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Record W2326327326 · doi:10.1149/1.3571973

Improved Model for Nanowire BioFETs on SOI Operating in Electrolyte

2011· article· en· W2326327326 on OpenAlexaff
M. W. Denhoff, D. Landheer

Bibliographic record

VenueECS Transactions · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsNational Research Council CanadaInstitute for Microstructural Sciences
Fundersnot available
KeywordsNanowireSilicon on insulatorElectrolyteMaterials scienceFabricationTransistorOptoelectronicsInsulator (electricity)Finite element methodNanotechnologyPhysicsVoltageElectrodeElectrical engineeringSiliconEngineering

Abstract

fetched live from OpenAlex

Using a readily available finite element code (Freefem++) the performance of nanowire (NW) field-effect transistors used as bio-affinity sensors has been simulated in 2D using realistic models for the semiconductor, gate insulator, Stern layer, and a layer of charged biomolecules (DNA) in electrolyte. The simulations are compared to those published previously for cylindrical NWs suspended in electrolyte. Calculations for Si NWs with circular and trapezoidal cross-section on SOI substrates are compared to assess the relative sensitivities for the devices made during the top-down (cylindrical) and bottom-up (trapezoidal) approach to device fabrication. It is shown that the performance of the trapezoidal structures could be superior, even when compared to cylinders with smaller dimensions. The simulations are compared to recent pH measurements with trapezoidal nanowires and pave the way to improved simulations for DNA and protein attachment.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.418

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 head0.023
GPT teacher head0.269
Teacher spread0.246 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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