pasto case": B2H6 + alkene in THF solvent. Brown's SN2/SN1 "dissociative" mechanism, of SN2 formation of borane-ether adducts followed by SN1 alkene attack, was at odds with Pasto's original SN2/SN2 hypothesis, and while Brown could prove his mechanism for a variety of cases, he could not perform the experimental test with THF adducts in THF solvent, where the higher THF concentrations might favor an SN2 second step. Two diboranes were tested: B2H6, used by Pasto, and (9BBN)2 (9BBN = 9-borabicyclo[3.3.1]nonane, C8H15B), used by Brown. The new entropy terms resulted in improved accuracy vs traditional techniques (∼2 kcal mol(-1)), but this accuracy was not sufficient to resolve the mechanism in the Pasto case.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".