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Record W2912140197 · doi:10.1109/iedm.2018.8614713

Highly Performant Integrated pH-Sensor Using the Gate Protection Diode in the BEOL of Industrial FDSOI

2018· article· en· W2912140197 on OpenAlexaff
Getenet Tesega Ayele, S. Monfray, Serge Ecoffey, J-P. Cloarec, Dominique Drouin, A. Souifi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
Fundersnot available
KeywordsOptoelectronicsCMOSDiodeMaterials scienceSensitivity (control systems)FabricationTransistorVoltageElectrical engineeringCurrent (fluid)Electronic engineeringEngineering

Abstract

fetched live from OpenAlex

This is the first demonstration of a CMOS pH-sensor using the gate protection diode of standard FDSOI transistors in the BEOL. The extremely steep switching of the drain current induced by an exploitation of the DIBL effect is used for fabrication of extremely sensitive pH-sensors. The back gate voltage at which the abrupt switching of drain current occurs depends on the potential at the gate protection diode. Integrating the pH sensing film on this diode BEOL metal, the shift depends on the pH value of the liquid which creates a proportional potential. The abrupt switching (as small as 9 mV/decade) of the drain current can give a theoretical maximum sensitivity of 6.6 decade of drain current change per unit pH. In this paper, we report an experimental sensitivity of 1.25 decade/pH which is superior to state-of-the-art CMOS pH sensors which have a maximum sensitivity of 0.9 decade/pH.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002

Distilled classifier scores by category (both heads)

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 head0.055
GPT teacher head0.253
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes1
Has abstractyes

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