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Record W2025565289 · doi:10.1149/2.004307jes

The Use of UV-Cross-Linkable Di-Block Copolymers as Functional Reaction Surfaces for Microelectrode Arrays

2013· article· en· W2025565289 on OpenAlexfundno aff
Libo Hu, Matthew D. Graaf, Kevin D. Moeller

Bibliographic record

VenueJournal of The Electrochemical Society · 2013
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsnot available
FundersEgg Farmers of CanadaNational Institutes of HealthNational Science Foundation
KeywordsCopolymerPolymerMicroelectrodeElectrochemistryMaterials scienceMultielectrode arrayCombinatorial chemistryPolymer chemistryElectrodeChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Three types of UV-cross-linkable di-block copolymers have been developed as coatings for microelectrode arrays. All three polymers share the same PCEMA block for the cross-linking reaction. The PBrSt-b-CEMA polymer was shown to be compatible with a series of Pd(0)- and Cu(I)-catalyzed reactions. It was compatible with electrochemical signaling experiments, although it showed non-specific binding to proteins at higher concentrations. In order to study weak binding interactions, PCEMA-b-PPEGMA was developed to reduce non-specific binding. However, it was shown not to be a stable enough surface for array-based reactions. In an effort to make a tunable surface, PCEMA-b-BSt was made and was shown to be compatible with Suzuki reactions on the array, however, the inability of achieving a stable current deemed it incompatible with signaling experiments. The use of a pinacol protected PCEMA-b-pBSt polymer solved these issues. The protected polymer could be site-selectively deprotected, transesterified, and functionalized with Cu(II)-catalyzed reactions. It is also compatible with the electrochemical impedance experiments used to signal binding events on the arrays.

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 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 score0.395

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 studies0.0010.000
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 head0.025
GPT teacher head0.263
Teacher spread0.238 · 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.

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

Citations22
Published2013
Admission routes1
Has abstractyes

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