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Record W2086974201 · doi:10.1063/1.3050329

Sensitivity of field-effect biosensors to charge, pH, and ion concentration in a membrane model

2008· article· en· W2086974201 on OpenAlexaff
W. R. McKinnon, D. Landheer, G. C. Aers

Bibliographic record

VenueJournal of Applied Physics · 2008
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsInstitute for Microstructural Sciences
Fundersnot available
KeywordsBiomoleculeBiosensorSurface chargeIonSensitivity (control systems)ChemistryMembraneField-effect transistorMoleculePoisson's equationPoisson–Boltzmann equationCharged particleCharge (physics)Chemical physicsOxideAnalytical Chemistry (journal)TransistorMaterials scienceNanotechnologyPhysical chemistryPhysicsChromatographyVoltageElectronic engineering

Abstract

fetched live from OpenAlex

In field-effect transistors used to detect charged biomolecules (BioFETs), the biomolecules form a charged membrane on the transistor surface. In this paper, the one-dimensional Poisson–Boltzmann equation is used to calculate the charge sensitivity (the sensitivity of the BioFET to changes in biomolecule charge), ion sensitivity (to changes in ion concentration of the solution), or pH sensitivity (to changes in pH of the solution), both analytically and numerically, and the results are compared to models where the charged molecules are represented as an infinitely thin plane. Complexation of ions with the oxide surface is shown to have a negligible effect on parameters typical of devices, but the layer used to tether the charged molecules to the surface could modify the sensitivity considerably.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.326

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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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

Citations28
Published2008
Admission routes1
Has abstractyes

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