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Record W4234156068 · doi:10.26434/chemrxiv-2021-4j8z6

Effects of molecular design parameters on plasticizer performance in poly(vinyl chloride): a comprehensive molecular simulation study

2021· preprint· en· W4234156068 on OpenAlexafffund
Dongyang Li, Kushal Panchal, Naveen Kumar Vasudevan, Roozbeh Mafi, Li Xi

Bibliographic record

VenueChemRxiv · 2021
Typepreprint
Languageen
FieldMaterials Science
TopicPolymer Science and PVC
Canadian institutionsCanadian General-Tower (Canada)McMaster University
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsPlasticizerVinyl chlorideMaterials scienceModulusCompatibility (geochemistry)Polyvinyl chlorideChemical engineeringPolymerPolymer chemistryComposite materialEngineeringCopolymer

Abstract

fetched live from OpenAlex

Using all-atom molecular simulation, a wide range of plasticizers for poly(vinyl chlorid) (PVC), including ortho- and tere-phthalates, trimellitates, citrates, and various aliphatic dicarboxylates, are systematically studied. We focus on the effects of plasticizer molecular structure on its performance, as measured by performance metrics including its thermodynamic compatibility with PVC, effectiveness of reducing the material's Young's modulus, and migration rate in the PVC matrix. The wide variety of plasticizer types covered in the study allows us to investigate the effects of seven molecular design parameters. Experimental findings about the effects of plasticizer molecular design are also compiled from various literature sources and reviewed. Comparison with experiments establishes the reliability of our simulation predictions. The study aims to provide a comprehensive set of guidelines for the selection and design of high-performance plasticizers at the molecular level. Molecular mechanisms for how each design parameter influences plasticizer performance metrics are also discussed. Moreover, we report a nontrivial dependence of plasticizer migration rate on temperature, which reconciles seemingly conflicting experimental reports on the migration tendency of different plasticizers.

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 categoriesMeta-epidemiology (narrow)
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 score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.273
Teacher spread0.245 · 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.

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

Citations3
Published2021
Admission routes2
Has abstractyes

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