Comparison of ab initio and group additive ideal gas heat capacities
Bibliographic record
Abstract
Abstract Three case studies comparing molecular ideal gas heat capacity estimations using empirical group additive methods and statistical mechanical methods using ab initio vibrational frequencies are reported. In the first study, results from several ab initio levels of theory are compared with the experimental heat capacities of piperidine and the heat capacities calculated from the observed vibrational frequencies. In the second study, heat capacities for a benchmark group of 27 organic molecules were calculated using vibrational frequencies from AM1, HF/3‐21G(d), and B3LYP/6‐31G(d) theory level, and the results were compared to three recently updated additivity schemes. In the third study, semiempirical corrections to the heat capacities of n‐alkanes were investigated. The strength of additivity schemes is that they are easy to use and understand, and often give reasonable results, but predict the same thermodynamic properties for isomers containing the same functional groups, and are of limited accuracy when the near‐neighbor interactions are strong or if the input data set is not appropriate. Ab initio vibrational frequencies can rapidly provide accurate heat capacities using the harmonic oscillator model, especially if one conformer dominates. The results can be comparable to additivity, and better for rigid molecules containing heteroatoms. Furthermore, ab initio results do not require a calibration data set. © 2004 American Institute of Chemical Engineers AIChE J, 51: 292–297, 2005
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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) | 0.000 | 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 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".