MétaCan
Menu
Back to cohort
Record W2064723636 · doi:10.1039/c3ra40768c

Investigation of the electrical stability of Si-nanowire biologically sensitive field-effect transistors with embedded Ag/AgCl pseudo reference electrode

2013· article· en· W2064723636 on OpenAlexaff
Taiuk Rim, Kihyun Kim, Nanki Hong, Wooree Ko, Chang‐Ki Baek, Sangmin Jeon, M. Jamal Deen, M. Meyyappan, Yoon‐Ha Jeong, Jeong‐Soo Lee

Bibliographic record

VenueRSC Advances · 2013
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsMcMaster University
FundersNational IT Industry Promotion Agency
KeywordsElectrodeReference electrodeMaterials scienceMicrofabricationNanowireField-effect transistorDetection limitBiosensorElectrochemistryOptoelectronicsTransistorNanotechnologyAnalytical Chemistry (journal)VoltageFabricationChemistryElectrical engineeringChromatography

Abstract

fetched live from OpenAlex

We report on the electrical stability of Si-nanowire biologically sensitive field-effect transistors (BioFETs) fabricated using conventional microfabrication technique, with an embedded Ag/AgCl pseudo-reference electrode (pRE) formed by an electrochemical method. The open-circuit potential (OCP) characteristics between the pRE and a commercial reference electrode have been measured in order to evaluate the influence of the pRE potential on the device performance. In a pH sensing mode, the fabricated pRE follows the applied potential accurately with a small offset value of below 6 mV for pH in the range of 4 to 10. The BioFET was also used for the detection of alpha fetoprotein (AFP) with a detection limit of 10 pg mL−1 and the corresponding OCP fluctuation of the pRE was less than 1.5 mV, independent of the AFP concentrations. These results suggest that the Si-NW BioFETs with the embedded Ag/AgCl pRE are very promising for reliable biosensing applications.

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 score0.015
Threshold uncertainty score0.308

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 head0.210
Teacher spread0.200 · 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

Citations20
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueRSC AdvancesSame topicNanowire Synthesis and ApplicationsFrench-language works237,207