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Synergistic Polydopamine/Graphene Oxide Hybrids: Elevating Electrochemical Performance

2025· article· en· W4405996428 on OpenAlexaff
Buşra Özlü, Saimon Moraes Silva, Simon E. Moulton, Bong Sup Shim

Bibliographic record

VenueACS electrochemistry. · 2025
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsDiscovery Centre
FundersMinistry of Trade, Industry and EnergyAustralia-Korea Foundation
KeywordsGrapheneOxideElectrochemistryMaterials scienceHybridNanotechnologyChemistryElectrodeMetallurgyBiologyBotany

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Melanin, a natural biopolymer with a conjugated backbone, stands out as a promising candidate for bioelectronics owing to its redox activity, metal ion chelation, hydration-dependent electrical response, wet adhesion, potential electronic transport, anti-inflammatory properties, and excellent thermal stability. In this study, we explore the impact of hybridizing liquid crystalline graphene oxide (LCGO) into the conductive melanin-like polymer polydopamine (PDA) on the morphology, stability, and synergistic electrochemical performance. Our findings reveal that the gold electrode coated with PDA:LCGO composites exhibit more than two orders of magnitude lower impedance and more than 100 times higher charge storage capacity compared to both bare gold electrodes and those coated with pure PDA. Furthermore, we demonstrate that the morphology and the electrode performance could be tuned by adjusting the synthesis parameters in the PDA:LCGO electrochemical deposition. This PDA:LCGO composite, with its superior electrochemical performance, holds promise for diverse bioelectronics applications ranging from biosensors to implantable bionic interfaces.

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 score0.005
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.235
Teacher spread0.228 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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