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A Time-Based CMOS Readout Circuit for Amperometric Biosensors

2023· article· en· W4382536802 on OpenAlexaff
Hanieh Ashrafirad, Virgilio Valente

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPotentiostatCMOSComparatorElectronic engineeringMiniaturizationComputer scienceDynamic rangeElectrical engineeringMultiplexingTransistorVoltageComputer hardwareEngineeringPhysics

Abstract

fetched live from OpenAlex

Miniaturization of electrochemical sensing devices for point-of-care, wearable and implantable diagnostics relies on CMOS potentiostat readouts that offer rapid and accurate test results. Conventional CMOS potentiostats are based on traditional analog blocks such as op amps and comparators, with a performance penalty in terms of power consumption and dynamic range. Time-based readout architectures offer unique advantages to achieve ultra-low power and low voltage operation without sacrificing small area and resolution. In this paper, we present the design of a CMOS potentiostat circuit with a current-mode time-based SAR ADC readout. The simulated results suggest that the readout channel can achieve an estimated energy efficiency of 1.5 pJ/bit from a 1.8 V supply. The proposed architecture can be readily scaled and programmed for a wide range of input currents, which makes it suitable for multiplexed multi-analyte systems.

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 categoriesInsufficient payload (model declined to judge)
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 score0.899
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.030
GPT teacher head0.218
Teacher spread0.188 · 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.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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