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Record W2317756307 · doi:10.1021/nn201791k

Graphene as Cellular Interface: Electromechanical Coupling with Cells

2011· article· en· W2317756307 on OpenAlex

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.

Bibliographic record

VenueACS Nano · 2011
Typearticle
Languageen
FieldEngineering
TopicGraphene and Nanomaterials Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGrapheneInterfacingMaterials scienceNanotechnologyNanomaterialsCarbon nanotubeCoupling (piping)OptoelectronicsComputer scienceComposite material

Abstract

fetched live from OpenAlex

Interfacing cells with nanomaterials such as graphene, nanowires, and carbon nanotubes is useful for the integration of cellular physiology with electrical read outs. Here we show the interfacing of graphene sheets on the surface of yeast cells, leading to electromechanical coupling between the sheets and the cells. The cells are viable after the interfacing. The response caused by physiologically stressing the cells by exposure to alcohols, which causes a change in cell volume, can be observed in the electrical signal through graphene. The change in the cell volume leads to straining of the sheets, forming wrinkles which reduce the electrical conductivity. As the dynamic response of the cell can be observed, it is possible to differentiate between ethanol, 2-propanol, and water. We believe this will lead to further development of cell-based electrical devices and sensors.

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 score0.012
Threshold uncertainty score0.534

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)0.0000.000

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 head0.010
GPT teacher head0.187
Teacher spread0.178 · 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