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Record W4396882809 · doi:10.6000/jascm.v5i2.3895

New General Models for Evaluating Interactions in Non-Regular Solutions and Adsorption Energies Based on Both Hansen's and Drago's Parameters

2016· article· en· W4396882809 on OpenAlexvenueno aff
Michel Buchmann, Nam-Tran Ho, Roger Lamartine, Isabelle Bonnamour

Bibliographic record

VenueJournal of Applied Solution Chemistry and Modeling · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAdsorptionApplied mathematicsThermodynamicsMathematicsStatistical physicsChemistryPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

This study aims at providing a model for the internal mixing energy of two liquids. The concerned variables are the solute molar volume V (cm3/mol.), the cohesion parameters and the Drago's parameters. The model is based on the following fundamental novelties: The fragmentation of molar cohesive energy ∆Ecoh (kJ/mol) into two distinct categories. Indeed, the dispersive and polar cohesion energies are magnetic and electrical in nature, and the cohesive energy of the chemical bonds (Hydrogen Bond) is due to charge transfer and orbital overlap. The origins of these two categories of energy are different, requiring two different treatments in use. For the first time, a relationship has been established between the cohesive energy from chemical bonds ∆Eh (kJ/mol) and Drago's parameters Ea, Eb, Ca, and Cb (KJ1/ 2mol-1/2). A simple equation has been proposed for the salvation energy of a gaseous solute in a liquid solvent. This equation contains a term for the perturbation energy of the solvent in the presence of the solute, namely the cavity formation energy, and different types of interaction energies between the solvent and the solute at infinite dilution. Based on calorimetric data published, the proposed model is compared with the classic model in terms of the mixing energy. The result shows a clear advantage of the new model over the old or conventional one. Clearly, this new model should provide a new method to determine the interaction parameters or interaction capacities of complex pharmaceutical molecules using a series of simple and well-chosen solvents.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.066
GPT teacher head0.312
Teacher spread0.246 · 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 designSimulation or modeling
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

Citations1
Published2016
Admission routes1
Has abstractyes

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