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Record W1984802922 · doi:10.1002/aic.10344

Comparison of ab initio and group additive ideal gas heat capacities

2004· article· en· W1984802922 on OpenAlexafffund
Robert A. Marriott, Mary Anne White

Bibliographic record

VenueAIChE Journal · 2004
Typearticle
Languageen
FieldChemistry
TopicChemical Thermodynamics and Molecular Structure
Canadian institutionsDalhousie University
FundersKillam Trusts
KeywordsAb initioHeat capacityAdditive functionChemistryThermodynamicsIdeal gasComputational chemistryMoleculeStandard enthalpy of formationBasis setIdeal (ethics)Ab initio quantum chemistry methodsPhysical chemistryDensity functional theoryPhysicsMathematicsOrganic chemistry

Abstract

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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

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.263
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2004
Admission routes2
Has abstractyes

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