Reaction kinetics of hydrogen atom abstraction from isopentanol by the H atom and HO<sub>2</sub>˙ radical
Bibliographic record
Abstract
Isopentanol is a potential next-generation biofuel for future applications to Homogeneous Charge Compression Ignition (HCCI) engine concepts. To provide insights into the combustion behavior of isopentanol, especially to its auto-ignition behavior which is linked both to efficiency and pollutant formation in real combustion systems, detailed quantum chemical studies for crucial reactions are desired. H-Abstraction reaction rates from fuel molecules are key initiation steps for chain branching required for auto-ignition. In this study, rate constants are determined for the hydrogen atom abstraction reactions from isopentanol by the H atom and HO2˙ radical by implementing the CBS-QB3 composite method. For the treatment of the internal rotors, a Pitzer-Gwinn-like approximation is applied. On comparing the computed reaction energies, the highest exothermicity (ΔE = -46 kJ mol-1) is depicted for Hα abstraction by the H atom whereas the lowest endothermicity (ΔE = 29 kJ mol-1) is shown for the abstraction of Hα by the HO2˙ radical. The formation of hydrogen bonding is found to affect the kinetics of the H atom abstraction reactions by the HO2˙ radical. Further above 750 K, the calculated high pressure limit rate constants indicate that the total contribution from delta carbon sites (Cδ) is predominant for hydrogen atom abstraction by the H atom and HO2˙ radical.
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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 | 0.000 | 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) | 0.003 | 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".