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Record W3021969131 · doi:10.1149/09705.0165ecst

Readout Circuit Design Using Experimental Data of Line-TFET Devices

2020· article· en· W3021969131 on OpenAlexaff
Walter Gonçalez, Roberto Rangel, João Antônio Martino, Paula Ghedini Der Agopian

Bibliographic record

VenueECS Transactions · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransistorSubthreshold conductionResistorLine (geometry)AmplifierElectrical engineeringCapacitorElectronic circuitLinearityCircuit designPhysicsOptoelectronicsComputer scienceElectronic engineeringVoltageCMOSEngineering

Abstract

fetched live from OpenAlex

By considering the analog characteristics of Line Tunneling Field Effect Transistors (Line-TFETs) that are suitable for small-signal amplification, this paper studies the design of a readout circuit with these devices while making comparisons with conventional MOSFET designs. The results show that the Line-TFET design exhibits high gain and low reading error (51dB open loop gain) while using a simple one-stage amplifier and results in a huge reduction in circuit area by using pseudo feedback resistors that have their differential resistance increased for smaller dimensions, achieving up to 50Gohm in a 120nm x 100nm device. This enables cutoff frequencies below 1Hz while using nanometer devices and smaller capacitors. Moreover, the readout circuit achieves 33nW of power consumption even though the Line-TFET devices are not biased in the subthreshold regime.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.695

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 head0.242
GPT teacher head0.317
Teacher spread0.075 · 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 designSimulation or modeling
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
Published2020
Admission routes1
Has abstractyes

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