MétaCan
Menu
Back to cohort
Record W3097530535 · doi:10.1021/acs.macromol.0c02115

Simple and Accurate Calibration of the Flory–Huggins Interaction Parameter

2020· article· en· W3097530535 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMacromolecules · 2020
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlory–Huggins solution theoryPolymerCalibrationDispersityThermodynamicsAsymmetryStatistical physicsMaterials scienceRange (aeronautics)PolymerizationChemistryPhysicsPolymer chemistryQuantum mechanicsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

This paper improves upon a standard method of determining the Flory–Huggins χ parameter, whereby experimental order–disorder transitions (ODTs) of symmetric diblock polymer melts are fit to the mean-field prediction, (χN)ODT = 10.495. The improvement is achieved by switching to an accurate prediction of (χN)ODT from Glaser et al. (Phys. Rev. Lett. 2014, 113, 068302), supplemented with corrections for the small degrees of polydispersity and compositional asymmetry that inevitably exist in real diblock polymers. The first correction is evaluated by simulating polydisperse diblocks over a wide range of invariant polymerization indices, and the second correction is extracted from analogous simulations for compositionally asymmetric diblocks by Ghasimakbari and Morse (Macromolecules 2020, 53, 7399). The resulting calibration method is then demonstrated on 19 different chemical pairs, using previously published experimental data. It provides a considerable increase in accuracy, but yet is nearly as simple to apply as the original version.

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.

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 score0.009
Threshold uncertainty score0.274

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 head0.019
GPT teacher head0.254
Teacher spread0.235 · 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