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Record W2041582151 · doi:10.1002/cjce.20646

Molar heat capacities of solvents used in CO<sub>2</sub> capture: A group additivity and molecular connectivity analysis

2011· article· en· W2041582151 on OpenAlexaffvenueabout
Aravind V. Rayer, Amr Henni, Paitoon Tontiwachwuthikul

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsAdditive functionChemistryHeat capacityThermodynamicsMolarGroup contribution methodAtmospheric temperature rangeMolar ratioEnthalpyPhysical chemistryOrganic chemistryPhase equilibriumPhysicsCatalysis

Abstract

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Abstract The molar heat capacities of 38 pure solvents used for CO2 capture studies are reported in the temperature range of 303.15–393.15 K and atmospheric pressure. Existing structural similarities between these compounds were explored using a group additivity analysis (GAA) and molecular connectivity principles in terms of the reported heat capacity data. Group additivity yields the estimates of CH3, CH2, CH, C, CH, NH2, NH, N, N–, OH, O and O group contributions to the molar heat capacities at each investigated temperature. Molecular connectivity approach provides a single equation that models the molar heat capacities of amines over the investigated temperature range. Absolute average deviations for the GAA were found to be <2.5%, and <3% for the molecular connectivity analysis. The developed equations were tested by predicting the molar heat capacities of solvents newly proposed for CO2 capture. Les capacités calorifiques molaires de trente huit (38) solvants purs utilisés pour les études de capture du CO2 sont rapportées dans la gamme de température de (303.15 à 393.15) K et à pression atmosphérique. Les similitudes structurelles existantes entre ces composés ont été explorées à l'aide d'une analyse additivité de groupe et les principes de connectivité moléculaire en termes de capacité thermique. L'analyse fournit les estimations de la contribution des groups CH3, CH2, CH, C, CH, NH2, NH, N, N–OH, O et S = aux capacités calorifiques molaires à chaque température étudiée. L'approche de connectivité moléculaire fournit une seule équation qui modélise les capacités calorifiques molaires des amines dans l'intervalle de température étudié. Les écarts absolus moyens pour l'analyse additivité des groupes ont été de moins de 2.5%, et de moins de 3% pour l'analyse de la connectivité moléculaire. Les équations développées ont été testées en prédisant les capacités calorifiques molaires des solvants nouvellement proposés pour la capture du CO2. © 2011 Canadian Society for Chemical Engineering

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.170
Teacher spread0.162 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations26
Published2011
Admission routes3
Has abstractyes

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