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Record W1984254159 · doi:10.1063/1.2814023

Thermal quenching sample chamber for grazing incidence small angle x-ray scattering studies of polymer films

2007· article· en· W1984254159 on OpenAlexaff
M. A. Singh, Michael N. Groves, Matthew S. Muller, I. J. Stahlbrand, Detlef‐M. Smilgies

Bibliographic record

VenueReview of Scientific Instruments · 2007
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsQueen's University
FundersU.S. Public Health Service
KeywordsMaterials scienceLamellar structureScatteringSiliconSubstrate (aquarium)ThermalGrazing-incidence small-angle scatteringQuenching (fluorescence)Small-angle X-ray scatteringPolymerOpticsComposite materialSmall-angle neutron scatteringNeutron scatteringOptoelectronicsThermodynamicsPhysicsFluorescence

Abstract

fetched live from OpenAlex

The second generation of a sample chamber designed for in situ measurement of temperature- and time-dependent polymer film nanostructure using the method of grazing incidence small angle x-ray scattering is presented. An increased operating temperature limit (from 260 to 400 degrees C) with precise control (+/-0.1 degrees C) at fixed temperatures as well as a fourfold increase in maximum instantaneous cooling rate (up to 73 degrees C/s) relative to the first generation chamber [M. N. Groves et al, J. Appl. Crystallogr. 39, 120 (2006)] are reported. Thermal quenches from 220 to 90 degrees C are shown to be reproducible to within +/-1 degrees C of the final temperature. Experimental tests on spin-coated films of symmetric diblock styrene-butadiene copolymer demonstrate the ability to resolve the kinetics of orientation of lamellar domains parallel to the silicon substrate, distinct from the initial formation of randomly oriented lamellar domains immediately following the thermal quench.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.042
GPT teacher head0.313
Teacher spread0.271 · 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 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

Citations2
Published2007
Admission routes1
Has abstractyes

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