Accurate entropy calculation for large flexible hydrocarbons using a multi-structural 2-dimensional torsion method
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
Entropy is one of the key thermodynamic parameters in combustion kinetic modeling. Accurate entropy prediction needs to account for the conformational torsional anharmonicity, which could be solved by the state-of-the-art multi-structural torsion (MS-T) method. However, this method is computationally expensive or even not feasible for large flexible molecules. To address this issue, we proposed a multi-structural 2-dimensional torsion (MS-2DT) method that adopts minimally coupled torsions to reduce the computational cost. In this method, a series of 2-dimensional coupled torsion combinations were used to generate an initial conformer space with a size of CN2·9 (N is the number of torsions). The standard entropy (and the heat capacity) values of 18 C6-C8 alkanes with 5-7 torsions were computed at 200-2000 K. The MS-2DT calculation is in good agreement with the benchmark MS-T method: only a small deviation of -0.19 ± 0.15 cal mol-1 K-1 in standard entropy and -0.10 ± 0.21 cal mol-1 K-1 in heat capacity. Additionally, a further application of MS-2DT to n-decane with 9 torsions implies an improved accuracy in entropy (and heat capacity) prediction compared to other conventional simplified treatments. This method provides an affordable and accurate solution to treat the conformational torsional anharmonicity of large flexible alkanes.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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