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Record W4399356327 · doi:10.1007/s00894-024-05929-w

The temperature dependence of the Hildebrand solubility parameters of selected hydrocarbon polymers and hydrocarbon solvents: a molecular dynamics investigation

2024· article· en· W4399356327 on OpenAlexafffund
Gabriel P. Costa, Phillip Choi, Stanislav R. Stoyanov, Qi Liu

Bibliographic record

VenueJournal of Molecular Modeling · 2024
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsNatural Resources CanadaUniversity of ReginaUniversity of Alberta
FundersFaculty of Graduate Studies and Research, University of AlbertaUniversity of AlbertaNatural Resources CanadaAlliance de recherche numérique du CanadaGovernment of CanadaGovernment of Alberta
KeywordsHildebrand solubility parameterPolymerThermodynamicsSolubilityCyclohexaneChemistryMaterials sciencePhysical chemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Context To determine the miscibility of liquids at high temperatures using the concept of Hildebrand solubility parameter $$\delta$$ δ , the current practice is to examine the difference in $$\delta$$ δ between two liquids at room temperature, assuming that $$\delta$$ δ is not sensitive to temperature. However, such an assumption may not be valid for certain polymer blends and solutions. Therefore, a knowledge of the δ values of the liquids of interest at high temperatures is desirable. The determination of δ at high temperatures, especially for high-molecular-weight polymers, is impossible, as polymers have vapor pressures of zero. To this end, molecular dynamics (MD) simulations provide a practical means for determining δ over a wide range of temperatures. In this work, we study the temperature dependence of $$\delta$$ δ of five hydrocarbon polymers: polyethylene (PE), isotactic and atactic polypropylene (i-PP and a-PP), polyisobutylene (PIB), and polyisoprene (PI) in five hydrocarbon solvents: n-pentane, n-hexane, n-dodecane, isobutene, and cyclohexane. The polymers are modeled as monodisperse chains with 100 repeat units. The average δ values of PE, i-PP, a-PP, PIB, and PI at 300 K are determined as 18.6, 14.9, 14.6, 14.3, and 16.4 MPa1/2, respectively, in a good agreement with experimental data. The δ values of these polymers at various temperatures are also determined. The temperature dependence of δ is fitted to two linear equations, one above and the other below the polymer’s glass transition temperature Tg. The δ values are more sensitive to temperature at T ≥ Tg. The Tg values of the polymers, determined based upon their specific volumes and δ values agree with the experiment qualitatively. The determination of the temperature dependence of δ has a great potential for industrial applications, such as determining miscibility, developing polymeric organogelators as flocculants and oil spill treating agents, and identifying potential solvents and ideal processing temperatures. Methods The MD simulations are performed using the GROMACS 2022.3 package with optimized potential for liquid simulations-all atom (OPLS-AA) force field parameters. All polymers are built as extended chains using CHARMM-GUI Polymer Builder. Graphical Abstract

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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

Citations15
Published2024
Admission routes2
Has abstractyes

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