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Record W2512482161 · doi:10.1002/mren.201600029

Synthesis of Narrow Molecular Weight Distribution Copolymers for ArF Photoresist Materials by Nitroxide Mediated Polymerization

2016· article· en· W2512482161 on OpenAlexafffund
Zijun Wang, Kevin Wylie, Milan Marić

Bibliographic record

VenueMacromolecular Reaction Engineering · 2016
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCopolymerPolymer chemistryComonomerPolymerizationNitroxide mediated radical polymerizationAcrylonitrileMethyl methacrylateMethacrylateStyreneMolar mass distributionMaterials sciencePhotoresistRadical polymerizationPolymerDispersityChemistryOrganic chemistryNanotechnology

Abstract

fetched live from OpenAlex

ArF candidate photoresist polymers have been synthesized by nitroxide mediated polymerization (NMP). Statistical copolymerizations of α‐gamma butyrolactone methacrylate, 3‐hydroxy‐1‐adamantyl methacrylate, and 2‐methyl 2‐adamantyl methacrylate with 5–10 mol% of controlling comonomers (i.e., styrene, p‐acetoxystyrene, 2‐vinyl naphthalene, acrylonitrile, and pentafluorostyrene), which are necessary for controlled polymerization of methacrylates by NMP with the unimolecular alkoxyamine initiator BlocBuilder, have been used. As little as 5 mol% controlling comonomer in the feed is demonstrated to be sufficient to produce linear evolution of number average molecular weight against conversion ( X ) up to X = 0.7 for relatively low target degrees of polymerization. All of the resulting copolymers have relatively low dispersities and show relatively low absorbance at 193 nm, comparable to other 193 nm candidate photoresists reported previously, with the exception of VN‐containing copolymer. image

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 score0.271
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.002
GPT teacher head0.181
Teacher spread0.179 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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