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Record W2589709066 · doi:10.1021/acs.chemmater.7b00181

Patterning of Stretchable Organic Electrochemical Transistors

2017· article· en· W2589709066 on OpenAlex
Shiming Zhang, Hubis Elizabeth, Gaia Tomasello, G. Soliveri, Prajwal Kumar, Fabio Cicoira

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemistry of Materials · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsPolytechnique Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsTransistorElectrochemistryMaterials scienceNanotechnologyThin-film transistorOptoelectronicsElectrodeChemistryElectrical engineeringEngineeringVoltage

Abstract

fetched live from OpenAlex

The fabrication of stretchable electronic devices is presently rather challenging on account of both the limited number of materials showing the desired combination of mechanical and electrical properties and the lack of techniques to process and pattern them. Here we report on a fast and reliable transfer patterning process to fabricate high-resolution metal microelectrodes on polydimethylsiloxane (PDMS) by using ultrathin Parylene films (2 μm thick). By combining transfer patterning of metal electrodes with orthogonal patterning of the conducting polymer poly(3,4-ethylenedioxythiophene) doped with polystyrenesulfonate (PEDOT:PSS) on a prestretched PDMS substrate and a biocompatible “cut and paste” hydrogel, we demonstrated a fully stretchable organic electrochemical transistor, relevant for wearable electronics, biosensors, and surface electrodes to monitor body conditions.

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.

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 score0.001
Threshold uncertainty score0.758

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 studies0.0000.000
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 head0.009
GPT teacher head0.205
Teacher spread0.196 · 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