MétaCan
Menu
Back to cohort
Record W2611404385 · doi:10.1063/1.4993572

Molecular simulation of caloric properties of fluids modelled by force fields with intramolecular contributions: Application to heat capacities

2017· article· en· W2611404385 on OpenAlexafffund
William R. Smith, Jan Jirsák, Ivó Nezbeda, Weikai Qi

Bibliographic record

VenueThe Journal of Chemical Physics · 2017
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of GuelphOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaGrantová Agentura České RepublikyAgence Nationale de la Recherche
KeywordsCaloric theoryIntramolecular forceForce field (fiction)MechanicsMolecular dynamicsStatistical physicsMaterials sciencePhysicsThermodynamicsChemistryComputational chemistry

Abstract

fetched live from OpenAlex

The calculation of caloric properties such as heat capacity, Joule-Thomson coefficients, and the speed of sound by classical force-field-based molecular simulation methodology has received scant attention in the literature, particularly for systems composed of complex molecules whose force fields (FFs) are characterized by a combination of intramolecular and intermolecular terms. The calculation of a thermodynamic property for a system whose molecules are described by such a FF involves the calculation of the residual property prior to its addition to the corresponding ideal-gas property, the latter of which is separately calculated, either using thermochemical compilations or nowadays accurate quantum mechanical calculations. Although the simulation of a volumetric residual property proceeds by simply replacing the intermolecular FF in the rigid molecule case by the total (intramolecular plus intermolecular) FF, this is not the case for a caloric property. We describe the correct methodology required to perform such calculations and illustrate it in this paper for the case of the internal energy and the enthalpy and their corresponding molar heat capacities. We provide numerical results for cP, one of the most important caloric properties. We also consider approximations to the correct calculation procedure previously used in the literature and illustrate their consequences for the examples of the relatively simple molecule 2-propanol, CH3CH(OH)CH3, and for the more complex molecule monoethanolamine, HO(CH2)2NH2, an important fluid used in carbon capture.

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 score0.418
Threshold uncertainty score0.235

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Chemical PhysicsSame topicPhase Equilibria and ThermodynamicsFrench-language works237,207