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Record W2776125858 · doi:10.1021/acs.macromol.7b01640

Scale-Dependent Miscibility of Polylactide and Polyhydroxybutyrate: Molecular Dynamics Simulations

2017· article· en· W2776125858 on OpenAlexaff
Artyom D. Glova, Stanislav G. Falkovich, Daniil I. Dmitrienko, Alexey V. Lyulin, Sergey V. Larin, Victor M. Nazarychev, Mikko Karttunen, Sergey V. Lyulin

Bibliographic record

VenueMacromolecules · 2017
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsWestern University
FundersRussian Academy of SciencesLomonosov Moscow State UniversityMinistry of Education and Science of the Russian Federation
KeywordsMiscibilityPolyhydroxybutyrateMolecular dynamicsGlass transitionMaterials scienceMicrosecondThermodynamicsSpinodal decompositionScale (ratio)PolymerPolymer chemistryChemical engineeringChemical physicsChemistryPhase (matter)Computational chemistryOrganic chemistryComposite materialPhysics

Abstract

fetched live from OpenAlex

Miscibility of polylactide (PLA) and polyhydroxybutyrate (PHB) is studied by the microsecond atomistic molecular dynamics (MD) simulations for the first time. The model and the simulation protocol were confirmed through comparison of the glass transition temperature ( T g ) with experimental data. It was established that PLA and PHB are miscible on the basis of the Flory–Huggins theory. Analysis of the mobilities of PLA and PHB subchains revealed that the blends have two transitions to a glassy state at the length scale of a few Kuhn segments, which is in line with the predictions of the self-concentration model. At the same time at the larger length scale a single transition to a glassy state was observed, suggesting scale dependence of PLA and PHB miscibility. This scale dependence was confirmed through the evaluation of the interchain pair correlation functions.

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 score0.014
Threshold uncertainty score0.489

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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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

Citations72
Published2017
Admission routes1
Has abstractyes

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