Rationalizing Solvent Effect in Bronsted Acid-Catalyzed C–O Scission: A Thermodynamically Consistent Framework with Assessable Descriptors
Bibliographic record
Abstract
Rates of unimolecular C–O bond scission across a broad library of structurally diverse alkanol and ether reactant and chemically distinct solvent (protophilic, protophobic, and protogenic) pairs catalyzed by solid Bro̷nsted acid (Amberlyst 15) span 6 orders of magnitude (338 K) without clear reactivity trends. We capture this apparently complex and unpredictable solvent-induced rate modulation with a simple thermochemical framework, decoupling the solvent and reactant-dependent contributions within the context of excess free energies of the transition states and acid sites. Within this model, we decompose the reaction excess activation free energies, the difference in activation free energies between liquid–solid and vapor–solid interfaces, into the sum of two physically distinct energetic components: (1) the excess adsorption free energy of a probe molecule (methanol), which implicitly captures all solvent–H + interactions at the interface, that is reactant-independent and experimentally measurable; and (2) an electrostatic correction term, expressed as the product between a regressed transition state polarity parameter and the effective dielectric constant of the solvent, which captures differences in dielectric screening by solvent molecules around transition states polarized to different extents relative to that of the probe molecule. This model predicts all measured excess activation free energies, spanning across 36 kJ mol –1 across all reactant–solvent pairs, within a mean error of 2.3 kJ mol –1 at 338 K. These findings demonstrate that, despite their apparent complexities, solvent effects on intrinsic catalytic rates remain well-governed by fundamental thermodynamic principles.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".