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Record W2170708728 · doi:10.1149/1.3646929

Comparative Electrochemical Investigation of Pt, Au and Ti Electrodes on Liquid Crystal Polymer for the Application of Neuromuscular Prostheses

2011· article· en· W2170708728 on OpenAlexaff
Saba Mohtashami, Matiar R. Howlader, Thomas E. Doyle

Bibliographic record

VenueECS Transactions · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceElectrodeDielectric spectroscopyCapacitanceSurface roughnessSurface finishCyclic voltammetryComposite materialElectrical impedanceElectrochemistryLayer (electronics)EvaporationNanotechnologyChemistryElectrical engineering

Abstract

fetched live from OpenAlex

This paper studies the electrochemical impedance of Platinum (Pt), Gold (Au), and Titanium (Ti) deposited on liquid crystal polymer (LCP) to understand charge transfer mechanism of implantable electrodes for neuromuscular electrical stimulation. Electrodes are fabricated through e-beam evaporation and characterized using electrochemical impedance spectroscopy (EIS) and atomic force microscopy (AFM) measurements. A theoretical model is proposed to explain physical functionalities. The results demonstrate as the size of electrodes increases, higher conductivity and double layer capacitance are obtained. In neuromuscular stimulation frequencies, Pt electrodes offer the best conductivity followed by Ti and Au respectively. This material dependence of impedance magnitude is related to the surface morphology of the electrodes and is assessed by AFM. Deposition pressure dependence of Ti electrodes on the impedance is observed due to change of surface roughness and double layer capacitor. This study addresses the interface impedance of implanted electrodes and permits further development of neuromuscular prostheses.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.028
GPT teacher head0.233
Teacher spread0.205 · 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

Citations11
Published2011
Admission routes1
Has abstractyes

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