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Record W2884006966 · doi:10.1149/2.0061812jes

Diazonium-Based Anchoring of PEDOT on Pt/Ir Electrodes via Diazonium Chemistry

2018· article· en· W2884006966 on OpenAlexafffund
Danny Chhin, David Polcari, Côme Bodart-Le Guen, Gaia Tomasello, Fabio Cicoira, Steen B. Schougaard

Bibliographic record

VenueJournal of The Electrochemical Society · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsPolytechnique MontréalUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPEDOT:PSSCovalent bondConductive polymerElectrodeAdsorptionMaterials scienceElectrochemistryPoly(3,4-ethylenedioxythiophene)NanotechnologySurface modificationChemical engineeringBiocompatibilityPolymerPolymerizationAdhesionChemistryPolymer chemistryLayer (electronics)Organic chemistryComposite material

Abstract

fetched live from OpenAlex

ABSTRACT: Conducting polymers, specifically poly (3,4-ethylenedioxythiophene) (PEDOT), have recently been coated onto Pt/Ir electrodes intended for neural applications, such as deep brain stimulation (DBS). This modification reduces impedance, increases biocompatibility, and increases electrochemically active surface area. However, direct electropolymerization of PEDOT onto a metallic surface results in physically adsorbed films that suffer from poor adhesion, precluding their use in applications requiring in vivo functionality (i.e. DBS treatment). In this work, we propose a new attachment strategy, whereby PEDOT is covalently attached to an electrode surface through an intermediate phenylthiophene layer, deposited by electrochemical reduction of a diazonium salt. Our electrodes retain their electrochemical performance after more than 1000 redox cycles, whereas physically adsorbed films begin to delaminate after only 40 cycles. Additionally, covalently attached PEDOT maintained strong adhesion even after 10 minutes of ultrasonication (vs. 10 s for physically adsorbed films), confirming its suitability for long-term implantation in the brain. The simple two-step covalent attachment strategy proposed here is particularly useful for neural applications and could also be adapted to introduce other functionalities on the conducting surface.

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)0.001
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 score0.002
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.242
Teacher spread0.230 · 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

Citations25
Published2018
Admission routes2
Has abstractyes

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