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Record W3011725198 · doi:10.1515/epoly-2020-0013

Synthesis of amphiphilic poly(ethylene glycol)-<i>block</i>-poly(methyl methacrylate) containing trityl ether acid cleavable junction group and its self-assembly into ordered nanoporous thin films

2020· article· en· W3011725198 on OpenAlexaff
Yinghua Qi, Akash Nathani, Jianxin Zhang, Zhengji Song, Chandra Shekhar Sharma, Sunil K. Varshney

Bibliographic record

Venuee-Polymers · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCovalent Organic Framework Applications
Canadian institutionsPolymer Source (Canada)
Fundersnot available
KeywordsEthylene glycolNanoporousCopolymerMaterials scienceAtom-transfer radical-polymerizationPolymer chemistryEtherAmphiphileMethacrylateMethyl methacrylateOrganic chemistryPolymerChemistryNanotechnology

Abstract

fetched live from OpenAlex

Abstract A strategy for the synthesis of well defined poly(ethylene glycol)-block-poly(methyl methacrylate) diblock copolymers containing trityl ether acid cleavable junctions is demonstrated. This approach is achieved by using a combination of poly(ethylene glycol) macroinitiator containing a trityl ether end group, which is susceptible to acid cleavage, and atom transfer radical polymerization technique. The trityl ether linkage between blocks can be readily cleaved in solution or in solid phase under very mild acid condition, which has been confirmed by 1H NMR. These diblock copolymers have been used to successfully fabricate nanoporous thin films by acid cleavage of trityl ether junction followed by complete removal of poly(ethylene glycol) block. The fabricated nanoporous thin films may have a wide range of application such as Recessed Nanodisk-array electrode (RNE) or as a template to fabricate nanoelectrode array for senor applications.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.238
Teacher spread0.225 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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