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Record W2016334125 · doi:10.3390/polym6020565

Synthesis of Narrow Molecular Weight Distribution Norbornene-Lactone Functionalized Polymers by Nitroxide-Mediated Polymerization: Candidates for 193-nm Photoresist Materials

2014· article· en· W2016334125 on OpenAlexaff
Zi Wang, Milan Marić

Bibliographic record

VenuePolymers · 2014
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsCopolymerPolymer chemistryMaterials scienceStyreneMonomerComonomerPolymerizationNitroxide mediated radical polymerizationPhotoresistPolymerRadical initiatorRadical polymerizationNanotechnology

Abstract

fetched live from OpenAlex

One hundred ninety three-nanometer candidate photoresist materials were synthesized by nitroxide-mediated polymerization (NMP). Statistical copolymerizations of 5-methacryloyloxy-2,6-norboranecarbolactone (NLAM) with 5–10 mol% of controlling co-monomers (which are necessary for controlled polymerizations of methacrylates by NMP with the initiator used) in the feed, such as styrene (ST), p-acetoxystyrene (AcOST), 2-vinyl naphthalene (VN) and pentafluorostyrene (PFS), using the unimolecular BlocBuilder® initiator in 35 wt% dioxane solution at 90 °C were performed. As little as 5 mol% controlling comonomer in the feed was demonstrated to be sufficient to lead to linear evolution of number average molecular weight with respect to conversion up to 50%, and the resulting copolymers had dispersities of ~1.3 in most cases, an attractive feature for reducing line width roughness (LWR) in photoresists. The copolymers generally showed relatively low absorbance at 193 nm, comparable to other 193-nm candidate photoresists reported previously, despite the inclusion of a small amount of the styrenic co-monomers in the copolymer.

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), Insufficient payload (model declined to judge)
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 score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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)0.0080.000

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 head0.004
GPT teacher head0.202
Teacher spread0.198 · 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

Citations15
Published2014
Admission routes1
Has abstractyes

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